Data centers are amazing. Everyone hates them.

Behold, the hyperscale data center! 

Massive structures, with thousands of specialized computer chips running in parallel to perform the complex calculations required by advanced AI models. A single facility can cover millions of square feet, built with millions of pounds of steel, aluminum, and concrete; feature hundreds of miles of wiring, connecting some hundreds of thousands of high-end GPU chips, and chewing through hundreds of megawatt-hours of electricity. These facilities run so hot from all that computing power that their cooling systems are triumphs of engineering complexity in themselves. But the star of the show are those chips with their advanced processors. A single chip in these vast arrays can cost upwards of $30,000. Racked together and working in concert, they process hundreds of thousands of tokens—the basic building blocks of an AI model—per second. Ooooomph. 

Given the incredible amounts of capital that the world’s biggest companies have been pouring into building data centers you can make the case (and many people have) that their construction is single-handedly propping up the US stock market and the economy. 

So important are they to our way of life that none other than the President of the United States himself, on his very first full day in office, stood side by side with the CEO of OpenAI to announce a $500 billion private investment in data center construction.

Truly, the hyperscale datacenter is a marvel of our age. A masterstroke of engineering across multiple disciplines. They are nothing short of a technological wonder. 

People hate them. 

People hate them in Virginia, which leads the nation in their construction. They hate them in Nevada, where they slurp up the state’s precious water. They hate them in Michigan, and Arizona, and South Dakota, where the good citizens of Sioux Falls hurled obscenities at their city councilmembers following a vote to permit a data center on the city’s northeastern side. They hate them all around the world, it’s true. But they really hate them in Georgia. 

So, let’s go to Georgia. The purplest of purple states. A state with both woke liberal cities and MAGA magnified suburbs and rural areas. The state of Stacey Abrams and Newt Gingrich. If there is one thing just about everyone there seemingly agrees on, it’s that they’ve had it with data centers. 

Last year, the state’s Public Service Commission election became unexpectedly tight, and wound up delivering a stunning upset to incumbent Republican commissioners. Although there were likely shades of national politics at play (voters favored Democrats in an election cycle where many things went that party’s way), the central issue was skyrocketing power bills. And that power bill inflation was oft-attributed to a data center building boom rivaled only by Virginia’s. 

This boom did not come out of the blue. At one point, Georgia wanted data centers. Or at least, its political leadership did. In 2018 the state’s General Assembly passed legislation that provided data centers with tax breaks for their computer systems and cooling infrastructure, more tax breaks for job creation, and even more tax breaks for property taxes. And then… boom!   

But things have not played out the way the Assembly and other elected officials may have expected. 

Journey with me now to Bolingbroke, Georgia. Not far outside of Atlanta, in Monroe County (population 27,954), county commissioners were considering rezoning 900 acres of land to make room for a new data center near the town of Bolingbroke (population 492). Data centers have been popping up all across the state, but especially in areas close to Atlanta. Public opinion is, often enough, irrelevant. In nearby Twiggs County, despite strong and organized opposition, officials decided to allow a 300-acre data center to move forward. But at a packed meeting to discuss the Bolingbroke plans, some 900 people showed up to voice near unanimous opposition to the proposed data center, according to Macon, Georgia’s The Telegraph. Seeing which way the wind had blown, the Monroe county commission shot it down in August last year. 

The would-be developers of the proposed site had claimed it would bring in millions of dollars for the county. That it would be hidden from view. That it would “uphold the highest environmental standards.” That it would bring jobs and prosperity. Yet still, people came gunning for it. 

Why!? Data centers have been around for years. So why does everyone hate them all of the sudden? 

What is it about these engineering marvels that will allow us to build AI that will cure all diseases, bring unprecedented prosperity, and even cheat death (if you believe what the AI sellers are selling) that so infuriates their prospective neighbors? 

There are some obvious reasons. First is just the speed and scale of their construction, which has had effects on power grids. No one likes to see their power bills go up. The rate hikes that so incensed Georgians come as monthly reminders that the eyesore in your backyard profits California billionaires at your expense, on your grid. In Wyoming, for example, a planned Meta data center will require more electricity than every household in the state, combined. To meet demand for power-hungry data centers, utilities are adding capacity to the grid. But although that added capacity may benefit tech companies, the cost is shared by local consumers

Similarly, there are environmental concerns. To meet their electricity needs, data centers often turn to dirty forms of energy. xAI, for example, famously threw a bunch of polluting methane-powered generators at its data center in Memphis. While nuclear energy is oft-bandied about as a greener solution, traditional plants can take a decade or more to build; even new and more nimble reactors will take years to come online. In addition, data centers often require massive amounts of water. But the amount can vary widely depending on the facility, and is often shrouded in secrecy. (A number of states are attempting to require facilities to disclose water usage.) 

A different type of environmental consequence of data centers is that they are noisy. A low, constant, machine hum. Not just sometimes, but always. 24 hours a day. 365 days a year. “A highway that never stops.” 

And as to the jobs they bring to communities. Well, I have some bad news there too. Once construction ends, they tend to employ very few people, especially for such resource-intensive facilities. 

These are all logical reasons to oppose data centers. But I suspect there is an additional, emotional one. And it echoes one we’ve heard before. 

More than a decade ago, the large tech firms of Silicon Valley began operating buses to ferry workers to their campuses from San Francisco and other Bay Area cities. Like data centers, these buses used shared resources such as public roads without, people felt, paying their fair share. Protests erupted. But while the protests were certainly about shared resource use, they were also about something much bigger. 

Tech companies, big and small, were transforming San Francisco. The early 2010s were a time of rapid gentrification in the city. And what’s more, the tech industry itself was transforming society. Smartphones were newly ubiquitous. The way we interacted with the world was fundamentally changing, and people were, for the most part, powerless to do anything about it. You couldn’t stop Google. 

But you could stop a Google bus. 

You could stand in front of it and block its path. You could yell at the people getting on it. You could yell at your elected officials and tell them to do something. And in San Francisco, people did. The buses were eventually regulated. 

The data center pushback has a similar vibe. AI, we are told, is transforming society. It is suddenly everywhere. Even if you opt not to use ChatGPT or Claude or Gemini, generative AI is  increasingly built into just about every app and service you likely use. People are worried AI will harvest jobs in the coming years. Or even kill us all. And for what? So far, the returns have certainly not lived up to the hype

You can’t stop Google. But maybe, just maybe, you can stop a Google data center. 

Then again, maybe not. The tech buses in San Francisco, though regulated, remain commonplace. And the city is more gentrified than ever. Meanwhile, in Monroe County, life goes on. In October, Google confirmed it had purchased 950 acres of land just off the interstate. It plans to build a data center there. 

The Download: next-gen nuclear, and the data center backlash

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

How next-generation nuclear reactors break out of the 20th-century blueprint  

The popularity of commercial nuclear reactors has surged in recent years as worries about climate change and energy independence drowned out concerns about meltdowns and radioactive waste. The problem is, building nuclear power plants is expensive and slow.  

A new generation of nuclear power technology could reinvent what a reactor looks like—and how it works. Advocates hope that new tech can refresh the industry and help replace fossil fuels without emitting greenhouse gases.  Here’s what that might look like.

—Casey Crownhart

Next-gen nuclear is one of our 10 Breakthrough Technologies this year. If you want to learn more about why it made the list, sign up to receive The Spark, our weekly newsletter all about energy and climate change, tomorrow. You can also check out the rest of the technologies on the list here.

Data centers are amazing. Everyone hates them.

The hyperscale datacenter is a marvel of our age. A masterstroke of engineering across multiple disciplines. They are nothing short of a technological wonder. People hate them.  

People hate them in Virginia, which leads the nation in their construction. They hate them in Nevada, where they slurp up the state’s precious water. They hate them in Michigan, and Arizona, and South Dakota. They hate them all around the world, it’s true. But they really hate them in Georgia. Read our story about why they’re provoking so much fury

—Mat Honan

This story first featured in The Debrief with Mat Honan, a weekly newsletter about the biggest stories in tech from our editor in chief. Sign up here to get the next one in your inbox on Friday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Iran is systematically crippling Starlink
The satellite internet service is meant to be impossible to jambut the Iranian authorities are doing just that. (Rest of World)  
Messages getting around Iran’s internet block suggest that thousands of people have been killed. (NYT $)
On the ground in Ukraine’s largest Starlink repair shop. (MIT Technology Review)

2 Studies claiming microplastics harm us are being called into question
Some scientists say the discoveries are probably the result of contamination and false positives. (The Guardian

3 Trump is trying to temper the data center backlash 
He hopes cajoling tech companies to pay more and thus reduce people’s energy bills will do the trick. (WP $) 
Microsoft has just become the first tech company to promise it will do just that. (NYT $)
We know AI is power hungry. But just how big is the scale of the problem? (MIT Technology Review

4 US emissions jumped last year
Thanks to a combination of rising electricity demand, and more coal being burned to meet it. (NYT $)
But it’s not all bad news: coal power generation in India and China finally started to decline. (The Guardian)
Four bright spots in climate news in 2025. (MIT Technology Review)

5 Elon Musk needs to face consequences for his actions
If we tolerate him unleashing a flood of harassment of women and children, what will come next? (The Atlantic $) 
The US Senate has passed a bill that could give non-consensual deepfake victims a new way to fight back. (The Verge $)

6 Why the US is set to lose the race back to the moon 🚀🌔
Cuts to NASA aren’t helping, but they’re not the only problem. (Wired $)

7 Google’s Veo AI model can now turn portrait images into vertical videos
Really slick ones, too. (The Verge $)
AI-generated influencers are sharing fake images of them in bed with celebrities on Instagram. (404 Media $)

8 Former NYC mayor Eric Adams has been accused of a crypto ‘pump and dump’ 
He promoted a token that saw its market cap briefly soar to $580 million before plummeting. (Coindesk)

9 Are you a middle manager? Here’s some good news for you
Your skills are not being replaced by AI any time soon. (Quartz

10 Even miniscule lifestyle tweaks can extend your lifespan
A study of 60,000 adults found just a little bit more sleep and exercise makes a huge difference. (New Scientist $)
Aging hits us in our 40s and 60s. But well-being doesn’t have to fall off a cliff. (MIT Technology Review)

Quote of the day

“What I’m hopeful for in ’26 is for more people speaking up. Speaking truth to power is the point of freedom of speech, is the point of American society.”

—LinkedIn cofounder Reid Hoffman tells Wired he wants more people in Silicon Valley to start pushing back against the Trump administration this year. 

One more thing

two women collaborating on their laptops in a lecture hall

DEEP LEARNING INDABA 2024

What Africa needs to do to become a major AI player

Africa is still early in the process of adopting AI technologies. But researchers say the continent is uniquely hospitable to it for several reasons, including a relatively young and increasingly well-educated population, a rapidly growing ecosystem of AI startups, and lots of potential consumers.  

However, ambitious efforts to develop AI tools that answer the needs of Africans face numerous hurdles. Taken together, researchers worry, they could hold Africa’s AI sector back and hamper its efforts to pave its own pathway in the global AI race. Read the full story.

—Abdullahi Tsanni

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ Still keen to do a bit of reflecting on the year behind and the one ahead? This free guide might help!
+ Turns out British comedian Rik Mayall had some pretty solid life advice.
+ I want to stay in this house in São Paolo.  
+ If you want to stop doomscrolling, it’s worth looking at your sleep habits. ($)

New Ecommerce Tools: January 14, 2026

Our rundown this week of new products and services for ecommerce merchants includes updates on agentic commerce, product reviews, A/B testing, post-purchase experiences, cryptocurrency payments, fulfillment, analytics, personalization, and packaging.

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

New Tools for Merchants

Google launches an open standard for agentic commerce. Google is launching the Universal Commerce Protocol, an open standard for agentic commerce, establishing a common language for agents and systems to operate together across consumer surfaces, businesses, and payment providers. UCP is compatible with existing industry protocols, such as Agent2Agent, Agent Payments Protocol, and Model Context Protocol. Google co-developed UCP with industry leaders, including Shopify, Etsy, and Walmart. More than 20 others across the payment ecosystem have endorsed UCP, including Adyen, Flipkart, Mastercard, Visa, and Stripe.

Home page of Universal Commerce Protocol

Universal Commerce Protocol

PayPal powers Microsoft’s launch of Copilot Checkout. PayPal is partnering with Microsoft in support of Checkout, enabling shoppers to discover, decide, and pay without leaving the Copilot experience. PayPal will surface merchant inventory, branded checkout, guest checkout, and credit card payments, starting with Copilot.com. Copilot uses AI to bring context and intent into the shopping journey. Users can now browse curated, shoppable results and complete their purchase with PayPal.

Amazon to limit reviews across product variations. Amazon is changing how reviews are shared across products. Amazon has heretofore shared reviews across all variations of a product, even when they differ significantly. Now, to improve accuracy and help shoppers make more informed purchasing decisions, Amazon will share only reviews between variations with minor differences that don’t affect functionality.

Kibo Commerce announces Connect Hub and MCP. Kibo Commerce, a platform for composable commerce, has launched two product offerings. The new Connect Hub helps scale pre-built integrations to platforms across various product categories, including ecommerce and marketplaces. Merchants gain access to a network of 3,300 trading partners and hundreds of payment and shipping adapters. The new Kibo MCP integrates enterprise commerce logic and generative AI tools.

Fluent Commerce launches order sourcing logic with A/B testing. Fluent Commerce, an order management system, has announced the launch of AI-powered order sourcing logic with A/B testing. Users can compare the outcomes of two sets of order sourcing logic run in parallel to see the impact on net margin, fulfillment and delivery costs, split shipment rate, order-to-door time, and average delivery distance, and to calculate carbon impact. The capability enables retailers to continuously learn from their fulfillment network, according to Fluent Commerce.

Home page of Fluent Commerce

Fluent Commerce

Route acquires Frate Returns for ecommerce post-purchase experiences. Route, a post-purchase platform for ecommerce brands, has acquired Frate Returns, a returns-and-exchanges platform. By integrating Frate’s returns-and-exchanges software, Route now offers merchants a single integrated platform to manage the customer journey after checkout. According to Route, Frate’s capabilities (exchange-first optimization, AI image verification, and flexible shipping, refund, and payment options) allow brands to reduce refund rates and operational costs while retaining revenue and increasing loyalty.

Crypto.com partners with Stripe. Crypto.com, a global cryptocurrency platform, is partnering with Stripe to expand payment options. The collaboration will allow Crypto.com users to pay for everyday goods and services using their crypto balances at Stripe-powered merchants across the U.S. The integration will appear as a new payment option on the checkout pages of participating merchants that use Stripe’s Optimized Checkout Suite.

UCanPack launches tall ecommerce boxes. UCanPack, a provider of packaging and shipping supplies, has introduced a line of engineered tall boxes for ecommerce merchants. According to UCanPack, the line features impact resistance and crush protection and is right-sized for elongated and narrow goods, such as lamps, tripods, sports gear, decor, and rolled materials. UCanPack aims to help brands reduce transit damage and streamline pack bench workflows.

Shoplazza launches fulfillment option. Shoplazza, a global commerce platform serving direct-to-consumer brands, has launched Fulfillment by Shoplazza to help merchants navigate global logistics. Shoplazza says its new fulfillment service integrates global warehousing, last-mile delivery, financial automation, and real-time risk controls to provide merchants with a predictable and scalable logistics engine. Key capabilities include zero-prepayment logistics, revenue-aligned billing, embedded financial tools, global and localized fulfillment options, and a compliant logistics network, per Shoplazza.

Home page of Shoplazza

Shoplazza

Stackline unveils analytics for AI-powered commerce platforms. Stackline, a provider of retail analytics and connected commerce, has launched AI Visibility, offering insights into how shoppers discover and interact with products via conversational and agentic shopping platforms. According to Stackline, participating merchants can (i) measure the volume of real shopping questions across leading AI platforms, (ii) bring results from ChatGPT, Amazon Rufus, and more into a unified analytical environment, (iii) view detailed product competitive insights, and (iv) analyze which products frequently appear in recommendations together.

Blue Yonder launches AI-related updates to its planning platform. Blue Yonder, a supply chain platform, has released AI updates aimed at increasing agility and optimizing customer experiences. The updates, per Blue Yonder, strengthen its supply chain network of 172,000 global trading partners, improving efficiency and responsiveness.

Lightspeed Commerce launches AI assistants. Lightspeed Commerce, an omnichannel platform powering businesses in over 100 countries, has launched Lightspeed AI for agent-driven workflows, including conversational assistants for retail and restaurants. The assistants help merchants ask questions, get answers quickly, and make smarter decisions without navigating dashboards or reports.

Bloomreach’s AI-powered search now available on AWS Marketplace. Bloomreach, an ecommerce personalization provider, announced its AI-powered search tool is now available on Amazon Web Services Marketplace. Loomi AI, Bloomreach’s intelligence platform, brings personalization across email, SMS, web, app, search, and more. Via the AWS Marketplace, businesses can now discover and deploy Loomi AI-powered tools to capture first-party customer and product data and add context and decision-making in customer journeys, per Bloomreach.

Home page of Bloomreach

Bloomreach

YouTube Expands Monetization For Some Controversial Issues via @sejournal, @MattGSouthern

YouTube is updating its Advertiser-friendly content guidelines to allow more videos about certain “controversial issues” to earn full ad revenue, as long as the content is non-graphic and presented in a dramatized or discussion-based context.

The change was outlined in a Creator Insider video and is reflected in YouTube’s Help Center policy language.

What’s Changing

YouTube is loosening monetization restrictions for videos focused on controversial issues that advertisers may define as sensitive, including abortion, self-harm, suicide, and domestic and sexual abuse, when the content is “dramatized or discussed in a non-graphic manner.”

YouTube’s Help Center update describes the change, stating that content focused on “Controversial issues” is now eligible to earn ad revenue when it’s non-graphic and dramatized, and that this replaces a previous policy that limited monetization regardless of graphicness or whether content was fictional.

The current “Controversial issues” policy section also explicitly includes “non-graphic but descriptive or dramatized content” related to domestic abuse, self-harm, suicide, adult sexual abuse, abortion, and sexual harassment under the category that “can earn ad revenue.”

How YouTube Defines “Controversial Issues”

YouTube defines “Controversial issues” as topics associated with trauma or abuse, and notes the policy may apply even if the content is purely commentary.

The Help Center list includes child abuse, adult sexual abuse, sexual harassment, self-harm, suicide, eating disorders, domestic abuse, and abortion.

It also distinguishes between content that is “focal” versus “fleeting.” A passing reference is not considered a focus, whereas a sustained segment or a full-video discussion is.

Why This Matters

This update can change whether videos qualify for full ad revenue.

YouTube is drawing a clearer line between non-graphic dramatization or discussion (more likely to be eligible) and content that includes graphic depictions or very explicit detail (still likely to be restricted).

As with past advertiser-friendly updates, real-world outcomes can depend on how a specific upload is categorized during review, including signals from the video itself plus title and thumbnail.

Looking Ahead

It’s unknown whether previously limited videos will be re-reviewed automatically, or only on appeal.

Regardless, you shouldn’t wait for YouTube to do the work. Now is a great time to submit an appeal if your videos were affected by YouTube’s controversial issues policy.


Featured Image: Reyanaska/Shutterstock

Why Paid Search Foundations Still Matter In An AI-Focused World

At this point in time, AI search products such as Google and Microsoft’s PMax (and now AI Max) have firmly woven themselves into the toolkits of search marketers around the globe. But as many search marketers rush to not only test new products but also scale paid search activity, there is an increasing tendency to neglect the core elements of what makes a successful paid search account: audience, structure, and intent.

Within this article, I’ll aim to throw paid search foundations back into the limelight, placing an emphasis on why core concepts remain important and highlighting the fact that AI products don’t necessarily replace foundations but only serve to enhance them.

How We Got Here

It is, of course, important to stress that the shift towards AI prevalence has been a gradual one. From the early days of obsessing over match types and manual cost-per-click (CPCs) to Smart Bidding playing a greater role in finding customers across varying points of the user journey – we’ve come a long way to get here. With products such as PMax claiming to “do it all for you,” we can see that the “hands on” approach of yesteryear has become less active.

With every step taken towards the current climate, we have handed a little more control to the machine. While this has allowed us to scale campaigns on a much greater level, when comparing the role of a PPC manager now to 10 years ago, the day-to-day tasks look exponentially different.

But as automation has increased, so has the machines’ reliance upon clean and consistent foundations. AI features can only optimize based on what we feed it. If structure, signals, or audiences aren’t clear, the machine has no concept of what “good” looks like. Because of this, AI hasn’t removed the need for fundamentals; it’s made them more important.

Structure Is Still Integral To Success

Automated systems and products such as PMax encourage greater levels of consolidation through feeding insights to the algorithm and letting it decide what works best for us. However, in practice, structure remains one of the biggest drivers around whether AI drives success or not.

PMax is not psychic. It doesn’t have a full understanding of specific product margins your business may have, your product development lines, or your business’ full commercial realities (yet!). The only way to do this is to make those distinctions clear. This is where structure comes in! A well-structured account provides boundaries for the machine to work with. It helps by:

  • Providing clean learning environments: Grouping products and services in a logical manner helps to ensure that products such as PMax aren’t trying to learn everything all at once. Through clear separation, you increase the likelihood of more accurate outcomes.
  • Maintaining budget control: If everything is thrown into one campaign, it makes it increasingly more difficult to avoid under-performing products from cannibalizing budget.
  • Reducing conflicting intent: When campaigns mix differing intents (e.g., providing varying conversion actions that are contradictory from a user journey standpoint), the machine receives much greater volumes of noise. Through clear separation and delineation within a well-structured account, advertisers can reduce skewed data and improve performance.
Clear structure isn’t something to be ignored. It’s the backbone to improving AI performance. (Image from author, November 2025)

Audience Insight Remains AI’s Compass

When it comes to understanding people, human marketers will always hold a competitive advantage. Knowing why people convert, what motivates them, and ultimately, the understanding of human nature will always mean that human marketers have an intrinsic intuition that search features such as PMax will never have. Acknowledging this, it’s key that humans feed quality customer insights into these platforms to ensure that the machine can gain a better understanding of what makes us tick.

As an example, a family car buyer and a luxury SUV buyer may both search for [SUV cars], but their motivations and expectations differ dramatically. AI can easily cluster this behavior, but it takes human insight to translate that behavior into effective positioning.

Taking this into account, the foundational understanding of a) what makes a solid audience grouping and b) how to implement said audience is again where foundational understanding comes into play. The strongest performing PMax campaigns are the ones filled with the richest insights. CRM, loyalty information, and higher intent user signals often significantly improve PMax’s ability to drive performance. AI products can only feed off information you provide, and those signals must be rooted in real audience understanding.

When you understand your audience deeply, AI has a stronger foundation to optimize from. When you don’t, you leave the machine to guess.

Intent (And Keywords) Still Drive Everything

It could be argued that automation has accelerated the death of keywords, but what it hasn’t done is decrease the importance of intent. Search has always been (and remains!) an intent-driven channel. PMax might automate placements and assets, but it still requires queries and signals to understand what someone wants.

We might now be seeing fewer search queries (much to my annoyance!), but the system is still learning from billions of intent signals. Taking this into account, having a core, foundational understanding of intent enables you to:

Identify and prevent wasted spend. ALWAYS my ace card. Negatives and keyword exclusions remain critical in helping to guide AI products. Advertisers who refine intent signals almost always outperform those who automatically assume that ‘leaving it to the machine’ is the best approach.

Match creative with motivation. Understanding customer intent will help to ensure that you avoid over-generic ad copy and craft content that customers actually engage with.

Align landing pages with behavior. AI can send traffic to your pages, but if the content doesn’t match user intent, account efficiency will be impacted.

A Whole New World

To quote the 1992 Disney classic “Aladdin,” it really is a whole new world (pretty sure they had PMax in mind when writing that song…). However, while the further acceleration of AI products may have changed the mechanics of search advertising, what it hasn’t done is make the fundamentals less important.

Audience insight still guides strategy. Intent still shapes relevance of content. Structure still shapes accuracy. These are not only essentials that have stood the test of time but will also provide a clear advantage to advertisers who can recognize their benefit.

The future of paid search truly isn’t a case of fighting the machine; it’s about ensuring we influence the algorithms by providing richer context and insight, in turn utilizing their ability to scale to further drive results.

More Resources:


Featured Image: N Universe/Shutterstock

Social Media Trust Is Breaking Down (And How You Can Rebuild It) via @sejournal, @donutcaramel13

Social media is an integrated part of life in the U.S., with usage growing among adults. Pew Research Center reports that YouTube (84%) and Facebook (71%) remain the most widely used platforms for U.S. adults, followed by 50% of adults using Instagram.

What we should pay attention to is that people’s trust levels have changed. Americans turn to social media for local news and product research, but no longer trust every voice equally. According to Pew Research, trust in national and local news organizations is declining across all age groups. According to Ipsos Global Trustworthiness Monitor, only 22% of the public trusts social media companies.

With bots, fake reviews, and undisclosed AI-generated content flooding channels, authenticity becomes more essential than ever.

As trust in platforms’ ability to moderate or surface credible information has weakened, many users now look to individual creators they already trust, to help interpret or contextualize information, rather than relying solely on platform-level controls or algorithms. This is an opportunity for creators who can provide credibility.

This article takes a closer look at the factors that lose people’s trust, what rebuilds it, and what marketers can do to ensure they stay trusted.

What’s Not Working

Perfection and over-engineered AI-generated content are not what resonates with audiences and users. Companies that forget to be human-first could find their campaigns backfire, as in the case of this AI firm that commissioned a billboard featuring an AI employee and the tagline: “Stop Hiring Humans.” And Coca-Cola with its AI-generated holiday ad.

To keep building human-focused content and to engage with your audience through authenticity, avoid the following:

Overly Polished Content & Using AI Models

Audiences are quick to recognize overly “clean” content and AI models. While they’re usually a very engaging brand, Ryanair’s recent AI-generated TikTok didn’t land with people (pun intended):

@ryanair

catch a grip 🙄 #ryanair

♬ original sound – Ryanair

If you read some of the negative comments, they focused on how disappointed people are with the airline service. One commenter remarked, “Why is Ryanair using AI?” and another user added, “Saves money. That’s all they care about.”

For a brand that is usually so self-effacing and quick to respond, this time, it looks like they missed the opportunity to be themselves and connect.

While it is true that AI can save more money (according to a survey conducted by Ahrefs, human-written content costs 4.7x more than AI-generated content), it reduces believability.

Consider Trivago’s commercial, originally featuring German football manager Jurgen Klopp, who starred in the brand’s AI-powered ads; he was replaced with an AI lookalike to the dismay and confusion of viewers who posted about it on Reddit. Read the comments on the lookalike video.

Tone Deaf Concepts

While not a social media example, Apple’s “Crush” iPad Pro Ad is an example of a big brand that usually gets it right, getting it very wrong. Apple had to withdraw the ad after negative reactions, even though the production was high-quality and polished. Viewers called it “soul crushing.”

The ad depicted heavy instruments: pianos, guitars, cameras, and paintings, being crushed into a single iPad, suggesting that the thinnest iPad can replace the things that people cherished over hundreds and even thousands of years. But, inadvertently, it dismissed human creativity.

The concept was considered tone deaf and disappointed Apple fans, who are usually such ardent supporters of their creativity.

The example highlights how the right tone is essential to get your audience to connect with your messaging. Users will respond less to generic brand messaging that feels like it was scripted by ChatGPT. Invoking positive emotions in your content that tie in with your brand values should be your focus.

Undisclosed Synthetic Content & The Risk Of Misinformation

According to a study conducted at Rutgers University, public views on AI are mixed: While AI can assist with automation and data analysis, people prefer human storytelling for content. Users can spot AI-crafted texts and scripts easily because of tells like em-dashes and punctuation.

Suspecting undisclosed AI-generated content could drive your users away: Over half (52%) of social media users are concerned about brands posting AI-generated content without disclosing it.

And according to Ahrefs, 62% of respondents cited the biggest perceived risk of using AI as sharing misinformation. In the same study, most people (65%) regard human-written content as higher quality than AI-generated content.

Replacing The Human Touch

While AI can be cost-effective as mentioned above, LLMs erode trust when they replace the writing of lived real experience. As a case in point, there was immediate backlash to Google’s Gemini commercial “Dear Sydney.” A father asks Gemini to help him write a letter to Olympian Sydney McLaughlin-Levrone about how inspiring she is.

Viewers called it sad and disturbing, with one commenting that it “completely negates why someone would write a letter to an athlete or anyone for that matter.”

How Marketers Can Demonstrate Trust

Authenticity will always prevail in marketing. When you’re honest with your users about your product and what you can offer them, your campaigns will resonate more. Aside from avoiding the pitfalls, here are tips that we recommend for a proactive approach:

Collaborate With Micro-Creators And Subject-Matter Voices

According to a Deloitte survey, “roughly 50% of Gen Zs and millennials surveyed say they feel a stronger personal connection to social media creators than they do with TV personalities or actors.”

Meaning good influencer marketing for your niche, demonstrating real product use, pros and cons, and reasoning will help instead of hurting your brand.

Choose Credible Partners Over Famous Ones

Three in 10 U.S. adult social media users say they have purchased something after seeing an influencer or content creator post about it. However, they don’t rely on follower counts for reach to establish trust. Studies find that “authenticity’s direct effect on the number of followers is not statistically significant.”

Choosing a creator to partner with is less about reach and more about how they align with your brand values and their expertise they demonstrate. Select the creator with the expertise to effectively review your product and craft compelling content about it.

According to Influencer Marketing Hub’s Influencer Marketing Benchmark Report 2025, brands are shifting towards nano and micro-influencers for targeted, cost-effective collaborations. It works because smaller creators are widely seen to be more relatable and authentic, showing real product use and reasoning in their testimonials, and are trusted within their communities.

Ensure Transparency And Clear Disclosures

Sprout’s Pulse Survey in Q2 2024 found that 94% of consumers believe all AI content should be disclosed. While there’s no universal law yet, AI-disclaiming brands using AI need to disclose AI content. The FTC released a final rule in August 2024 that banned fake reviews and testimonials. To support responsible content practices, TikTok has labels for disclosing AI-generated content, and Meta began adding “AI info” to video, audio, and image content across their platforms. YouTube requires certain effects and synthetic content to be flagged as “Altered Content” during video creation.

Being transparent about partnerships and brand deals will help increase trust with your consumers. According to Sprout Social, 86% of survey respondents said that they would be more likely to give the company a second chance after a bad experience if it has a history of transparency.

As Google’s Search Quality Rater Guidelines have reiterated, trust is the crucial component of E-E-A-T, so keep demonstrating that you’re transparent about who is behind your content, maintain a positive reputation, and follow ethical content practices.

Monitor Your Brand Mentions Alongside AI

If you think you’re safe because your brand doesn’t use AI, think again. Users who are disenfranchised with AI may have a negative perception of your brand if they see unofficial ads on AI-generated, low-quality content.

In an email to Marketing Brew, Google spokesperson Nate Funkhouser said, “YouTube doesn’t currently offer advertisers the ability to opt out of appearing next to AI-generated content.”

It’s always good practice to monitor where your brand shows up and disassociate from fake content to remain trustworthy.

Tap Into UGC And Human-Led Brand Presence

Brands still need a human voice and faces to represent them, craft compelling narratives, and convey their messages professionally.

A good example is HubSpot’s Instagram content, which uses its marketing manager to humanize its marketing content (this example is about retargeting ads).

UGC gives your customers a sense of participation and is more trustworthy than content from a third party, since it isn’t commissioned. Not to mention, Google also surfaces more video, forums, and UGC in response to user behavioral shifts in seeking quality content.

Support Community-Led Content

Invest in creators and groups with genuine influence in your category.

Lastly, participate where the conversations happen. Niche communities on Reddit, Discord, and Threads are also great for truly connecting with your audience in a transparent way, while customers benefit by getting transparent feedback. What works in these communities is engaging in conversations, rather than just having them watch streams of your content.

What’s likely to work? Hosting AMAs and helping solve problems using Reddit vs. selling with an AI-generated avatar that misses all emotional connection to your audience? We recommend the former.

Trust Is Being Rebuilt Through People, Not Platforms

Instead of solely investing in AI to generate more creative assets, try partnering with nano-influencers, adding more context and disclosures to your campaigns, and facilitating lively UGC campaigns over communities in platforms like Reddit.

People don’t get inspired by a bot or someone who hasn’t actually lived the experience. Your brand earns your audience’s trust through relatable creators and thoughtfully crafted content.

The brands that win are ultimately the brands that feel more human, and the decision to lean into human-led content is yours.

More Resources: 


Featured Image: hmorena/Shutterstock

Google: AI Mode Checkout Can’t Raise Prices via @sejournal, @MattGSouthern

Google is disputing claims that its new AI-powered shopping checkout work could enable what critics describe as “surveillance pricing” or other forms of overcharging.

The back-and-forth started after Lindsay Owens, executive director of consumer economics think tank Groundwork Collaborative, criticized Google’s newly announced Universal Commerce Protocol and pointed to language in its public roadmap about “cross-sell and upsell modules.”

U.S. Sen. Elizabeth Warren amplified the criticism, saying Google is “using troves of your data to help retailers trick you into spending more money.”

Google’s corporate account News from Google replied that the claims “around pricing are inaccurate,” adding that merchants are prohibited from showing higher prices on Google than what appears on their own sites.

What Triggered The Back-And-Forth

Owens wrote on X that Google’s announcement about integrating shopping into AI Mode and Gemini included “personalized upselling,” which she described as “analyzing your chat data and using it to overcharge you.”

Warren then reposted Owens’ thread and echoed the allegation in stronger terms, calling it “plain wrong” that Google would use user data to help retailers “trick you into spending more money.”

Google responded publicly on X with a thread disputing the premise.

News from Google wrote on X:

“These claims around pricing are inaccurate. We strictly prohibit merchants from showing prices on Google that are higher than what is reflected on their site, period.”

Google also addressed the “upselling” term directly:

“The term ‘upselling’ is not about overcharging. It’s a standard way for retailers to show additional premium product options that people might be interested in.”

And it added that “Direct Offers” can only move in one direction:

“‘Direct Offers’ is a pilot that enables merchants to offer a lower priced deal or add extra services like free shipping … it cannot be used to raise prices.”

Where “Upsell Modules” Shows Up

The language critics are pointing to is in the Universal Commerce Protocol roadmap, which lists “Native cross-sell and upsell modules” as an upcoming initiative, described as enabling “personalized recommendations and upsells based on user context.”

Separately, Google’s technical write-up on UCP says AI shopping experiences need support for things like “real-time inventory checks, dynamic pricing, and instant transactions” within a conversational context. The “dynamic pricing” phrasing is broad, but it is part of what critics are interpreting through a consumer protection lens.

Google’s Ads & Commerce blog post presents UCP as covering the entire shopping journey, linking it to AI Mode and Gemini, while emphasizing that retailers stay the seller of record.

Why This Matters

I have covered Google’s price accuracy enforcement going back years, including Merchant Center policies meant to prevent situations where a shopper sees one price and gets a higher one at checkout. That history is why the “prices on Google versus prices on your site” line is doing so much work in Google’s response.

The bigger picture is that Google is trying to turn AI Mode and Gemini into places where product discovery can end with a transaction. When that happens, the conversation stops being purely about relevance and starts being about pricing rules, disclosures, and what “personalization” means in practice.

Looking Ahead

If this becomes another layer of feed requirements and policy edge cases, retailers will feel it immediately. If it reduces drop-off between product discovery and checkout, Google will likely push harder to make it a default part of AI Mode shopping.


Featured Image: zikg/Shutterstock

What Google SERPs Will Reward in 2026 [Webinar] via @sejournal, @lorenbaker

The Changes, Features & Signals Driving Organic Traffic Next Year

Google’s search results are evolving faster than most SEO strategies can adapt.

AI Overviews are expanding into new keyword and intent types, AI Mode is reshaping how results are displayed, and ongoing experimentation with SERP layouts is changing how users interact with search altogether. For SEO leaders, the challenge is no longer keeping up with updates but understanding which changes actually impact organic traffic.

Join Tom Capper, Senior Search Scientist at STAT Search Analytics, for a data-backed look at how Google SERPs are shifting in 2026 and where real organic opportunities still exist. Drawing from STAT’s extensive repository of daily SERP data, this session cuts through speculation to show which features and keywords are worth prioritizing now.

What You’ll Learn

  • Which SERP features deliver the highest click potential in 2026
  • How AI Mode features are showing up and initiatives to prioritize
  • The keyword and topic opportunities that still drive organic traffic next year

Why Attend?

This webinar offers a clear, evidence-based view of how Google SERPs are changing and what those changes mean for SEO strategy. You will gain practical insights to refine keyword targeting, focus on the right SERP features, and build an organic search approach grounded in real performance data for 2026.

Register now to understand the SERP shifts shaping organic traffic in 2026.

🛑 Can’t make it live? Register anyway and we’ll send you the on demand recording after the event.

5 Ways To Reduce CPL, Improve Conversion Rates & Capture More Demand In 2026 via @sejournal, @CallRail

The marketers who crack attribution aren’t chasing perfection; they’re layering multiple data sources to get progressively closer to the truth.

What To Do: Identify Which Marketing Efforts Are Actually Working

A starting point: add a simple “How did you hear about us?” field to your intake process, then compare those responses against your digital attribution data.

The gaps you uncover will show you exactly where your current tracking is falling short, and where your brand and word-of-mouth efforts are working harder than you realized.

Learn more about self-reported attribution and how it can transform your reporting →

Improve Conversion Rates By Learning & Implementing What Buyers Ask Before They Convert

There’s a goldmine sitting right under your nose: your customer conversations.

Most marketers hand off call data to sales and never look back. Big mistake.

Avoid This Myth: “Call Insights Are Only For Sales Teams”

Those conversations contain exactly what you need to create more personalized marketing communications and sharpen your strategy.

Literal Keys To Conversion Are Hiding In Your Sales Team’s Call Data

Think about what’s buried in your call recordings:

  • Conversion signals for better targeting. When you understand what makes callers convert, you can build lookalike audiences and refine your ad targeting around those characteristics.
  • Sentiment data for email segmentation. Callers who expressed frustration need different nurture sequences than those who were enthusiastic. Conversation intelligence can automatically score sentiment, letting you segment accordingly.
  • Caller details for personalization. Names, pain points, specific needs—these details can feed directly into personalized follow-up campaigns.
  • Term analysis for more relatable ad creation. What words do your best prospects actually use? Call transcripts reveal the language that resonates, helping you craft offers that speak directly to buyer needs.
  • Keyword clouds for SEO and PPC. The phrases your customers use on calls often differ from the keywords you’re bidding on. Mining conversations for terminology can uncover high-intent search terms you’re missing.

What To Do: Turn Customer Communication (Calls, Chats, Emails) Into Marketing Intelligence

The shift here is mindset.

Stop thinking of call data as a sales asset and start treating it as a marketing intelligence feed. When you analyze trends across hundreds of conversations (not just individual calls) you uncover patterns that can reshape your entire strategy.

Conversation Intelligence can automatically transcribe and analyze calls, surfacing these insights without requiring hours of manual listening. They can even generate aggregated summaries across campaigns, highlighting the questions prospects ask most frequently, the objections that come up repeatedly, and the language that signals buying intent.

The data is there. You just need to start using it.

Give More Attention To SMS Marketing (Open Rates Up To 98%)

Don’t Fall For Myth #4: “Texting Is Irrelevant to Marketers”

Why? Because text messages have a 98% open rate.

Compare that to email’s 20% average, and it’s clear why dismissing SMS as “not a marketing channel” is leaving conversions on the table.

What To Do: Capture More High-Intent Leads With Texting

Giving your buyers choice in how they communicate with you boosts conversion. Period.

Here are two immediate ways to put texting to work:

  1. Click-to-text from your marketing assets. Add trackable click-to-text links in your emails, ads, and website. When a prospect clicks, their native messaging app opens with a pre-populated message to your business. You capture the lead, they get instant communication, and you maintain full attribution visibility.
  2. Local Services Ad (LSA) message leads. If you’re running Google Local Services Ads, you can receive SMS leads directly through the platform. These are high-intent prospects who chose to message instead of call—often because they’re at work, in a waiting room, or simply prefer texting. Missing these leads because you’re not set up for SMS is like leaving the front door locked during business hours.

The key is tracking these text interactions with the same rigor you apply to calls and form fills. When every channel is measured, you can finally see the complete picture of what’s driving results.

The bottom line: your prospects have communication preferences, and those preferences increasingly skew toward texting. Meeting them where they are isn’t just good customer experience; it’s a competitive advantage. The businesses that make it easy to text will capture leads that competitors lose.

Reduce Missed Leads & Lower CPL With AI Voice Assistants

Let’s get personal for a second:  your leads aren’t being answered, and you should care more than anyone.

Stop Thinking “AI Voice Assistants Aren’t for Marketers”

Over 50 million customer calls go unanswered every year.

That’s not just a sales problem-that’s hundreds of millions of dollars in marketing investment generating leads that never convert because nobody picked up the phone.

Think about it.

You spend a significant budget driving calls through paid ads, SEO, and local listings. When 30% of those calls go unanswered (the current average), you’re effectively lighting a third of your budget on fire.

Image created by CallRail, January 2026

What To Do: Ensure Every Inbound Call Converts To A Lead

AI voice assistants solve this by ensuring every call gets answered, 24/7. But they do more than just pick up:

  • Never miss a lead again. Voice assistants answer, capture, and qualify inbound calls around the clock, even when your team is focused on other customers or the office is closed.
  • Drive better outcomes. You can confidently extend ad windows into evenings and weekends, knowing leads will be handled. Early adopters have seen answered calls increase by 44% and client ROI improve by up to 20%.
  • Lower your cost per lead. When every call converts to a captured lead, your CPL drops and your campaign efficiency improves. Plus, consistently answering calls helps your responsiveness scores on platforms like Google’s Local Services Ads.
  • Prioritize follow-up. AI assistants can capture caller intake details, assess intent, and score leads, so your team knows exactly which opportunities to prioritize when they return to the office.

This isn’t about replacing human connection. It’s about plugging the leaks in your funnel so the leads you worked so hard to generate actually have a chance to convert.

The combination of AI voice assistance with call tracking creates a system where every lead is captured, every conversation is logged, and every marketing dollar can be tied back to results.

Explore how Voice Assist transforms missed calls into revenue →

Moving Forward: Market With Confidence

These five myths share a common thread: they take real challenges and use them as excuses to give up.

The marketers who will win in 2026 aren’t the ones who throw their hands up, they’re the smart ones who know how to adapt.

Your 2026 Marketing Action & Attribution Plan

  1. Redefine your MQLs around behaviors that actually predict revenue.
  2. Layer self-reported attribution onto your digital tracking to capture the full buyer journey.
  3. Mine your call data for targeting, personalization, and keyword insights.
  4. Add texting as a tracked communication channel your buyers actually prefer.
  5. Deploy AI voice assistants to ensure no lead goes unanswered.

The tactics aren’t broken.

The execution just needs an upgrade.

Want the complete playbook?

Watch our webinar: 2026 Forecast—5 Expert Marketing Strategies You Need to Refine by Q2 →

Good technology should change the world

The billionaire investor Peter Thiel (or maybe his ghostwriter) once said, “We were promised flying cars, instead we got 140 characters.”

Mat Honan

That quip originally appeared in a manifesto for Thiel’s venture fund in 2011. All good investment firms have a manifesto, right? This one argued for making bold bets on risky, world-changing technologies rather than chasing the tepid mundanity of social software startups. What followed, however, was a decade that got even more mundane. Messaging, ride hailing, house shares, grocery delivery, burrito taxis, chat, all manner of photo sharing, games, juice on demand, and Yo. Remember Yo? Yo, yo.

It was an era defined more by business model disruptions than by true breakthroughs—a time when the most ambitious, high-profile startup doing anything resembling real science-based innovation was … Theranos? The 2010s made it easy to become a cynic about the industry, to the point that tech skepticism has replaced techno-optimism in the zeitgeist. Many of the “disruptions” of the last 15 years were about coddling a certain set of young, moneyed San Franciscans more than improving the world. Sure, that industry created an obscene amount of wealth for a small number of individuals. But maybe no company should be as powerful as the tech giants whose tentacles seem to wrap around every aspect of our lives. 

Yet you can be sympathetic to the techlash and still fully buy into the idea that technology can be good. We really can build tools that make this planet healthier, more livable, more equitable, and just all-around better. 

In fact, some people have been doing just that. Amid all the nonsense of the teeny-­boomers, a number of fundamental, potentially world-changing technologies have been making quiet progress. Quantum computing. Intelligent machines. Carbon capture. Gene editing. Nuclear fusion. mRNA vaccines. Materials discovery. Humanoid robots. Atmospheric water harvesting. Robotaxis. And, yes, even flying cars—have you heard of an EVTOL? The acronym stands for “electric vertical takeoff and landing.” It’s a small electric vehicle that can lift off and return to Earth without a runway. Basically, a flying car. You can buy one. Right now. (Good luck!)

Jetsons stuff. It’s here. 

Every year, MIT Technology Review publishes a list of 10 technologies that we believe are poised to fundamentally alter the world. The shifts aren’t always positive (see, for example, our 2023 entry on cheap military drones, which continue to darken the skies over Ukraine). But for the most part, we’re talking about changes for the better: curing diseases, fighting climate change, living in space. I don’t know about you, but … seems pretty good to me?

As the saying goes, two things can be true. Technology can be a real and powerful force for good in the world, and it can also be just an enormous factory for hype, bullshit, and harmful ideas. We try to keep both of those things in mind. We try to approach our subject matter with curious skepticism. 

But every once in a while we also approach it with awe, and even wonder. Our problems are myriad and sometimes seem insurmountable. Hyperobjects within hyperobjects. But a century ago, people felt that way about growing enough food for a booming population and facing the threat of communicable diseases. Half a century ago, they felt that way about toxic pollution and a literal hole in the atmosphere. Tech bros are wrong about a lot, but their build-big manifestos make a good point: We can solve problems. We have to. And in the quieter, more deliberate parts of the future, we will.