Ecommerce MGMT, Author at Ecommerce Management Education

Dec 26 2025

The 7 Best Landing Page Builders For 2026 via @sejournal, @MattGSouthern

Landing pages are a core part of the user journey, influencing ad performance, conversion rates, and how effectively you can test, personalize, and scale your marketing.

Lead generation isn’t just about driving traffic; it’s about delivering seamless, trustworthy landing page experiences that convince visitors to take the next step. Even the best ad campaigns can fall flat if your landing pages aren’t designed to convert.

In this article, we will compare the top platforms that help marketers create fast, compelling, conversion-focused pages and then walk you through how to choose a landing page builder that fits your goals,

While this is, by no means, an exhaustive list of considerations, it’s a starting point to help you choose a landing page builder that makes sense for your business needs.

Now, let’s look at seven of the best landing page builders to choose from.

Pure Landing Page Builders

1. Unbounce

Unbounce is a leading landing page builder renowned for its focus on conversion rate optimization (CRO). Its website promises to help you “launch landing pages faster, accelerate results” with a no-code approach augmented by AI-powered tools.

It offers a suite of advanced tools, such as A/B testing, dynamic text replacement, custom code, and the Smart Traffic (AI optimization) system, which optimizes visitor flow to the highest-converting page variant based on user behavior and characteristics.

It also focuses on features that can help you boost your lead gen efforts, such as opt-in email pop-ups and sticky banners.

With its customizable conversion-optimized responsive templates and drag-and-drop builder, Unbounce makes it easy to create landing pages that are both engaging and effective.

Compared to some other options on this list, Unbounce is a particularly robust platform with tons of customization and integrations, and the price point reflects that.

As a premium offering with a steeper learning curve, it might not be the best for beginners, but its AI-powered features and conversion-focused tools make it a formidable tool for achieving your goals.

Pros:

Advanced A/B testing and AI-driven optimization.
Large selection of responsive templates.
Integrated features for enhancing lead capture.

Cons:

Higher price point than some other builders, which might not work for those with limited budgets.
Complex setup and steeper learning curve for new users.
Some customization limitations, such as not being able to mix and match page template sections.

Pricing

The Build plan starts at $99/month (billed monthly) and covers unlimited conversions, one root domain, and up to 20,000 monthly unique visitors.
Other paid plans range from $149/month (billed monthly) to $249/month (billed monthly), with a custom price available for their Agency plan. There are cheaper options for annual billing.

What Users Say

Unbounce is known for ease of use and quality. GhostProsaic praised the tool, saying “unless you’re coding the entire page from scratch, and hosting it yourself, the upsides of using something like Unbounce outweigh the downsides of having to do a custom build.”

In response to a r/PPC poster asking if they use Unbounce, user PaidSearchHub says, “We use Unbounce and it also has a native integration with our lead intelligence platform. Sometimes, ya get what ya pay for.”

But it seems the pricing is higher-end vs. the rest. Others like QuantumWolf99 declared that, “Most agencies have moved away from Unbounce/Instapage because the pricing doesn’t justify the performance difference anymore. WordPress with Elementor or custom Webflow builds usually convert just as well at a fraction of the cost.”

2. Leadpages

Best for: Small businesses and entrepreneurs looking to generate sales.

Need a landing page that will help you generate sales? Consider taking a look at Leadpages.

Its strength lies in its user-friendly, drag-and-drop editor and an extensive collection of templates that streamline the page-building process. Plus, according to the Leadpages website, it’s a platform that converts five times better than the industry average.

Leadpages offers CRO tools, real-time analytics, and A/B testing capabilities, enabling users to effectively enhance page performance.

Its various widgets let you add videos, images, forms, and even payment integrations directly to your landing pages, making it a versatile tool for businesses that want to combine content with sales functionality.

On top of all this, Leadpages now includes an AI Engine for creating headlines and images and an AI writing assistant with full access available to Pro accounts, which can help you write better content.

Pros:

Intuitive no-code editor and easy payment integration.
Comprehensive A/B testing and real-time analytics.
Extensive template library with over 200+ options.

Cons:

Higher cost compared to some alternatives.
Limited ecommerce features.
Some users report mobile responsiveness issues.

Pricing:

The standard plan starts at $49/month (billed monthly) for one custom domain, unlimited traffic, and leads.
More advanced features are available in higher-tier plans, which start at $99/month (billed monthly). You can save 25% when billed yearly.

What Users Say

Leadpages is recommended primarily for conversion. When asked on subreddit r/Solopreneur about Leadpages vs. Wix, user Straight_Tooth4294 replied, “I’d honestly go with Leadpages or Instapage – they’re built for conversion and specifically for landing pages.” When asked if realtors use the tool on r/marketing, user patrick24601 replied, “Leadpages is good for landing/squeeze pages. Most realtors don’t need those.”

But other users have expressed dismay that Leadpages raised their rates and doesn’t have great customer service. Redditor constantineinamerica wrote, “I would favor Wix or Unbounce over Leadpages. I’ve known lots of people who have had terrible customer service experiences with Leadpages.” and user Abroja seconded, sharing, “Been with Leadpages for over 5 years. They just raised the rates huge overnight but it’s ok because they ‘sent us an email’.”

3. Instapage

Best for: Large businesses, marketing teams, or agencies that require collaboration and advanced optimization features.

If you’re seeking a more high-end landing page platform, Instapage might be the one for you. It offers advanced features tailored for professional marketing teams and agencies with a need to create optimized landing pages at scale.

In addition to a drag-and-drop builder and plenty of high-quality templates, Instapage offers a bevy of features, including advanced cloud-based team collaboration tools, heatmaps for user engagement analysis, robust A/B testing capabilities, AI-generated content creation, and more.

One of its standout features is Instablocks & Global Blocks, which lets users create custom page components that can be easily reused across projects, and then update hundreds or thousands of pages in one go.

Instapage supports advanced marketing goals with features like AdMap, which lets you view your overall campaigns, ad groups, and ads, then align them with relevant landing pages. Plus, its mobile-friendly design ensures a fast, seamless user experience.

While Instapage offers a premium experience with its comprehensive set of tools and features, its higher price point and complex functionalities may be a barrier for smaller businesses or those new to landing page optimization.

Pros:

Extensive customization with a library of professional templates.
Instablocks for efficient design and asset reuse.
Effective team collaboration features.

Cons:

Premium pricing will be a barrier for many businesses.
Steep learning curve for utilizing advanced features.
Limitations in reporting and visitor tracking for lower-tier plans.

Pricing:

The Create plan starts at $99/month (billed monthly). Plans cost up to 20% less if paid monthly vs. annually, with a 14-day free trial.
Customers will need to upgrade to a customized Convert plan to access more advanced features, such as root domain publishing, heatmaps, and more.

What Users Say

While Instapage’s pricing is on the steeper side, especially if you’re just getting started, it is considered one of the best platforms for high-converting landing pages, according to user JeanetteChapman, “It’s really geared more toward businesses running serious paid traffic campaigns where optimizing every click matters. If you’re spending at least a few thousand a month on ads, it’s worth it.”

One user named Rina-Lanaudiere-5, who made the switch from Unbounce to Instapage, was pleased with its A/B testing feature, “We’ve checked them out, quite quickly realized Instapage is much more obvious and easy for all to handle and made the move, that’s it. Doing A/B testing all the time, super handy.”

4. Landingi

Best for: From online shops with international customers to enterprise businesses seeking a versatile landing page solution with a wide range of features.

If you’re in the market for versatility, Landingi is worth investigating. Landingi offers a flexible, comprehensive landing page builder with robust features, including an advanced editor, pop-ups, A/B testing, and a library with hundreds of templates.

Its Composer AI feature lets you skip writer’s block and quickly fill your pages with a ready-to-publish structure. With Smart Sections, you can also easily update specific page elements across multiple designs, saving time and headaches.

One of their attractive features is that you can translate your landing pages into 29 languages to scale your campaigns worldwide.

Designed to serve businesses of all sizes, Landingi’s simple, drag-and-drop builder can help you create and optimize various types of landing pages – and if you have any HTML and CSS knowledge, it can be a pretty impressive editor.

Landingi is a particularly strong choice for international businesses looking to target different customer segments with unique landing pages. With over 170 integrations with tools, including payment gateways like Stripe, it’s a great choice for companies looking to sell products.

While its rich feature set can be overwhelming for newcomers, creating pages might take a bit longer than on other platforms, the level of customization and control it offers makes Landingi one of the best landing page builders out there.

Pros:

Extensive template library with 400+ customizable options.
Powerful editing capabilities with Smart Sections for efficient design.
Broad integration with various apps, including payment systems.

Cons:

Steeper learning curve for beginners.
Potentially longer time to create landing pages compared to simpler platforms.

Pricing:

Landingi offers a free option with five active landing pages, 100 conversions, and 100 visits per month.
The Lite plan starts at $29/month (billed monthly) and includes 10 active landing pages, unlimited conversions, 5,000 visits per month, and one custom domain. Paid plans go up to $1,399 with a 14-day free trial for all plans.
Landingi also offers Professional and Enterprise tiers with more advanced features and capabilities.

What Users Say

User dejka_writes recommends this platform for businesses working at scale: “We were pumping out dozens of landing pages for ppc and webinars every month, and the editor didn’t choke even when pages got a bit heavy. I personally loved the smartsections thing because it saved hours when updating multiple pages at once.”

However, there are still not many reviews about it on Reddit, with one unanswered user, islandviewgirls, still left wondering and posting about it, stating, “For price point and ease of use, I really like the Landingi platform, but I don’t see much here on Reddit about it. They are dominant in Europe so perhaps that’s why.”

Full Site Builders That Include Landing Pages

5. Wix

Best for: Individuals and small businesses seeking creative control without advanced coding.

Now for something much more accessible: Wix is renowned for its user-friendly platform, which is ideal for creating attractive landing pages with minimal effort.

Like other options on this list, Wix offers an accessible drag-and-drop editor and a range of existing templates to help users craft aesthetically pleasing and functional landing pages.

Wix’s platform has a reputation for being particularly beginner-friendly, with a low learning curve and a free plan to help new users get started without any upfront investment.

For those focused on ecommerce, Wix offers specific features to build landing pages that showcase products and promotions and supports over 100 payment solutions.

While it offers a free starter plan, accessing more advanced functionalities and removing Wix ads requires upgrading to a paid subscription.

Wix’s balance of user-friendly design tools, ecommerce support, and cost-effective pricing makes it a favorable option for those new to web design or businesses needing straightforward, visually appealing landing pages.

Pros:

User-friendly with an intuitive drag-and-drop interface.
Free plan available, making it accessible for beginners.
Ecommerce capabilities with extensive payment integration.

Cons:

Advanced features and an ad-free experience require a paid plan.
Potential limitations in customization for complex requirements.
Site speed may decrease with more intricate designs.

Pricing:

A free plan is available, but it includes Wix branding and lacks more advanced features like payments.
Paid plans start at $17/month and offer additional features, including storage space; only the Business Elite option at $159 offers unlimited storage.

What Users Say

Wix has been praised for its ease of use; its drag-and-drop functionality with templates is highly useful, especially for those who can’t afford to hire a web designer or don’t know how to build from scratch. And according to a user named chmillout, who switched to Wix, said: “[I] think Wix is hard if you will [build] a website from scratch, and easy if you choose a template.”

However, there are complaints about its inconsistencies in scaling, as user cchurchill1985 commented on a poster who was being interviewed by Wix, “Can you tell them to add ‘scale proportionally’ to it?”

Some users have complained about substantial price increases, like poster chii-x3. Also, keep in mind a difficult migration, like thefanum explains, if you choose to leave the platform: “So if you build with them, then decide you want to take your website elsewhere (a simple process with normal hosts), you get to redo your entire website from scratch. Because you don’t own the code, they do.”

6. Elementor

Best for: WordPress users looking for a powerful and intuitive landing page builder.

If you’re a WordPress user, you’ll want to know about Elementor.

It’s a mainly WordPress page builder that’s gained popularity for its flexibility, comprehensive customization, and user-friendly interface.

Elementor allows users to design dynamic, detailed landing pages in WordPress. This feature makes it the perfect choice for WordPress users who want to extend their website’s functionality with sleek landing pages that maintain a consistent look and feel with their existing content.

Its real-time editing features provide immediate feedback on design changes without coding.

It also offers dozens of designer-made templates to choose from. You can add custom forms and pop-ups to your landing page, save page components for reuse, and seamlessly integrate with your customer relationship management (CRM) tools to create a powerful customer experience.

While Elementor offers a ton in terms of design flexibility and integration, it’s important to note that it’s exclusively for WordPress users and can be resource-intensive, which might impact site performance, especially on more complex websites.

Pros:

Advanced customization and design flexibility.
Real-time editing and instant feedback.
Seamless WordPress integration.

Cons:

Exclusively for WordPress users.
Potentially impacts site performance due to resource intensity.

Pricing:

Free version with limited functionality.
Paid versions of the Elementor plugin (assuming you are already a WordPress user and don’t need the full hosting package or WooCommerce bundles) start at $4.99/month billed annually (around $60 for the base plan) and include advanced features and support.

What Users Say

There is a definite learning curve with Elementor, but graphic designers like FeedMeMoreOranges love it, exclaiming, “I know my way around html/css but Elementor does the job well without having to develop a full site from the bottom up.”

However, some users like tracedef say, “It’s code and resource-heavy, which can lead to performance issues and higher requirements for memory at the server level. Poor hosting will compound these issues.”

Creator-Focused Simple Pages

7. Carrd

Best for: Simple projects, personal use, and small budgets.

Looking for a great landing page builder that won’t break the bank? Look no further than Carrd.

Carrd is a streamlined landing page builder that lets you create single-page websites quickly and easily. It’s designed for simplicity, making it ideal for anyone who wants to quickly create a webpage without building a multi-page site.

Think portfolios, personal profiles, project presentations, and small business showcases.

Carrd’s user-friendly interface and selection of themes allow users to create sleek pages in the blink of an eye without even needing an account – you can just visit the website, pick a theme, and get started. However, you will need to sign up to save or publish your site.

It balances simplicity and functionality to help you craft pages that are clean, focused, and responsive across all devices. If you’re just testing the waters or working with slim budgets, this is the right tool for you.

Pros:

Extremely affordable, with a free tier available.
Intuitive and user-friendly interface.
Responsive design.
Fast and lightweight, making it ideal for quick and simple sites.

Cons:

Limited to single-page websites.
Restrictive layouts/themes, which limit creative freedom.
Lacks advanced features and integrations found in more comprehensive builders.

Pricing:

Carrd’s free basic plan allows you to launch three sites with Carrd branding to .carrd.co domains.
Paid plans range from $9 to $49 per year and offer additional features such as no Carrd branding, custom domains, and Google Analytics support (depending on your membership tier).

What Users Say

Its simplicity is what users love about it, making it the best platform to try out ideas for purely one-page landing sites, according to a user named readingisfun, and they further exclaim, “SO MUCH EASIER than WordPress (without the Search capability). I LOVE CARRD. I hope you give it a try and tell us what you think.”

However, for those seeking more complex functions for analytics, as Alternative-Put-9978 puts it well: “It lets you add a couple of meta tags on Pro and a GA4 tag. but that’s about it. it does not do anything complex, it’s more a landing page type site or for trying out ideas. there is no database backend…”

Choosing The Right Landing Page Builder For Your Business

To help you choose between the top options, here are some considerations while you make a decision:

Marketing Objectives: What’s your goal? Is it to have readers sign up for your newsletter, generate leads for your product, or promote your product launch? Page builders have different use cases, so choose one that aligns with your vision.
Ease Of Use: If you are a beginner with no coding knowledge, you may want a simple drag-and-drop editor and ready-to-use templates. Or it could be that you’re looking for something that can be tweaked with your years of coding experience. Whichever one it may be, it should be fit for purpose.
Integration Needs: Do you want your landing pages to integrate with other software or tools you already use for your CRM or email marketing, enabling automation? Or are you starting from scratch and are open to more affordable builders without them?
SEO Features: For some, going the extra mile to add meta tags and alt text to images to enhance accessibility is highly important for discovery. You may also want one that offers A/B testing and heat mapping to know exactly what to optimize to boost conversions.
Mobile Optimization: It’s essential that your landing pages cater to mobile users, so make sure your builder considers that with features like responsive design.
Budget: Unfortunately, budget matters. Landing page builders come with various price tags depending on their capabilities and features. Make sure you’re working within your budget.

There’s A Landing Page Platform To Help You Convert Visitors

Choosing the right landing page builder for your business can significantly impact your marketing success, but the decision depends on your specific goals, needs, and budget.

As we’ve explored, each tool has unique strengths and caters to different aspects of the landing page creation and optimization process.

Whether you’re looking for advanced design capabilities, a client-friendly, user-friendly interface, or specific functionalities like CRO or SEO plugins baked into it, the right platform can not only streamline your landing page design process but also convert visitors into loyal customers.

More Resources:

Featured Image: Sammby/Shutterstock

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Dec 26 2025

AI Wrapped: The 14 AI terms you couldn’t avoid in 2025

If the past 12 months have taught us anything, it’s that the AI hype train is showing no signs of slowing. It’s hard to believe that at the beginning of the year, DeepSeek had yet to turn the entire industry on its head, Meta was better known for trying (and failing) to make the metaverse cool than for its relentless quest to dominate superintelligence, and vibe coding wasn’t a thing.

If that’s left you feeling a little confused, fear not. As we near the end of 2025, our writers have taken a look back over the AI terms that dominated the year, for better or worse.

Make sure you take the time to brace yourself for what promises to be another bonkers year.

—Rhiannon Williams

1. Superintelligence

a jack russell terrier wearing glasses and a bow tie

As long as people have been hyping AI, they have been coming up with names for a future, ultra-powerful form of the technology that could bring about utopian or dystopian consequences for humanity. “Superintelligence” is that latest hot term. Meta announced in July that it would form an AI team to pursue superintelligence, and it was reportedly offering nine-figure compensation packages to AI experts from the company’s competitors to join.

In December, Microsoft’s head of AI followed suit, saying the company would be spending big sums, perhaps hundreds of billions, on the pursuit of superintelligence. If you think superintelligence is as vaguely defined as artificial general intelligence, or AGI, you’d be right! While it’s conceivable that these sorts of technologies will be feasible in humanity’s long run, the question is really when, and whether today’s AI is good enough to be treated as a stepping stone toward something like superintelligence. Not that that will stop the hype kings. —James O’Donnell

2. Vibe coding

Thirty years ago, Steve Jobs said everyone in America should learn how to program a computer. Today, people with zero knowledge of how to code can knock up an app, game, or website in no time at all thanks to vibe coding—a catch-all phrase coined by OpenAI cofounder Andrej Karpathy. To vibe-code, you simply prompt generative AI models’ coding assistants to create the digital object of your desire and accept pretty much everything they spit out. Will the result work? Possibly not. Will it be secure? Almost definitely not, but the technique’s biggest champions aren’t letting those minor details stand in their way. Also—it sounds fun! — Rhiannon Williams

3. Chatbot psychosis

One of the biggest AI stories over the past year has been how prolonged interactions with chatbots can cause vulnerable people to experience delusions and, in some extreme cases, can either cause or worsen psychosis. Although “chatbot psychosis” is not a recognized medical term, researchers are paying close attention to the growing anecdotal evidence from users who say it’s happened to them or someone they know. Sadly, the increasing number of lawsuits filed against AI companies by the families of people who died following their conversations with chatbots demonstrate the technology’s potentially deadly consequences. —Rhiannon Williams

4. Reasoning

Few things kept the AI hype train going this year more than so-called reasoning models, LLMs that can break down a problem into multiple steps and work through them one by one. OpenAI released its first reasoning models, o1 and o3, a year ago.

A month later, the Chinese firm DeepSeek took everyone by surprise with a very fast follow, putting out R1, the first open-source reasoning model. In no time, reasoning models became the industry standard: All major mass-market chatbots now come in flavors backed by this tech. Reasoning models have pushed the envelope of what LLMs can do, matching top human performances in prestigious math and coding competitions. On the flip side, all the buzz about LLMs that could “reason” reignited old debates about how smart LLMs really are and how they really work. Like “artificial intelligence” itself, “reasoning” is technical jargon dressed up with marketing sparkle. Choo choo! —Will Douglas Heaven

5. World models

For all their uncanny facility with language, LLMs have very little common sense. Put simply, they don’t have any grounding in how the world works. Book learners in the most literal sense, LLMs can wax lyrical about everything under the sun and then fall flat with a howler about how many elephants you could fit into an Olympic swimming pool (exactly one, according to one of Google DeepMind’s LLMs).

World models—a broad church encompassing various technologies—aim to give AI some basic common sense about how stuff in the world actually fits together. In their most vivid form, world models like Google DeepMind’s Genie 3 and Marble, the much-anticipated new tech from Fei-Fei Li’s startup World Labs, can generate detailed and realistic virtual worlds for robots to train in and more. Yann LeCun, Meta’s former chief scientist, is also working on world models. He has been trying to give AI a sense of how the world works for years, by training models to predict what happens next in videos. This year he quit Meta to focus on this approach in a new start up called Advanced Machine Intelligence Labs. If all goes well, world models could be the next thing. —Will Douglas Heaven

6. Hyperscalers

Have you heard about all the people saying no thanks, we actually don’t want a giant data center plopped in our backyard? The data centers in question—which tech companies want to built everywhere, including space—are typically referred to as hyperscalers: massive buildings purpose-built for AI operations and used by the likes of OpenAI and Google to build bigger and more powerful AI models. Inside such buildings, the world’s best chips hum away training and fine-tuning models, and they’re built to be modular and grow according to needs.

It’s been a big year for hyperscalers. OpenAI announced, alongside President Donald Trump, its Stargate project, a $500 billion joint venture to pepper the country with the largest data centers ever. But it leaves almost everyone else asking: What exactly do we get out of it? Consumers worry the new data centers will raise their power bills. Such buildings generally struggle to run on renewable energy. And they don’t tend to create all that many jobs. But hey, maybe these massive, windowless buildings could at least give a moody, sci-fi vibe to your community. —James O’Donnell

7. Bubble

The lofty promises of AI are levitating the economy. AI companies are raising eye-popping sums of money and watching their valuations soar into the stratosphere. They’re pouring hundreds of billions of dollars into chips and data centers, financed increasingly by debt and eyebrow-raising circular deals. Meanwhile, the companies leading the gold rush, like OpenAI and Anthropic, might not turn a profit for years, if ever. Investors are betting big that AI will usher in a new era of riches, yet no one knows how transformative the technology will actually be.

Most organizations using AI aren’t yet seeing the payoff, and AI work slop is everywhere. There’s scientific uncertainty about whether scaling LLMs will deliver superintelligence or whether new breakthroughs need to pave the way. But unlike their predecessors in the dot-com bubble, AI companies are showing strong revenue growth, and some are even deep-pocketed tech titans like Microsoft, Google, and Meta. Will the manic dream ever burst? —Michelle Kim

8. Agentic

This year, AI agents were everywhere. Every new feature announcement, model drop, or security report throughout 2025 was peppered with mentions of them, even though plenty of AI companies and experts disagree on exactly what counts as being truly “agentic,” a vague term if ever there was one. No matter that it’s virtually impossible to guarantee that an AI acting on your behalf out in the wide web will always do exactly what it’s supposed to do—it seems as though agentic AI is here to stay for the foreseeable. Want to sell something? Call it agentic! —Rhiannon Williams

9. Distillation

Early this year, DeepSeek unveiled its new model DeepSeek R1, an open-source reasoning model that matches top Western models but costs a fraction of the price. Its launch freaked Silicon Valley out, as many suddenly realized for the first time that huge scale and resources were not necessarily the key to high-level AI models. Nvidia stock plunged by 17% the day after R1 was released.

The key to R1’s success was distillation, a technique that makes AI models more efficient. It works by getting a bigger model to tutor a smaller model: You run the teacher model on a lot of examples and record the answers, and reward the student model as it copies those responses as closely as possible, so that it gains a compressed version of the teacher’s knowledge. —Caiwei Chen

10. Sycophancy

As people across the world spend increasing amounts of time interacting with chatbots like ChatGPT, chatbot makers are struggling to work out the kind of tone and “personality” the models should adopt. Back in April, OpenAI admitted it’d struck the wrong balance between helpful and sniveling, saying a new update had rendered GPT-4o too sycophantic. Having it suck up to you isn’t just irritating—it can mislead users by reinforcing their incorrect beliefs and spreading misinformation. So consider this your reminder to take everything—yes, everything—LLMs produce with a pinch of salt. —Rhiannon Williams

11. Slop

If there is one AI-related term that has fully escaped the nerd enclosures and entered public consciousness, it’s “slop.” The word itself is old (think pig feed), but “slop” is now commonly used to refer to low-effort, mass-produced content generated by AI, often optimized for online traffic. A lot of people even use it as a shorthand for any AI-generated content. It has felt inescapable in the past year: We have been marinated in it, from fake biographies to shrimp Jesus images to surreal human-animal hybrid videos.

But people are also having fun with it. The term’s sardonic flexibility has made it easy for internet users to slap it on all kinds of words as a suffix to describe anything that lacks substance and is absurdly mediocre: think “work slop” or “friend slop.” As the hype cycle resets, “slop” marks a cultural reckoning about what we trust, what we value as creative labor, and what it means to be surrounded by stuff that was made for engagement rather than expression. —Caiwei Chen

12. Physical intelligence

Did you come across the hypnotizing video from earlier this year of a humanoid robot putting away dishes in a bleak, gray-scale kitchen? That pretty much embodies the idea of physical intelligence: the idea that advancements in AI can help robots better move around the physical world.

It’s true that robots have been able to learn new tasks faster than ever before, everywhere from operating rooms to warehouses. Self-driving-car companies have seen improvements in how they simulate the roads, too. That said, it’s still wise to be skeptical that AI has revolutionized the field. Consider, for example, that many robots advertised as butlers in your home are doing the majority of their tasks thanks to remote operators in the Philippines.

The road ahead for physical intelligence is also sure to be weird. Large language models train on text, which is abundant on the internet, but robots learn more from videos of people doing things. That’s why the robot company Figure suggested in September that it would pay people to film themselves in their apartments doing chores. Would you sign up? —James O’Donnell

13. Fair use

AI models are trained by devouring millions of words and images across the internet, including copyrighted work by artists and writers. AI companies argue this is “fair use”—a legal doctrine that lets you use copyrighted material without permission if you transform it into something new that doesn’t compete with the original. Courts are starting to weigh in. In June, Anthropic’s training of its AI model Claude on a library of books was ruled fair use because the technology was “exceedingly transformative.”

That same month, Meta scored a similar win, but only because the authors couldn’t show that the company’s literary buffet cut into their paychecks. As copyright battles brew, some creators are cashing in on the feast. In December, Disney signed a splashy deal with OpenAI to let users of Sora, the AI video platform, generate videos featuring more than 200 characters from Disney’s franchises. Meanwhile, governments around the world are rewriting copyright rules for the content-guzzling machines. Is training AI on copyrighted work fair use? As with any billion-dollar legal question, it depends. —Michelle Kim

14. GEO

Just a few short years ago, an entire industry was built around helping websites rank highly in search results (okay, just in Google). Now search engine optimization (SEO), is giving way to GEO—generative engine optimization—as the AI boom forces brands and businesses to scramble to maximize their visibility in AI, whether that’s in AI-enhanced search results like Google’s AI Overviews or within responses from LLMs. It’s no wonder they’re freaked out. We already know that news companies have experienced a colossal drop in search-driven web traffic, and AI companies are working on ways to cut out the middleman and allow their users to visit sites from directly within their platforms. It’s time to adapt or die. —Rhiannon Williams

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App Computing

Dec 25 2025

Meet the man hunting the spies in your smartphone

In April 2025, Ronald Deibert left all electronic devices at home in Toronto and boarded a plane. When he landed in Illinois, he took a taxi to a mall and headed directly to the Apple Store to purchase a new laptop and iPhone. He’d wanted to keep the risk of having his personal devices confiscated to a minimum, because he knew his work made him a prime target for surveillance. “I’m traveling under the assumption that I am being watched, right down to exactly where I am at any moment,” Deibert says.

Deibert directs the Citizen Lab, a research center he founded in 2001 to serve as “counterintelligence for civil society.” Housed at the University of Toronto, the lab operates independently of governments or corporate interests, relying instead on research grants and private philanthropy for financial support. It’s one of the few institutions that investigate cyberthreats exclusively in the public interest, and in doing so, it has exposed some of the most egregious digital abuses of the past two decades.

For many years, Deibert and his colleagues have held up the US as the standard for liberal democracy. But that’s changing, he says: “The pillars of democracy are under assault in the United States. For many decades, in spite of its flaws, it has upheld norms about what constitutional democracy looks like or should aspire to. [That] is now at risk.”

Even as some of his fellow Canadians avoided US travel after Donald Trump’s second election, Deibert relished the opportunity to visit. Alongside his meetings with human rights defenders, he also documented active surveillance at Columbia University during the height of its student protests. Deibert snapped photos of drones above campus and noted the exceptionally strict security protocols. “It was unorthodox to go to the United States,” he says. “But I really gravitate toward problems in the world.”

Deibert, 61, grew up in East Vancouver, British Columbia, a gritty area with a boisterous countercultural presence. In the ’70s, Vancouver brimmed with draft dodgers and hippies, but Deibert points to American investigative journalism—exposing the COINTELPRO surveillance program, the Pentagon Papers, Watergate—as the seed of his respect for antiestablishment sentiment. He didn’t imagine that this fascination would translate into a career, however.

“My horizons were pretty low because I came from a working-class family, and there weren’t many people in my family—in fact, none—who went on to university,” he says.

Deibert eventually entered a graduate program in international relations at the University of British Columbia. His doctoral research brought him to a field of inquiry that would soon explode: the geopolitical implications of the nascent internet.

“In my field, there were a handful of people beginning to talk about the internet, but it was very shallow, and that frustrated me,” he says. “And meanwhile, computer science was very technical, but not political—[politics] was almost like a dirty word.”

Deibert continued to explore these topics at the University of Toronto when he was appointed to a tenure-track professorship, but it wasn’t until after he founded the Citizen Lab in 2001 that his work rose to global prominence.

What put the lab on the map, Deibert says, was its 2009 report “Tracking GhostNet,” which uncovered a digital espionage network in China that had breached offices of foreign embassies and diplomats in more than 100 countries, including the office of the Dalai Lama. The report and its follow-up in 2010 were among the first to publicly expose cybersurveillance in real time. In the years since, the lab has published over 180 such analyses, garnering praise from human rights advocates ranging from Margaret Atwood to Edward Snowden.

The lab has rigorously investigated authoritarian regimes around the world (Deibert says both Russia and China have his name on a “list” barring his entry). The group was the first to uncover the use of commercial spyware to surveil people close to the Saudi dissident and Washington Post journalist Jamal Khashoggi prior to his assassination, and its research has directly informed G7 and UN resolutions on digital repression and led to sanctions on spyware vendors. Even so, in 2025 US Immigration and Customs Enforcement reactivated a $2 million contract with the spyware vendor Paragon. The contract, which the Biden administration had previously placed under a stop-work order, resembles steps taken by governments in Europe and Israel that have also deployed domestic spyware to address security concerns.

“It saves lives, quite literally,” Cindy Cohn, executive director of the Electronic Frontier Foundation, says of the lab’s work. “The Citizen Lab [researchers] were the first to really focus on technical attacks on human rights activists and democracy activists all around the world. And they’re still the best at it.”

When recruiting new Citizen Lab employees (or “Labbers,” as they refer to one another), Deibert forgoes stuffy, pencil-pushing academics in favor of brilliant, colorful personalities, many of whom personally experienced repression from some of the same regimes the lab now investigates.

Noura Aljizawi, a researcher on digital repression who survived torture at the hands of the al-Assad regime in Syria, researches the distinct threat that digital technologies pose to women and queer people, particularly when deployed against exiled nationals. She helped create Security Planner, a tool that gives personalized, expert-reviewed guidance to people looking to improve their digital hygiene, for which the University of Toronto awarded her an Excellence Through Innovation Award.

Work for the lab is not without risk. Citizen Lab fellow Elies Campo, for example, was followed and photographed after the lab published a 2022 report that exposed the digital surveillance of dozens of Catalonian citizens and members of parliament, including four Catalonian presidents who were targeted during or after their terms.

Still, the lab’s reputation and mission make recruitment fairly easy, Deibert says. “This good work attracts a certain type of person,” he says. “But they’re usually also drawn to the sleuthing. It’s detective work, and that can be highly intoxicating—even addictive.”

Deibert frequently deflects the spotlight to his fellow Labbers. He rarely discusses the group’s accomplishments without referencing two senior researchers, Bill Marczak and John Scott-Railton, alongside other staffers. And on the occasion that someone decides to leave the Citizen Lab to pursue another position, this appreciation remains.

“We have a saying: Once a Labber, always a Labber,” Deibert says.

While in the US, Deibert taught a seminar on the Citizen Lab’s work to Northwestern University undergraduates and delivered talks on digital authoritarianism at the Columbia University Graduate School of Journalism. Universities in the US had been subjected to funding cuts and heightened scrutiny from the Trump administration, and Deibert wanted to be “in the mix” at such institutions to respond to what he sees as encroaching authoritarian practices by the US government.

Since Deibert’s return to Canada, the lab has continued its work unearthing digital threats to civil society worldwide, but now Deibert must also contend with the US—a country that was once his benchmark for democracy but has become another subject of his scrutiny. “I do not believe that an institution like the Citizen Lab could exist right now in the United States,” he says. “The type of research that we pioneered is under threat like never before.”

He is particularly alarmed by the increasing pressures facing federal oversight bodies and academic institutions in the US. In September, for example, the Trump administration defunded the Council of the Inspectors General on Integrity and Efficiency, a government organization dedicated to preventing waste, fraud, and abuse within federal agencies, citing partisanship concerns. The White House has also threatened to freeze federal funding to universities that do not comply with administration directives related to gender, DEI, and campus speech. These sorts of actions, Deibert says, undermine the independence of watchdogs and research groups like the Citizen Lab.

Cohn, the director of the EFF, says the lab’s location in Canada allows it to avoid many of these attacks on institutions that provide accountability. “Having the Citizen Lab based in Toronto and able to continue to do its work largely free of the things we’re seeing in the US,” she says, “could end up being tremendously important if we’re going to return to a place of the rule of law and protection of human rights and liberties.”

Finian Hazen is a journalism and political science student at Northwestern University.

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Dec 25 2025

Four bright spots in climate news in 2025

Climate news hasn’t been great in 2025. Global greenhouse-gas emissions hit record highs (again). This year is set to be either the second or third warmest on record. Climate-fueled disasters like wildfires in California and flooding in Indonesia and Pakistan devastated communities and caused billions in damage.

In addition to these worrying indicators of our continued contributions to climate change and their obvious effects, the world’s largest economy has made a sharp U-turn on climate policy this year. The US under the Trump administration withdrew from the Paris Agreement, cut funds for climate research, and scrapped billions of dollars in funding for climate tech projects.

We’re in a severe situation with climate change. But for those looking for bright spots, there was some good news in 2025. Here are a few of the positive stories our climate reporters noticed this year.

China’s flattening emissions

One of the most notable and encouraging signs of progress this year occurred in China. The world’s second-biggest economy and biggest climate polluter has managed to keep carbon dioxide emissions flat for the last year and a half, according to an analysis in Carbon Brief.

That’s happened before, but only when the nation’s economy was retracting, including in the midst of the covid-19 pandemic. But emissions are now falling even as China’s economy is on track to grow about 5% this year, and electricity demands continue to rise.

So what’s changed? China has now installed so much solar and wind, and put so many EVs on the road, that its economy can continue to expand without increasing the amount of carbon dioxide it’s pumping into the atmosphere, decoupling the traditional link between emissions and growth.

Specifically, China added an astounding 240 gigawatts of solar power capacity and 61 gigawatts of wind power in the first nine months of the year, the Carbon Brief analysis noted. That’s nearly as much solar power as the US has installed in total, in just the first three quarters of this year.

It’s too early to say China’s emissions have peaked, but the country has said it will officially reach that benchmark before 2030.

To be clear, China still isn’t moving fast enough to keep the world on track for meeting relatively safe temperature targets. (Indeed, very few countries are.) But it’s now both producing most of the world’s clean energy technologies and curbing its emissions growth, providing a model for cleaning up industrial economies without sacrificing economic prosperity—and setting the stage for faster climate progress in the coming years.

Batteries on the grid

looking down a row on battery storage units on an overcast day

It’s hard to articulate just how quickly batteries for grid storage are coming online. These massive arrays of cells can soak up electricity when sources like solar are available and prices are low, and then discharge power back to the grid when it’s needed most.

Back in 2015, the battery storage industry had installed only a fraction of a gigawatt of battery storage capacity across the US. That year, it set a seemingly bold target of adding 35 gigawatts by 2035. The sector passed that goal a decade early this year and then hit 40 gigawatts a couple of months later.

Costs are still falling, which could help maintain the momentum for the technology’s deployment. This year, battery prices for EVs and stationary storage fell yet again, reaching a record low, according to data from BloombergNEF. Battery packs specifically used for grid storage saw prices fall even faster than the average; they cost 45% less than last year.

We’re starting to see what happens on grids with lots of battery capacity, too: in California and Texas, batteries are already helping meet demand in the evenings, reducing the need to run natural-gas plants. The result: a cleaner, more stable grid.

AI’s energy funding influx

Aerial view of a large Google Data Centre being built in Cheshunt, Hertfordshire, UK

The AI boom is complicated for our energy system, as we covered at length this year. Electricity demand is ticking up: the amount of power utilities supplied to US data centers jumped 22% this year and will more than double by 2030.

But at least one positive shift is coming out of AI’s influence on energy: It’s driving renewed interest and investment in next-generation energy technologies.

In the near term, much of the energy needed for data centers, including those that power AI, will likely come from fossil fuels, especially new natural-gas power plants. But tech giants like Google, Microsoft, and Meta all have goals on the books to reduce their greenhouse-gas emissions, so they’re looking for alternatives.

Meta signed a deal with XGS Energy in June to purchase up to 150 megawatts of electricity from a geothermal plant. In October, Google signed an agreement that will help reopen Duane Arnold Energy Center in Iowa, a previously shuttered nuclear power plant.

Geothermal and nuclear could be key pieces of the grid of the future, as they can provide constant power in a way that wind and solar don’t. There’s a long way to go for many of the new versions of the tech, but more money and interest from big, powerful players can’t hurt.

Good news, bad news

Aerial view of solar power and battery storage units in the desert

Perhaps the strongest evidence of collective climate progress so far: We’ve already avoided the gravest dangers that scientists feared just a decade ago.

The world is on track for about 2.6 °C of warming over preindustrial conditions by 2100, according to Climate Action Tracker, an independent scientific effort to track the policy progress that nations have made toward their goals under the Paris climate agreement.

That’s a lot warmer than we want the planet to ever get. But it’s also a whole degree better than the 3.6 °C path that we were on a decade ago, just before nearly 200 countries signed the Paris deal.

That progress occurred because more and more nations passed emissions mandates, funded subsidies, and invested in research and development—and private industry got busy cranking out vast amounts of solar panels, wind turbines, batteries, and EVs.

The bad news is that progress has stalled. Climate Action Tracker notes that its warming projections have remained stubbornly fixed for the last four years, as nations have largely failed to take the additional action needed to bend that curve closer to the 2 °C goal set out in the international agreement.

But having shaved off a degree of danger is still demonstrable proof that we can pull together in the face of a global threat and address a very, very hard problem. And it means we’ve done the difficult work of laying down the technical foundation for a society that can largely run without spewing ever more greenhouse gas into the atmosphere.

Hopefully, as cleantech continues to improve and climate change steadily worsens, the world will find the collective will to pick up the pace again soon.

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Dec 25 2025

New Ecommerce Tools: December 24, 2025

Every week we publish a rundown of new services for ecommerce merchants. This installment includes updates on answer engine optimization, agentic commerce, analytics, marketplaces, cryptocurrencies and alternative payments, AI marketing, fulfillment, fraud prevention, and creator-led commerce.

Got an ecommerce product release? Email updates@practicalecommerce.com.

New Tools for Merchants

Contentsquare and Shopify partner to deliver customer-experience insights. Contentsquare, a provider of AI-first analytics, has partnered with Shopify to provide customer experience visibility across ecommerce. According to the companies, the combination of Shopify’s commerce platform and Contentsquare’s granular behavioral insights gives businesses a comprehensive view of the customer experience, from first interaction through post-purchase. The partnership enables participating merchants to (i) visualize how shoppers browse, search, and move across products and categories, (ii) use AI to detect obstacles and strengthen A/B testing, and (iii) analyze placement, merchandising, and cross-sell strategies.

Contentsquare

GoDaddy’s ANS Marketplace advises which AI Agents to trust. GoDaddy has announced the next phase of its Agent Name Service by launching the ANS Marketplace and related AI agents. According to GoDaddy, the ANS Marketplace lets users discover ANS-verified agents, understand how they work, and see them in action. The curated set of agents includes Brand Advisor, Home Page Advisor, Place Reviews Analyzer, Social Media Post Generator, and Business Information Snoopy.

Shift4 launches stablecoin settlement platform for merchants. Shift4, a developer of integrated payments and commerce technology, has launched its stablecoin settlement platform to receive and move money 24/7. According to Shift4, the platform will allow merchants to opt into being settled in popular stablecoins such as USDC, USDT, EURC, and DAI rather than receiving a bank transfer. It will also give merchants the flexibility to choose from popular networks such as Ethereum, Solana, Plasma, Stellar, Polygon, Ton, and Base.

Squarespace introduces Pay Links to help small businesses get paid. Squarespace, a website builder and hosting platform, has introduced Pay Links, dedicated URLs that collect payments online via text, social media, QR code, or embedded links. Pay Links offer a fast way to collect payments with a branded design, built-in security, and integrated tools for tracking and analytics. Unlimited use of Pay Links is included across all plans and can be accessed through Squarespace’s merchant dashboard once connected to a payment processor.

Squarespace Pay Links

Akii launches AI Engage to train genAI engines on brand content. Akii, a search intelligence tool for businesses and marketers, has launched AI Engage, a search engagement platform to help brands educate genAI engines at scale about their content, offerings, and positioning. The platform runs automated engagement campaigns that prompt AI search engines to fetch, analyze, and learn from a brand’s content using realistic user-style queries. The platform executes campaigns across four major AI search engines simultaneously.

BigCommerce partners with Stripe to support Agentic Commerce Suite. Commerce, parent company of BigCommerce, has announced BigCommerce’s integration with Stripe’s new Agentic Commerce Suite, which will enable BigCommerce merchants to leverage AI agent-driven shopping by making products more discoverable and purchasable. Through a single integration, BigCommerce merchants can connect their existing product catalogs to their chosen AI agents to power an agentic checkout experience, allowing merchants to scale while still maintaining control of their brand.

Teikametrics announces Artificial Retail Intelligence for marketplaces. Teikametrics, a marketplace optimization platform, has announced its AI-driven Artificial Retail Intelligence to scale across marketplaces such as Amazon, Walmart, and TikTok Shop. Users can unify campaigns and optimize inventory on one platform, which populates and edits listings based on performance data from ad campaigns and on what’s working in the marketplace.

Teikametrics

Salesforce to acquire Qualified. Salesforce has agreed to acquire Qualified, a provider of agentic AI marketing tools to engage and convert inbound buyers. Qualified says its flagship product transforms websites into multimodal conversational experiences to screen and nurture leads. According to Salesforce, bringing Qualified into the Salesforce ecosystem will enable customers to quickly deploy fully featured marketing agents that autonomously generate sales pipelines. Salesforce states the transaction will close in the February to April 2026 range.

Kibo Commerce announces advanced B2B and fulfillment innovations. Kibo Commerce, a provider of composable commerce tools, has announced product releases and enhancements, including expanded Agentic Commerce capabilities, streamlined order management processes, and extended B2B functionality. Kibo’s Merchandiser Agent empowers teams to generate and update product descriptions and search-engine metadata using natural language. Agentic Roadmap includes a suite of order management agents: Order Routing, Reverse Logistics, and Forecasting. B2B merchants can now define custom roles and permissions.

Intelo.ai launches on Microsoft Marketplace for retail operations. Intelo.ai, a provider of retail technology, has announced the availability of its specialized AI agent network on the Microsoft Marketplace. Microsoft customers can now access Intelo.ai’s retail agents that automate workflows across planning, allocation, and replenishment. The agents include Strategic Planning, Core Planning, Assortment Planning, In-Season Management, Pricing & Promotion, and Vendor Management.

Intelo.ai

Shopline partners with Hive Analytics. Global commerce platform Shopline has partnered with Hive Analytics, a performance marketing and growth agency that builds custom fractional marketing teams. Shopline says the partnership enables consumer brands to launch or migrate onto its platform with an optimized, “growth-ready” setup supported by Hive Analytics’ dedicated fractional teams. This includes streamlined store execution, conversion rate optimization, user-experience setup, full-funnel performance marketing, scalable retention strategies, and regional market insights.

Amenexia launches AI shopping assistant for ecommerce. Amenexia, an AI-powered digital shopping assistant, is entering the U.S. ecommerce market. According to Amenexia, its AI assistant provides seamless, human-like interaction for customers at every step of their journey, from product inquiries to checkout. Available 24/7, Amenexia ensures that online stores can engage with customers in real-time, offering personalized assistance and boosting conversion rates without additional human staff.

Pattern acquires NextWave, expanding TikTok Shop and creator-led commerce. Pattern Group, a marketplace accelerator for brands, has acquired NextWave, an agency specializing in creator-led product discovery, TikTok Shop operations, live selling, and affiliate acceleration. According to Pattern, the acquisition enhances the platform’s ability to help brands reach customers through TikTok Shop and social commerce.

Pattern

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Dec 24 2025

Track Santa On Christmas Eve 2025 (Via NORAD & Google) via @sejournal, @MattGSouthern

Santa’s coming!

The world waits with excitement and anticipation for the arrival of Santa Claus as he starts his world tour for 2025.

Children (and adults) everywhere are eager to track the man in the red suit as he defies the speed limit to make his journey across the globe in just one night.

To help you keep up to date on what time Santa will arrive in your neighborhood, there are now two portals you can use to follow the sleigh.

The original Santa tracker from NORAD tracks Santa’s sleigh as he starts his busy night shift at the International Date Line in the Pacific Ocean and heads across the world towards New Zealand and Australia.

Google also has an interactive website and mobile app so users can follow Old Saint Nick’s journey as he delivers presents worldwide until he finishes in South America after the world’s longest night shift.

NORAD Santa Tracker: A Holiday Tradition

For over 65 years, the NORAD Santa Tracker has helped families follow Santa’s whereabouts.

The NORAD Santa Tracker began in 1955 when a misprinted phone number in a Sears advertisement directed children to call NORAD’s predecessor, the Continental Air Defense Command (CONAD), instead of Santa.

Colonel Harry Shoup, the director of operations, instructed his staff to give updates on Santa’s location to every child who called.

NORAD continues the tradition to this day.

santa tracker — Screenshot from noradsanta.org/en/, December 2025

How To Track Santa With NORAD

Visit the NORAD Santa Tracker website.
On Christmas Eve, the live map will display Santa’s current location and next stop.
For a more traditional experience, call the NORAD Tracks Santa hotline at 1-877-HI-NORAD (1-877-446-6723) to speak with a volunteer who will provide you with Santa’s current location.
Follow NORAD’s social media channels for regular daily updates.

This year, NORAD has added an AI chatbot called Radar to help you get the latest updates.

The Evolution Of Google’s Santa Tracker

Since it launched in 2004, Google’s Santa Tracker has changed and improved. The team uses this project to try out new technologies and make design updates. Some of these new features, like “View in 3D,” are later added to other Google products and services.

What’s In The 2025 Google Santa Tracker

Screenshot from santatracker.google.com/, December 2025

Google’s Santa Tracker returns for its 21st year with the familiar village experience you know and love. The site features games, videos, and activities throughout December, with the live tracker launching on Christmas Eve.

This year’s collection includes classics like Elf Ski and Penguin Dash alongside creative activities like Santa’s Canvas and Code Lab. Google uses the Santa Tracker project to test new technologies that often make their way into other Google products.

On Christmas Eve, the live map shows Santa’s current location, where he’s heading next, his distance from your location, and an estimated arrival time. The tracker begins at midnight in the furthest east time zone (10:00 a.m. UTC) as Santa starts his journey at the International Date Line in the Pacific Ocean.

For each city Santa visits, the tracker displays Wikipedia excerpts and photos, turning the experience into a geography lesson wrapped in Christmas magic.

How To Use The Google Santa Tracker

Visit the Google Santa Tracker website or download the mobile app for Android devices.
On Christmas Eve, the live map will show Santa’s current location, the number of gifts delivered, and his estimated arrival time at your location.
Explore the map to learn more about the 500+ locations Santa visits, with photos and information provided by Google’s Local Guides.

Extra Features & Activities

Beyond games, the platform showcases detailed animated environments ranging from cozy kitchens where elves prepare holiday treats to snowy outdoor scenes filled with winter activities.

The experience is wrapped in Google’s characteristic bright, cheerful art style, with colorful illustrations that bring North Pole activities to life.

Whether practicing basic coding concepts or learning holiday traditions from around the world, kids (and big kids) can explore while counting down to Christmas.

To All, A Good Night

Settle down for the evening tonight with your choice of favorite Christmas snack and follow Santa’s journey with either Google or NORAD.

Santa has an estimated 2.2 billion homes to visit, so it’s going to be a busy night tonight! Don’t forget to leave out your carrots and mince pies.

Happy holidays from all of us at Search Engine Journal!

Featured Image: Roman Samborskyi/Shutterstock

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News SEO SEO

Dec 24 2025

The 2025 SEO wrap-up: What we learned about search, content, and trust

SEO didn’t stand still in 2025. It didn’t reinvent itself either. It clarified what actually matters. If you followed The SEO Update by Yoast monthly webinars this year, you’ll recognize the pattern. Throughout 2025, our Principal SEOs, Carolyn Shelby and Alex Moss, cut through the noise to explain not just what was changing but why it mattered as AI-powered search reshaped visibility, trust, and performance. If you missed some sessions or want the full picture in one place, this wrap-up is for you. We’re looking back at how SEO evolved over the year, what those changes mean in practice, and what they signal going forward.

Key takeaways

In 2025, SEO shifted its focus from rankings to visibility management, as AI-driven search reshaped priorities
Key developments included the rise of AI Overviews, a shift from clicks to citations, and increased importance of clarity and trust
Brands needed to prioritize structured, credible content that AI systems could easily interpret to remain visible
By December, SEO transformed to retrieval-focused strategies, where success rested on clarity, relevance, and E-E-A-T signals
Overall, 2025 clarified that the fundamentals still matter but emphasized the need for precision in content for AI-driven systems

SEO in 2025: month-by-month overview

Month	Key evolutions	Core takeaways
January	AI-powered, personalized search accelerated. Zero-click results increased. Brand signals, E-E-A-T, performance, and schema shifted from optimizations to requirements.	SEO expanded from ranking pages to representing trusted brands that machines can understand.
February	Massive AI infrastructure investments. AI Overviews pushed organic results down. Traffic dropped while brand influence and revenue held steady.	SEO outcomes can no longer be measured by traffic alone. Authority and influence matter more than raw clicks.
March	AI Overviews expanded as clicks declined. Brand mentions appeared to play a larger role in AI-driven citation and selection behavior than links alone. Search behavior grew despite fewer referrals.	Visibility fractured across systems. Trust and brand recognition became the differentiators for inclusion.
April	Schema and structure proved essential for AI interpretation. Multimodal and personalized search expanded. Zero-click behavior increased further.	SEO shifted from optimization to interpretation. Clarity and structure determine reuse.
May	Discovery spread beyond Google. AI Overviews reached mass adoption. Citations replaced visits as success signals.	SEO outgrew the SERP. Presence across platforms and AI systems became critical.
June – July	AI Mode became core to search. Ads entered AI answers. Indexing alone no longer offers guaranteed visibility. Reporting lagged behind reality.	Traditional SEO remained necessary but insufficient. Resilience and adaptability became essential.
August	Visibility without value became a real risk. SEO had to tie exposure to outcomes beyond the number of sessions.	Visibility without value became a real risk. SEO had to tie exposure to outcomes beyond sessions.
September	AI Mode neared default status. Legal, licensing, and attribution pressures intensified. Persona-based strategies gained relevance.	Control over visibility is no longer guaranteed. Trust and credibility are the only durable advantages.
October	Search Console data reset expectations. AI citations outweighed rankings. AI search became the destination.	SEO success depends on presence inside AI systems, not just SERP positions.
November	AI Mode became core to search. Ads entered AI answers. Indexing alone is no longer a guarantee of visibility. Reporting lagged behind reality.	Clarity and structure beat scale. Authority decides inclusion.
December	SEO fully shifted to retrieval-based logic. AI systems extracted answers, not pages. E-E-A-T acted as a gatekeeper.	SEO evolved into visibility management for AI-driven search. Precision replaced volume.

January: SEO enters the age of representation

January set the tone for the year. Not through a single disruptive update, but through a clear signal that SEO was moving away from pure rankings toward something broader. The search was becoming more personalized, AI-driven, and selective about which sources it chose to surface. Visibility was no longer guaranteed just because you ranked well.

Do read: Perfect prompts: 10 tips for AI-driven SEO content creation

From the start of the year, it was clear that SEO in 2025 would reward brands that were trusted, technically sound, and easy for machines to understand.

What changed in January

Here are a few clear trends that began to shape how SEO worked in practice:

AI-powered search became more personalized: Search results reflected context more clearly, taking into account location, intent, and behavior. The same query no longer produced the same result for every user
Zero-click searches accelerated: More answers appeared directly in search results, reducing the need to click through, especially for informational and local queries
Brand signals and reviews gained weight: Search leaned more heavily on real-world trust indicators like brand mentions, reviews, and overall reputation
E-E-A-T became harder to ignore: Clear expertise, ownership, and credibility increasingly acted as filters, not just quality guidelines
The role of schema started to shift: Structured data mattered less for visual enhancements and more for helping machines understand content and entities

What to take away from January

January wasn’t about tactics. It was about direction.

SEO started rewarding clarity over cleverness. Brands over pages. Trust over volume. Performance over polish. If search engines were going to summarize, compare, and answer on your behalf, you needed to make it easy for them to understand who you are, what you offer, and why you are credible.

That theme did not fade as the year went on. It became the foundation for everything that followed.

Do check out the full recording of The SEO update by Yoast – January 2025 Edition webinar.

February: scale, money, and AI made the shift unavoidable

If January showed where search was heading, February showed how serious the industry was about getting there. This was the month where AI stopped feeling like a layer on top of search and started looking like the foundation underneath it.

Massive investments, changing SERP layouts, and shifting performance metrics all pointed to the same conclusion. Search was being rebuilt for an AI-first world.

What changed in February

As the month unfolded, the signs became increasingly difficult to ignore.

AI Overviews pushed organic results further down: AI Overviews appeared in a large share of problem-solving queries, favoring authoritative sources and summaries over traditional organic listings
Traffic declined while brand value increased: High-profile examples showed sessions dropping even as revenue grew. Visibility, influence, and brand trust started to matter more than raw sessions
AI referrals began to rise: Referral traffic from AI tools increased, while Google’s overall market share showed early signs of pressure. Discovery started spreading across systems, not just search engines

What to take away from February

February made January’s direction feel permanent.

When AI systems operate at this scale, they change how visibility works. Rankings still mattered, but they no longer told the full story. Authority, brand recognition, and trust increasingly influenced whether content was surfaced, summarized, or ignored.

The takeaway was clear. SEO could no longer be measured only by traffic. It had to be understood in terms of influence, representation, and relevance across an expanding search ecosystem.

Catch the full discussion in The SEO Update by Yoast – February 2025 Edition webinar recording.

March: visibility fractured, trust became the differentiator

By March, the effects of AI-driven search were no longer theoretical. The conversation shifted from how search was changing to who was being affected by it, and why.

This was the month where declining clicks, citation gaps, and publisher pushback made one thing clear. Search visibility was fragmenting across systems, and trust became the deciding factor in who stayed visible.

What changed in March

The developments in March added pressure to trends that had already been forming earlier in the year.

AI Overviews expanded while clicks declined: Studies showed that AI Overviews appeared more frequently, while click-through rates continued to decline. Visibility increasingly stopped at the SERP
Brand mentions mattered more than links alone: Citation patterns across AI platforms varied, but one signal stayed consistent. Brands mentioned frequently and clearly were more likely to surface
Search behavior continued to grow despite fewer clicks: Overall search volume increased year over year, showing that users weren’t searching less; they were just clicking less
AI search struggled with attribution and citations: Many AI-powered results failed to cite sources consistently, reinforcing the need for strong brand recognition rather than reliance on direct referrals
Search experiences became more fragmented: New entry points like Circle to Search and premium AI modes introduced additional layers to discovery, especially among younger users
Structured signals evolved for AI retrieval: Updates to robots meta tags, structured data for return policies, and “sufficient context” signals showed search engines refining how content is selected and grounded

Also read: Structured data with schema for search and AI

What to take away from March

March exposed the tension at the heart of modern SEO.

Search demand was growing, but traditional traffic was shrinking. AI systems were answering more questions, but often without clear attribution. In that environment, being a recognizable, trusted brand mattered more than being the best-optimized page.

The implication was simple. SEO was no longer just about earning clicks. It was about earning inclusion, recognition, and trust across systems that don’t always send users back.

Watch the complete recording of The SEO Update by Yoast – March 2025 Edition.

April: machines started deciding how content is interpreted

By April, the focus shifted again. The question was no longer whether AI would shape search, but how machines decide what content means and when to surface it.

After March exposed visibility gaps and attribution issues, April zoomed in on interpretation. How AI systems read, classify, and extract information became central to SEO outcomes.

What changed in April

April brought clarity to how modern search systems process content.

Schema has proven its value beyond rankings: Microsoft has confirmed that schema markup helps large language models understand content. Bing Copilot used structured data to generate clearer, more reliable answers, reinforcing the schema’s role in interpretation rather than visual enhancement
AI-driven search became multimodal: Image-based queries expanded through Google Lens and Gemini, allowing users to search using photos and visuals instead of text alone
AI Overviews expanded during core updates: A noticeable surge in AI Overviews appeared during Google’s March core update, especially in travel, entertainment, and local discovery queries
Clicks declined as summaries improved: AI-generated content summaries reduced the need to click through, accelerating zero-click behavior across informational and decision-based searches
Content structure mattered more than special optimizations: Clear headings that boost readability, lists, and semantic cues helped AI systems extract meaning. There were no shortcuts. Standard SEO best practices carried the weight

What to take away from April

April shifted SEO from optimization to interpretation.

Search engines and AI systems didn’t just look for relevance. They looked for clarity. Content that was well-structured, semantically clear, and grounded in real entities was easier to understand, summarize, and reuse.

The lesson was subtle but important. You didn’t need new tricks for AI search. You needed content that was easier for machines to read and harder to misinterpret.

Want the full context? Watch the complete The SEO Update by Yoast – April 2025 Edition webinar.

May: discovery spread beyond search engines

By May, it was no longer sufficient to discuss how search engines interpret content. The bigger question became where discovery was actually happening.

SEO started expanding beyond Google. Visibility fractured across platforms, AI tools, and ecosystems, forcing brands to think about presence rather than placement.

What changed in May

The month highlighted how search and discovery continued to decentralize.

Search behavior expanded beyond traditional search engines: Around 39% of consumers now use Pinterest as a search engine, with Gen Z leading adoption. Discovery increasingly happened inside platforms, not just through search bars
AI Overviews reached mass adoption: AI Overviews reportedly reached around 1.5 billion users per month and appeared in roughly 13% of searches, with informational queries driving most of that growth
Clicks continued to give way to citations: As AI summaries became more common, being referenced or cited mattered more than driving a visit, especially for top-of-funnel queries
AI-powered search diversified across tools: Chat-based search experiences added shopping, comparison, and personalization features, further shifting discovery away from classic result pages
Economic pressure on content ecosystems increased: Industry voices warned that widespread zero-click answers were starting to weaken the incentives for content creation across the web
Trust signals faced stricter scrutiny: Updated rater guidelines targeted fake authority, deceptive design patterns, and manufactured credibility

What to take away from May

May reframed SEO as a visibility problem, not a traffic problem.

When discovery happens across platforms, summaries, and AI systems, success depends on how clearly your content communicates meaning, credibility, and relevance. Rankings still mattered, but they were no longer the primary measure of success.

The message was clear. SEO had outgrown the SERP. Brands that focused on authenticity, semantic clarity, and structured information were better positioned to stay visible wherever search happened next.

Watch the full The SEO Update by Yoast – May 2025 Edition webinar to see all insights in context.

June and July: SEO adjusted to AI-first search

By early summer, SEO entered a more uncomfortable phase. Visibility still mattered, but control over how and where content appeared became increasingly limited.

June and July were about adjustment. Search moved closer to AI assistants, ads blended into answers, and traditional SEO signals no longer guaranteed exposure across all search surfaces.

What changed in June and July

This period introduced some of the clearest operational shifts of the year.

AI Mode became a first-class search experience: AI Mode was rolled out more broadly, including incognito use, and began to merge into core search experiences. Search was no longer just results. It was conversation, summaries, and follow-ups
Ads entered AI-generated answers: Google introduced ads inside AI Overviews and began testing them in conversational AI Mode. Visibility now competes not only with other pages, but with monetized responses
Measurement lagged behind reality: Search Console confirmed AI Mode data would be included in performance reports, but without separate filters or APIs. Visibility changed more rapidly than reporting tools could keep pace.
Citations followed platform-specific preferences: Different AI systems favored different sources. Some leaned heavily on encyclopedic content, others on community-driven platforms, reinforcing that one SEO strategy would not fit every system
Most AI-linked pages still ranked well organically: Around 97% of URLs referenced in AI Mode ranked in the top 10 organic results, showing that strong traditional SEO remained a prerequisite, even if it was no longer sufficient
Content had to resist summarization: Leaks and tests showed that some AI tools rarely surfaced links unless live search was triggered. Generic, easily summarized modern content became easier to replace
Infrastructure became an SEO concern again: AI agents increased crawl and request volume, pushing performance, caching, and server readiness back into focus
Search moved beyond text: Voice-based interactions, audio summaries, image-driven queries, and AI-first browsers expanded how users searched and consumed information

What to take away from June and July

This period forced a mindset shift.

SEO could no longer assume that ranking, indexing, or even traffic guaranteed visibility. AI systems decided when to summarize, when to cite, and when to bypass pages entirely. Ads, assistants, and alternative interfaces now often sit between users and websites more frequently than before.

The conclusion was pragmatic. Strong fundamentals still mattered, but they weren’t the finish line. SEO now requires resilience: content that carries authority, resists simplification, loads fast, and stays relevant even when clicks don’t follow.

By the end of July, one thing was clear. SEO wasn’t disappearing. It was operating under new constraints, and the rest of the year would test how well teams adapted to them.

Missed the session? You can watch the full The SEO Update by Yoast – June 2025 Edition recording here.

August: the gap between visibility and value widened

By August, SEO teams were staring at a growing disconnect. Visibility was increasing, but traditional outcomes were harder to trace back to it.

This was the month when the mechanics of AI-driven search became more transparent and more uncomfortable.

What changed in August

August surfaced the operational realities behind AI-powered discovery.

Impressions rose while clicks continued to decline: AI Overviews dominated the results, driving exposure without generating traffic. In some cases, conversions still improved, but attribution became harder to prove
The “great decoupling” became measurable: Visibility and performance stopped moving in sync. SEO teams saw growth in impressions even as sessions declined
Zero-click searches accelerated further: No-click behavior climbed toward 69%, reinforcing that many user journeys now ended inside search interfaces
AI traffic stayed small but influential: AI-driven referrals still accounted for under 1% of traffic for most sites, yet they shaped expectations around answers, speed, and convenience
Retrieval logic shifted toward context and intent: New retrieval approaches prioritized meaning, relationships, and query context over keyword matching

Must read: On-SERP SEO can help you battle zero-click results

What to take away from August

August made one thing unavoidable.

It reinforced the reality that SEO could no longer rely on traffic as the primary proof of value. Visibility still mattered, but only when paired with outcomes that could survive reduced clicks and blurred attribution.

The lesson was strategic. SEO needed to connect visibility to conversion, brand lift, or long-term trust, not just sessions. Otherwise, its impact would be increasingly hard to defend.

Didn’t catch the live session? You can still watch the full The SEO Update by Yoast – August 2025 Edition webinar.

September: control, attribution, and trust were renegotiated

September pushed the conversation further. It wasn’t just about declining clicks anymore. It was about who controlled discovery, attribution, and access to content.

This was the month where legal, technical, and strategic pressures collided.

What changed in September

September reframed SEO around governance and credibility.

AI Mode moved closer to becoming the default: Search experiences shifted toward AI-driven answers with conversational follow-ups and multimodal inputs
The decline of the open web was acknowledged publicly: Court filings and public statements confirmed what many publishers were already feeling. Traditional web traffic was under structural pressure
Legal scrutiny intensified: High-profile settlements and lawsuits highlighted growing challenges around training data, summaries, and lost revenue
Licensing entered the SEO conversation: New machine-readable licensing approaches emerged as early attempts to restore control and consent
Snippet visibility became a gateway signal: AI tools relied heavily on search snippets for real-time answers, making concise, extractable content more critical
Persona-based strategies gained traction: SEO began shifting from keyword targeting to persona-driven content aligned with how AI systems infer intent
Trust eroded around generic, formulaic, AI writing styles: Formulaic, overly polished AI content raised credibility concerns, reinforcing the need for editorial judgment
Measurement tools lost stability again: Changes to search parameters disrupted rank tracking, reminding teams that SEO reporting would remain volatile

What to take away from September

September forced SEO to grow up again.

Control over visibility, attribution, and content use was no longer guaranteed. Trust, clarity, and credibility became the only durable advantages in an ecosystem shaped by AI intermediaries.

The takeaway was sobering but useful. SEO could still drive value, but only when it is aligned with real user needs, strong brand signals, and content that earned its place in AI-driven answers.

Want to dig a little deeper? Watch the full The SEO Update by Yoast – September 2025 Edition webinar.

October: AI search became the destination

October marked a turning point in how SEO performance needed to be interpreted. The data didn’t just shift. It reset expectations entirely.

This was the month when SEO teams had to accept that AI-powered search was no longer a layer on top of results. It was becoming the place where searches ended.

What changed in October

October brought clarity, even if the numbers looked uncomfortable.

AI Mode reshaped user behavior: Around a third of searches now involve AI agents, with most sessions staying inside AI panels. Clicks became the exception, not the default
AI citations increasingly rivalled rankings: Visibility increasingly depended on whether content was selected, summarized, or cited by AI systems, not where it ranked
Search engines optimized for ideas, not pages: Guidance from search platforms reinforced that AI systems extract concepts and answers, not entire URLs
Metadata lost some direct control: Tests of AI-generated meta descriptions suggested that manual optimization would carry less influence over how content appears
Commerce and search continued to merge: AI-driven shopping experiences expanded, signaling that transactional intent would increasingly be handled inside AI interfaces

What to take away from October

October reframed SEO as presence within AI systems.

Traffic still mattered, but it was no longer the primary outcome. The real question became whether your content appeared at all inside AI-driven answers. Clarity, structure, and extractability replaced traditional ranking gains as the most reliable levers.

From this point on, SEO had to treat AI search as a destination, not just a gateway.

November: structure and credibility decided inclusion

If October reset expectations, November showed what actually worked.

This month narrowed the gap between theory and practice. It became clearer why some content consistently surfaced in AI results, while other content disappeared.

What changed in November

November focused on how AI systems select and trust sources.

Structured content outperformed clever content: Clear headings, predictable formats, and direct answers made it easier for AI systems to extract and reuse information
Schema supported understanding, not visibility alone: Structured data remained valuable, but only when paired with clean, readable on-page content
AI-driven shopping and comparisons accelerated: Product data quality, consistency, and accessibility directly influenced whether brands appeared in AI-assisted decision flows
Citation pools stayed selective: AI systems relied on a relatively small set of trusted sources, reinforcing the importance of brand recognition and authority
Search tooling evolved toward themes, not keywords: Grouped queries and topic-based insights replaced one-keyword performance views

What to take away from November

November made one thing clear. SEO wasn’t about producing more content or optimizing harder. It was about making content easier to understand and harder to ignore.

Clarity beats creativity. Structure beat scale. Authority determined whether content was reused at all.

This month quietly reinforced the fundamentals that would define SEO going forward.

For a complete breakdown, check out the full The SEO Update by Yoast – October and November 2025 Edition recording.

December: SEO moved from ranking to retrieval

December tied the entire year together.

Instead of introducing new disruptions, it clarified what 2025 had been building toward all along. SEO was no longer primarily about ranking pages. It was about enabling retrieval.

What changed in December

The year-end review highlighted the new reality of SEO.

Search systems retrieved answers, not pages: AI-driven search experiences pulled snippets, definitions, and summaries instead of directing users to full articles
Literal language still mattered: Despite advances in understanding, AI systems relied heavily on exact phrasing. Terminology choices directly affected retrieval
Content structure became mandatory: Front-loaded answers, short paragraphs, lists, and clear sections made content usable for AI systems
Relevance replaced ranking as the core signal: Being the clearest and most contextually relevant answer mattered more than traditional ranking factors
E-E-A-T acted as a gatekeeper: Recognized expertise, authorship, and trust signals determined whether content was eligible for reuse
Authority reduced AI errors: Strong credibility signals helped AI systems select more reliable sources and reduced hallucinated answers

What to take away from December

December didn’t declare the end of SEO. It defined its next phase.

SEO matured into visibility management for AI-driven systems. Success depended on clarity, credibility, and structure, not shortcuts or volume. The fundamentals still worked, but only when applied with discipline.

By the end of 2025, the direction was clear. SEO didn’t get smaller. It got more precise.

Missed the session? You can watch the full The SEO Update by Yoast – December 2025 Edition recording here.

SEO evolved into visibility management for AI-driven search. Precision replaced volume.

2025 didn’t rewrite SEO. It clarified it.

Search moved from ranking pages to retrieving answers. From rewarding volume to rewarding clarity. From clicks to credibility. And from optimization tricks to systems-level understanding.

The fundamentals still matter. Technical health, helpful content, and strong SEO foundations are non-negotiable. But they are no longer the finish line. What separates visible brands from invisible ones now is how clearly their content can be understood, trusted, and reused by AI-driven search systems.

Going into 2026, the goal isn’t to outsmart search engines. It’s to make your expertise unmistakable. Write for humans, structure for machines, and build authority that holds up even when clicks don’t follow.

SEO didn’t get smaller this year. It got more precise. Stay with us for our 2026 verdict on where search goes next.

Ahad Qureshi

I’m a Computer Science grad who accidentally stumbled into writing—and stayed because I fell in love with it. Over the past six years, I’ve been deep in the world of SEO and tech content, turning jargon into stories that actually make sense. When I’m not writing, you’ll probably find me lifting weights to balance my love for food (because yes, gym and biryani can coexist) or catching up with friends over a good cup of chai.

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Dec 24 2025

Top 10 Emotionally-Engaging Holiday Ads Of 2025 (With A Bonus One) via @sejournal, @gregjarboe

Every December, brands battle for something far more valuable than views: emotional resonance. And according to new data from DAIVID, 2025 may be one of the strongest holiday seasons yet for emotionally engaging advertising across North America.

This year shows an acceleration of trends I’ve long argued shape effective holiday storytelling: nostalgia, warmth, joy, and authentic human narratives. These insights echo themes from my other articles on nostalgia marketing, John Lewis, and the full spectrum of 39 emotions that digital marketers can use to deepen engagement.

Let’s break down the list and analyze what each ad teaches us about crafting emotionally resonant creative.

1. Disney, Best Christmas Ever

Directed by Oscar winner Taika Waititi, Disney’s spot leads the 2025 list with a commanding emotional profile: It got 169% more adoration, 149% more nostalgia, 125% more warmth, and 115% more joy than the average U.S. ad.

The story, a young girl’s doodle magically comes to life after Santa mistakes it for a Christmas wish, pulls on the intersection of childhood imagination and holiday wonder.

This kind of warm, universal narrative aligns with what I’ve previously identified in nostalgia-driven campaigns, including the emotional DNA found in John Lewis’s best Christmas ads. Disney proves once again that if you can trigger both memory and magic, audiences respond.

Strategic takeaway: Emotional universality beats demographic targeting. A timeless story, well told, surpasses segmentation.

Score: 58.2% of viewers likely to feel intense positive emotions.

2. Chevrolet, Memory Lane

Chevrolet continues its tradition of leaning into family history, shared rituals, and Americana. “Memory Lane” is a deeply human piece, evoking the kind of reflective nostalgia that has long powered the auto industry’s strongest holiday ads.

This year’s showing demonstrates something I discussed in “Emotions Digital Marketers Can Use in Advertising”: nostalgia isn’t a single emotion. It’s a bundle (longing, warmth, appreciation, bittersweetness) all working together.

Strategic takeaway: When your product has a long lifecycle, storytelling should reference the past to add emotional depth to the present.

Score: 57.5% of viewers likely to feel intense positive emotions.

3. Subaru Support Charities Like Make-A-Wish When You Get A New Subaru

Subaru leans into purpose marketing, reinforcing its “Share the Love” identity. Charity-driven campaigns often rank high on DAIVID’s emotional indices, but Subaru’s strength is its consistency. The ad doesn’t feel opportunistic; it builds on years of brand equity in social good.

Strategic takeaway: Authenticity is measurable. Audiences can detect whether a brand’s social message aligns with its long-term behavior.

Score: 56.5% of viewers likely to feel intense positive emotions.

4. Publix, Merry Birthday From Publix

Publix has mastered the art of “quiet emotional power.” Its ads rarely rely on spectacle. Instead, they focus on family dynamics, cultural rituals, and everyday moments that feel lived in.

The 2025 entry blends two celebrations (Christmas and a birthday) into a single heartfelt narrative.

Strategic takeaway: Small stories often outperform big concepts. Audiences crave relatability as much as creativity.

Score: 55.6% of viewers likely to feel intense positive emotions.

5. Lego, Is It Play You’re Looking For?

Lego continues to position imagination as its emotional currency. The ad combines fantasy sequences with grounded holiday moments, appealing to both children and nostalgic adults, a dual audience Lego has long excelled at engaging.

This reflects a key insight from my analysis of holiday campaigns in 2024: brands that empower the audience, rather than simply entertain them, create deeper emotional bonds.

Strategic takeaway: Invite viewers into the story. Ads that celebrate creativity encourage emotional participation.

Score: 55% of viewers likely to feel intense positive emotions.

6. Real Canadian Superstore, Bringing The Magic Of The Holidays With The Moose

This ad stands out because it doubles typical U.S. ad levels for warmth and gratitude, two emotions that consistently predict brand affinity.

A whimsical moose may sound silly, but DAIVID’s data tells a bigger story: high-performing retail ads use metaphor and magic to elevate everyday shopping messages.

Strategic takeaway: Unexpected characters can deliver familiar feelings if they serve a strong emotional narrative.

Score: 54.4% of viewers likely to feel intense positive emotions.

7. Teleflora, The Boy And The Bot

One of the most interesting entries, Teleflora’s film blends technology with humanity. A boy befriends a robot, only to discover the emotional meaning behind giving, and receiving, flowers.

For a category traditionally rooted in romance or sympathy, Teleflora’s pivot to holiday sci-fi is bold.

Strategic takeaway: Emotional relevance can come from genre-bending storytelling, when the payoff still ties back to the brand’s purpose.

Score: 54.2% of viewers likely to feel intense positive emotions.

8. Gap, Give Your Gift

Gap has been rediscovering its brand voice in recent years, and this year’s holiday ad continues the trend. Music, movement, and human connection anchor the campaign, familiar territory for Gap, but executed with contemporary warmth.

Strategic takeaway: Legacy brands can win big by refreshing, not reinventing, their core emotional themes.

Score: 53.7% of viewers likely to feel intense positive emotions.

9. Walmart, WhoKnewVille

Walmart goes whimsical with a fictional holiday town and an ensemble cast. While the ad leans more comedic and fantastical than emotional heavyweights like Disney, it still ranks high for joy and warmth.

Strategic takeaway: Joy is an underrated emotional driver. When executed well, it performs nearly as strongly as nostalgia or empathy.

Score: 53.5% of viewers likely to feel intense positive emotions.

10a. Crayola, Blue Christmas (Tie)

Crayola continues to position creativity as emotional healing. “Blue Christmas” plays with color metaphor to tell a story of sadness lifted by artistic expression, a message that resonates with both kids and parents.

Strategic takeaway: Emotional arcs matter. Audiences respond strongly when ads move from negative to positive feelings.

Score: 53.4% of viewers likely to feel intense positive emotions.

10b. Uber, An Uber Holiday Story (Tie)

Uber’s holiday narrative focuses on connection, highlighting moments when rides bring people home, or help people show up for one another. It’s a subtle but effective adaptation of holiday storytelling to the gig economy.

Uber’s presence in the top 10 reinforces what Barney Worfolk-Smith, Chief Growth Officer at DAIVID, said: “The mood of holiday advertising shifts slightly each year, but this festive season we’re seeing an even stronger push toward storytelling over functional messaging. One thing remains constant, though: to win the hearts, minds, and crucially, the wallets of consumers, brands need the emotional lift that only great storytelling can deliver. Those emotional peaks are what ultimately drive real business outcomes.”

Strategic takeaway: Service brands can achieve deep emotional impact when they focus on the human moments they enable, not the service itself.

Score: 53.4% of viewers likely to feel intense positive emotions.

Final Thoughts: The Return Of Big-Hearted Holiday Storytelling

The 2025 rankings reinforce one overarching truth: Emotion, not budget, not celebrities, not media spend, is what drives holiday advertising effectiveness.

Disney won because it told the strongest story.
Chevrolet and Subaru succeeded because they tapped deep cultural values.
Publix and Lego connected through relatability and imagination.
Teleflora and Crayola proved that inventive storytelling still wins.

As we enter the final stretch of the holiday season, this year’s ranking offers one more important lesson:

Even in an AI-driven media landscape, human emotion remains the ultimate competitive advantage.

If you want your campaigns to break through the noise, holiday or otherwise, start with emotion, build with authenticity, and let story be your strategy.

Methodology

DAIVID evaluated 176 holiday campaigns, ranking them by the percentage of viewers predicted to feel intense positive emotions. They use a hybrid approach to compile this data. Combining computer vision, audio analysis, facial coding, eye tracking, and tens of millions of human responses to predict emotional impact and brand lift.

For marketers, this matters because:

Emotion is the single most reliable predictor of effectiveness.
AI now makes emotional testing scalable, rather than relying solely on expensive panels.
The 39 emotions DAIVID tracks align closely with modern behavioral science.

Data source: DAIVID’s AI-powered Creative Data API

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

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App Artificial intelligence The Algorithm

Dec 24 2025

How social media encourages the worst of AI boosterism

Demis Hassabis, CEO of Google DeepMind, summed it up in three words: “This is embarrassing.”

Hassabis was replying on X to an overexcited post by Sébastien Bubeck, a research scientist at the rival firm OpenAI, announcing that two mathematicians had used OpenAI’s latest large language model, GPT-5, to find solutions to 10 unsolved problems in mathematics. “Science acceleration via AI has officially begun,” Bubeck crowed.

Put your math hats on for a minute, and let’s take a look at what this beef from mid-October was about. It’s a perfect example of what’s wrong with AI right now.

Bubeck was excited that GPT-5 seemed to have somehow solved a number of puzzles known as Erdős problems.

Paul Erdős, one of the most prolific mathematicians of the 20thcentury, left behind hundreds of puzzles when he died. To help keep track of which ones have been solved, Thomas Bloom, a mathematician at the University of Manchester, UK, set up erdosproblems.com, which lists more than 1,100 problems and notes that around 430 of them come with solutions.

When Bubeck celebrated GPT-5’s breakthrough, Bloom was quick to call him out. “This is a dramatic misrepresentation,” he wrote on X. Bloom explained that a problem isn’t necessarily unsolved if this website does not list a solution. That simply means Bloom wasn’t aware of one. There are millions of mathematics papers out there, and nobody has read all of them. But GPT-5 probably has.

It turned out that instead of coming up with new solutions to 10 unsolved problems, GPT-5 had scoured the internet for 10 existing solutions that Bloom hadn’t seen before. Oops!

There are two takeaways here. One is that breathless claims about big breakthroughs shouldn’t be made via social media: Less knee jerk and more gut check.

The second is that GPT-5’s ability to find references to previous work that Bloom wasn’t aware of is also amazing. The hype overshadowed something that should have been pretty cool in itself.

Mathematicians are very interested in using LLMs to trawl through vast numbers of existing results, François Charton, a research scientist who studies the application of LLMs to mathematics at the AI startup Axiom Math, told me when I talked to him about this Erdős gotcha.

But literature search is dull compared with genuine discovery, especially to AI’s fervent boosters on social media. Bubeck’s blunder isn’t the only example.

In August, a pair of mathematicians showed that no LLM at the time was able to solve a math puzzle known as Yu Tsumura’s 554th Problem. Two months later, social media erupted with evidence that GPT-5 now could. “Lee Sedol moment is coming for many,” one observer commented, referring to the Go master who lost to DeepMind’s AI AlphaGo in 2016.

But Charton pointed out that solving Yu Tsumura’s 554th Problem isn’t a big deal to mathematicians. “It’s a question you would give an undergrad,” he said. “There is this tendency to overdo everything.”

Meanwhile, more sober assessments of what LLMs may or may not be good at are coming in. At the same time that mathematicians were fighting on the internet about GPT-5, two new studies came out that looked in depth at the use of LLMs in medicine and law (two fields that model makers have claimed their tech excels at).

Researchers found that LLMs could make certain medical diagnoses, but they were flawed at recommending treatments. When it comes to law, researchers found that LLMs often give inconsistent and incorrect advice. “Evidence thus far spectacularly fails to meet the burden of proof,” the authors concluded.

But that’s not the kind of message that goes down well on X. “You’ve got that excitement because everybody is communicating like crazy—nobody wants to be left behind,” Charton said. X is where a lot of AI news drops first, it’s where new results are trumpeted, and it’s where key players like Sam Altman, Yann LeCun, and Gary Marcus slug it out in public. It’s hard to keep up—and harder to look away.

Bubeck’s post was only embarrassing because his mistake was caught. Not all errors are. Unless something changes researchers, investors, and non-specific boosters will keep teeing each other up. “Some of them are scientists, many are not, but they are all nerds,” Charton told me. “Huge claims work very well on these networks.”

*****

There’s a coda! I wrote everything you’ve just read above for the Algorithm column in the January/February 2026 issue of MIT Technology Review magazine (out very soon). Two days after that went to press, Axiom told me its own math model, AxiomProver, had solved two open Erdős problems (#124 and #481, for the math fans in the room). That’s impressive stuff for a small startup founded just a few months ago. Yup—AI moves fast!

But that’s not all. Five days later the company announced that AxiomProver had solved nine out of 12 problems in this year’s Putnam competition, a college-level math challenge that some people consider harder than the better-known International Math Olympiad (which LLMs from both Google DeepMind and OpenAI aced a few months back).

The Putnam result was lauded on X by big names in the field, including Jeff Dean, chief scientist at Google DeepMind, and Thomas Wolf, cofounder at the AI firm Hugging Face. Once again familiar debates played out in the replies. A few researchers pointed out that while the International Math Olympiad demands more creative problem-solving, the Putnam competition tests math knowledge—which makes it notoriously hard for undergrads, but easier, in theory, for LLMs that have ingested the internet.

How should we judge Axiom’s achievements? Not on social media, at least. And the eye-catching competition wins are just a starting point. Determining just how good LLMs are at math will require a deeper dive into exactly what these models are doing when they solve hard (read: hard for humans) math problems.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

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App Culture

Dec 24 2025

How I learned to stop worrying and love AI slop

Lately, everywhere I scroll, I keep seeing the same fish-eyed CCTV view: a grainy wide shot from the corner of a living room, a driveway at night, an empty grocery store. Then something impossible happens. JD Vance shows up at the doorstep in a crazy outfit. A car folds into itself like paper and drives away. A cat comes in and starts hanging out with capybaras and bears, as if in some weird modern fairy tale.

This fake-surveillance look has become one of the signature flavors of what people now call AI slop. For those of us who spend time online watching short videos, slop feels inescapable: a flood of repetitive, often nonsensical AI-generated clips that washes across TikTok, Instagram, and beyond. For that, you can thank new tools like OpenAI’s Sora (which exploded in popularity after launching in app form in September), Google’s Veo series, and AI models built by Runway. Now anyone can make videos, with just a few taps on a screen.

@absolutemem

If I were to locate the moment slop broke through into popular consciousness, I’d pick the video of rabbits bouncing on a trampoline that went viral this summer. For many savvy internet users, myself included, it was the first time we were fooled by an AI video, and it ended up spawning a wave of almost identical riffs, with people making videos of all kinds of animals and objects bouncing on the same trampoline.

My first reaction was that, broadly speaking, all of this sucked. That’s become a familiar refrain, in think pieces and at dinner parties. Everything online is slop now—the internet “enshittified,” with AI taking much of the blame. Initially, I largely agreed, quickly scrolling past every AI video in a futile attempt to send a message to my algorithm. But then friends started sharing AI clips in group chats that were compellingly weird, or funny. Some even had a grain of brilliance buried in the nonsense. I had to admit I didn’t fully understand what I was rejecting—what I found so objectionable.

To try to get to the bottom of how I felt (and why), I recently spoke to the people making the videos, a company creating bespoke tools for creators, and experts who study how new media becomes culture. What I found convinced me that maybe generative AI will not end up ruining everything. Maybe we have been too quick to dismiss AI slop. Maybe there’s a case for looking beyond the surface and seeing a new kind of creativity—one we’re watching take shape in real time, with many of us actually playing a part.

The slop boom

“AI slop” can and does refer to text, audio, or images. But what’s really broken through this year is the flood of quick AI-generated video clips on social platforms, each produced by a short written prompt fed into an AI model. Under the hood, these models are trained on enormous data sets so they can predict what every subsequent frame should look or sound like. It’s much like the process by which text models produce answers in a chat, but slower and far more power-hungry.

Early text-to-video systems, released around 2022 to 2023, could manage only a few seconds of blurry motion; objects warped in and out of existence, characters teleported around, and the giveaway that it was AI was usually a mangled hand or a melting face. In the past two years, newer models like Sora2, Veo 3.1, and Runway’s latest Gen-4.5 have dramatically improved, creating realistic, seamless, and increasingly true-to-prompt videos that can last up to a minute. Some of these models even generate sound and video together, including ambient noise and rough dialogue.

These text-to-video models have often been pitched by AI companies as the future of cinema—tools for filmmakers, studios, and professional storytellers. The demos have leaned into widescreen shots and dramatic camera moves. OpenAI pitched Sora as a “world simulator” while courting Hollywood filmmakers with what it boasted were movie-quality shorts. Google introduced Veo 3 last year as a step toward storyboards and longer scenes, edging directly into film workflows.

All this hinged on the idea that people wanted to make AI-generated videos that looked real. But the reality of how they’re being used is more modest, weirder—and arguably much more interesting. What has turned out to be the home turf for AI video is the six-inch screen in our hands.

Anyone can and does use these tools; a report by Adobe released in October shows that 86% of creators are using generative AI. But so are average social media users—people who aren’t “creators” so much as just people with phones.

That’s how you end up with clips showing things like Indian prime minister Narendra Modi dancing with Gandhi, a crystal that melts into butter the moment a knife touches it, or Game of Thrones reimagined as Henan opera—videos that are hypnotic, occasionally funny, and often deeply stupid. And while micro-trends didn’t start with AI—TikTok and Reels already ran on fast-moving formats—it feels as if AI poured fuel on that fire. Perhaps because the barrier to copying an idea becomes so low, a viral video like the bunnies on trampoline can easily and quickly spawn endless variations on the same concept. You don’t need a costume or a filming location anymore; you just tweak the prompt, hit Generate, and share.

Big tech companies have also jumped on the idea of AI videos as a new social medium. The Sora app allows users to insert AI versions of themselves and other users into scenes. Meta’s Vibes app wants to turn your entire feed into nonstop AI clips.

Of course, the same frictionless setup that allows for harmless, delightful creations also makes it easy to generate much darker slop. Sora has already been used to create so many racist deepfakes of Martin Luther King Jr. that the King estate pushed the company to block new MLK videos entirely. TikTok and X are seeing Sora-watermarked clips of women and girls being strangled circulating in bulk, posted by accounts seemingly dedicated to this one theme. And then there’s “nazislop,” the nickname for AI videos that repackage fascist aesthetics and memes into glossy, algorithm-ready content aimed at teens’ For You pages.

But the prevalence of bad actors hasn’t stopped short AI videos from flourishing as a form. New apps, Discord servers for AI creators, and tutorial channels keep multiplying. And increasingly, the energy in the community seems to be shifting away from trying to create stuff that “passes as real” toward embracing AI’s inherent weirdness. Every day, I stumble across creators who are stretching what “AI slop” is supposed to look like. I decided to talk to some of them.

Meet the creators

Like those fake surveillance videos, many popular viral AI videos rely on a surreal, otherworldly quality. As Wenhui Lim, an architecture designer turned full-time AI artist, tells me, “There is definitely a competition of ‘How weird we can push this?’ among AI video creators.”

It’s the kind of thing AI video tools seem to handle with ease: pushing physics past what a normal body can do or a normal camera can capture. This makes AI a surprisingly natural fit for satire, comedy skits, parody, and experimental video art—especially examples involving absurdism or even horror. Several popular AI creators that I spoke with eagerly tap into this capability.

Drake Garibay, a 39-year-old software developer from Redlands, California, was inspired by body-horror AI clips circulating on social media in early 2025. He started playing with ComfyUI, a generative media tool, and ended up spending hours each week making his own strange creations. His favorite subject is morbid human-animal hybrids. “I fell right into it,” he says. “I’ve always been pretty artistic, [but] when I saw what AI video tools can do, I was blown away.”

Since the start of this year, Garibay has been posting his experiments online. One that went viral on TikTok, captioned “Cooking up some fresh AI slop,” shows a group of people pouring gooey dough into a pot. The mixture suddenly sprouts a human face, which then emerges from the boiling pot with a head and body. It has racked up more than 8.3 million views.

@digitalpersons

AI video technology is evolving so quickly that even for creative professionals, there is a lot to experiment with. Daryl Anselmo, a creative director turned digital artist, has been experimenting with the technology since its early days, posting an AI-generated video every day since 2021. He tells me that uses a wide range of tools, including Kling, Luma, and Midjourney, and is constantly iterating. To him, testing the boundaries of these AI tools is sometimes itself the reward. “I would like to think there are impossible things that you could not do before that are still yet to be discovered. That is exciting to me,” he says.

Anselmo has collected his daily creations over the past four years into an art project, titled AI Slop, that has been exhibited in multiple galleries, including the Grand Palais Immersif in Paris. There’s obvious attention to mood and composition. Some clips feel like something closer to an art-house vignette than a throwaway meme. Over time, Anselmo’s project has taken a darker turn as his subjects shift from landscapes and interior design toward more of the body horror that drew Garibay in.

His breakout piece, feel the agi, shows a hyperrealistic bot peeling open its own skull. Another video he shared recently features a midnight diner populated by anthropomorphized Tater Tots, titled Tot and Bothered; with its vintage palette and slow, mystical soundtrack, the piece feels like a late-night fever dream.

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A post shared by Daryl Anselmo (@darylanselmo)

One further benefit of these AI systems is that they make it easier for creators to build recurring spaces and casts of characters that function like informal franchises. Lim, for instance, is the creator of a popular AI video account called Niceaunties, inspired by the “auntie culture” in Singapore, where she’s from.

“The word ‘aunties’ often has a slightly negative connotation in Singaporean culture. They are portrayed as old-fashioned, naggy, and lacking boundaries. But they are also so resourceful, funny, and at ease with themselves,” she says. “I want to create a world where it’s different for them.”

Her cheeky, playful videos show elderly Asian women merging with fruits, other objects, and architecture, or just living their best lives in a fantasy world. A viral video called Auntlantis, which has racked up 13.5 million views on Instagram, imagines silver-haired aunties as industrial mermaids working in an underwater trash-processing plant.

There’s also Granny Spills, an AI video account that features a glamorous, sassy old lady spitting hot takes and life advice to a street interviewer. It gained 1.8 million Instagram followers within three months of launch, posting new videos almost every day. Although the granny’s face looks slightly different in every video, the pink color scheme and her outfit stay mostly consistent. Creators Eric Suerez and Adam Vaserstein tell me that their entire workflow is powered by AI, from writing the script to constructing the scenes. Their role, as a result, becomes close to creative directing.

@grannyspills

These projects often spin off merch, miniseries, and branded universes. The creators of Granny Spills, for example, have expanded their network, creating a Black granny as well as an Asian granny to cater to different audiences. The grannies now appear in crossover videos, as if they share the same fictional universe, pushing traffic between channels.

In the same vein, it’s now more possible than ever to participate in an online trend. Consider “Italian brainrot,” which went viral earlier this year. Beloved by Gen Z and Gen Alpha, these videos feature human–animal–object hybrids with pseudo-Italian names like “Bombardiro Crocodilo” and “Tralalero Tralala.” According to Know Your Meme, the craze began with a few viral TikTok sounds in fake Italian. Soon, a lot of people were participating in what felt like a massive collaborative hallucination, inventing characters, backstories, and worldviews for an ever-expanding absurdist universe.

@patapimai

“Italian brainrot was great when it first hit,” says Denim Mazuki, a software developer and content creator who has been following the trend. “It was the collective lore-building that made it wonderful. Everyone added a piece. The characters were not owned by a studio or a single creator—they were made by the chronically online users.”

This trend and others are further enabled by specialized and sophisticated new tools—like OpenArt, a platform designed not just for video generation but for video storytelling, which gives users frame-to-frame control over a developing narrative.

Making a video on OpenArt is straightforward: Users start with a few AI-generated character images and a line of text as simple as “cat dancing in a park.” The platform then spins out a scene breakdown that users can tweak act by act, and they can run it through multiple mainstream models and compare the results to see which look best.

OpenArt cofounders Coco Mao and Chloe Fang tell me they sponsored tutorial videos and created quick-start templates to capitalize specifically on the trend of regular people wanting to get in on Italian brainrot. They say more than 80% of their users have no artistic background.

In defense of slop

The current use of the word “slop” online traces back to the early 2010s on 4chan, a forum known for its insular and often toxic in-jokes. As the term has spread, its meaning has evolved; it’s now a kind of derogatory slur for anything that feels like low-quality mass production aimed at an unsuspecting public, says Adam Aleksic, an internet linguist. People now slap it onto everything from salad bowls to meaningless work reports.

But even with that broadened usage, AI remains the first association: “slop” has become a convenient shorthand for dismissing almost any AI-generated output, regardless of its actual quality. The Cambridge Dictionary’s new sense of “slop” will almost certainly cement this perception, describing it as “content on the internet that is of very low quality, especially when it is created by AI.”

Perhaps unsurprisingly, the word has become a charged label among AI creators.

Anselmo embraces it semi-ironically, hence the title of his yearslong art project. “I see this series as an experimental sketchbook,” he says. “I am working with the slop, pushing the models, breaking them, and developing a new visual language. I have no shame that I am deep into AI.” Anselmo says that he does not concern himself with whether his work is “art.”

Garibay, the creator of the viral video where a human face emerged from a pot of physical slop, uses the label playfully. “The AI slop art is really just a lot of weird glitchy stuff that happens, and there’s not really a lot of depth usually behind it, besides the shock value,” he says. “But you will find out really fast that there is a heck of a lot more involved, if you want a higher-end result.”

That’s largely in line with what Suerez and Vaserstein, the creators of Granny Spills, tell me. They actually hate it when their work is called slop, given the way the term is often used to dismiss AI-generated content out of hand. It feels disrespectful of their creative input, they say. Even though they do not write the scripts or paint the frames, they say they are making legitimate artistic choices.

Indeed, for most of the creators I spoke to, making AI content is rarely a one-click process. They tell me that it takes skill, trial and error, and a strong sense of taste to consistently get the visuals they want. Lim says a single one-minute video can take hours, sometimes even days, to make. Anselmo, for his part, takes pride in actively pushing the model rather than passively accepting its output. “There’s just so many things that you can do with it that go well beyond ‘Oh, way to go, you typed in a prompt,’” he says. Ultimately, slop evokes a lot of feelings. Aleksic puts it well: “There’s a feeling of guilt on the user end for enjoying something that you know to be lowbrow. There’s a feeling of anger toward the creator for making something that is not up to your content expectations, and all the meantime, there’s a pervasive algorithmic anxiety hanging over us. We know that the algorithm and the platforms are to blame for the distribution of this slop.”

And that anxiety long predates generative AI. We’ve been living for years with the low-grade dread of being nudged, of having our taste engineered and our attention herded, so it’s not surprising that the anger latches onto the newest, most visible culprit. Sometimes it is misplaced, sure, but I also get the urge to assert human agency against a new force that seems to push all of us away from what we know and toward something we didn’t exactly choose.

But the negative association has real harm for the earlier adopters. Every AI video creator I spoke to described receiving hateful messages and comments simply for using these tools at all. These messages accuse AI creators of taking opportunities away from artists already struggling to make a living, and some dismiss their work as “grifting” and “garbage.” The backlash, of course, did not come out of nowhere. A Brookings study of one major freelance marketplace found that after new generative-AI tools launched in 2022, freelancers in AI-exposed occupations saw about 2% decline in contracts and a 5% drop in earnings.

“The phrase ‘AI slop’ implies, like, a certain ease of creation that really bothers a lot of people—understandably, because [making AI-generated videos] doesn’t incorporate the artistic labor that we typically associate with contemporary art,” says Mindy Seu, a researcher, artist, and associate professor in digital arts at UCLA.

At the root of the conflict here is that the use of AI in art is still nascent; there are few best practices and almost no guardrails. And there’s a kind of shame involved—one I recognize when I find myself lingering on bad AI content.

Historically, new technology has always carried a whiff of stigma when it first appears, especially in creative fields where it seems to encroach on a previously manual craft. Seu says that digital art, internet art, and new media have been slow to gain recognition from cultural institutions, which remain key arbiters of what counts as “serious” or “relevant” art.

For many artists, AI now sits in that same lineage: “Every big advance in technology yields the question ‘What is the role of the artist?’” she says. This is true even if creators are not seeing it as a replacement for authorship but simply as another way to create.

Mao, the OpenArt founder, believes that learning how to use generative video tools will be crucial for future content creators, much as learning Photoshop was almost synonymous with graphic design for a generation. “It is a skill to be learned and mastered,” she says.

There is a generous reading of the phenomenon so many people call AI slop, which is that it is a kind of democratization. A rare skill shifts away from craftsmanship to something closer to creative direction: being able to describe what you want with enough linguistic precision, and to anchor it in references the model is likely to understand. You have to know how to ask, and what to point to. In that sense, discernment and critique sit closer to the center of the process than ever before.

It’s not just about creative direction, though, but about the human intention behind the creation. “It’s very easy to copy the style,” Lim says. “It’s very easy to make, like, old Asian women doing different things, but they [imitators] don’t understand why I’m doing it … Even when people try to imitate that, they don’t have that consistency.”

“It’s the idea behind AI creation that makes it interesting to look at,” says Zach Lieberman, a professor at the MIT Media Lab who leads a research group called Future Sketches, where members explore code-enabled images. Lieberman, who has been posting daily sketches generated by code for years, tells me that mathematical logic is not the enemy of beauty. He echoes Mao in saying that a younger generation will inevitably see AI as just another tool in the toolbox. Still, he feels uneasy: By relying so heavily on black-box AI models, artists lose some of the direct control over output that they’ve traditionally enjoyed.

A new online culture

For many people, AI slop is simply everything they already resent about the internet, turned up: ugly, noisy, and crowding out human work. It’s only possible because it’s been trained to take all creative work and make it fodder, stripped of origin, aura, or credit, and blended into something engineered to be mathematically average—arguably perfectly mediocre, by design. Charles Pulliam-Moore, a writer for The Verge, calls this the “formulaic derivativeness” that already defines so much internet culture: unimaginative, unoriginal, and uninteresting.

But I love internet culture, and I have for a long time. Even at its worst, it’s bad in an interesting way: It offers a corner for every kind of obsession and invites you to add your own. Years of being chronically online have taught me that the real logic of slop consumption isn’t mastery but a kind of submission. As a user, I have almost no leverage over platforms or algorithms; I can’t really change how they work. Submission, though, doesn’t mean giving up. It’s more like recognizing that the tide is stronger than you and choosing to let it carry you. Good scrolling isn’t about control anyway. It’s closer to surfing, and sometimes you wash up somewhere ridiculous, but not entirely alone.

Mass-produced click-bait content has always been around. What’s new is that we can now watch it being generated in real time, on a scale that would have been unimaginable before. And the way we respond to it in turn shapes new content (see the trampoline-bouncing bunnies) and more culture and so on. Perhaps AI slop is born of submission to algorithmic logic. It’s unserious, surreal, and spectacular in ways that mirror our relationship to the internet itself. It is so banal—so aggressively, inhumanly mediocre—that it loops back around and becomes compelling.

To “love AI slop” is to admit the internet is broken, that the infrastructure of culture is opportunistic and extractive. But even in that wreckage, people still find ways to play, laugh, and make meaning.

Earlier this fall, months after I was briefly fooled by the bunny video, I was scrolling on Rednote and landed on videos by Mu Tianran, a Chinese creator who acts out weird skits that mimic AI slop. In one widely circulated clip, he plays a street interviewer asking other actors, “Do you know you are AI generated?”—parodying an earlier wave of AI-generated street interviews. The actors’ responses seem so AI, but of course they’re not: Eyes are fixed just off-camera, their laughter a beat too slow, their movements slightly wrong.

Watching this, it was hard to believe that AI was about to snuff out human creativity. If anything, it has handed people a new style to inhabit and mock, another texture to play with. Maybe it’s all fine. Maybe the urge to imitate, remix, and joke is still stubbornly human, and AI cannot possibly take it away.

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