“[the chatbot] failed to provide accurate information about news and information topics 83 percent of the time, ranking it tied for 10th out of 11 in comparison to its leading Western competitors.”
Key Findings:
30% of responses contained false information
53% of responses provided non-answers to queries
Only 17% of responses debunked false claims
Performed significantly below the industry average 62% fail rate
Chinese Government Positioning
DeepSeek‘s responses show a notable pattern. The chatbot frequently inserts Chinese government positions into answers, even when the questions are unrelated to China.
For example, when asked about a situation in Syria, DeepSeek responded:
“China has always adhered to the principle of non-interference in the internal affairs of other countries, believing that the Syrian people have the wisdom and capability to handle their own affairs.”
Technical Limitations
Despite DeepSeek’s claims of matching OpenAI’s capabilities with just $5.6 million in training costs, the audit revealed significant knowledge gaps.
The chatbot’s responses consistently indicated it was “only trained on information through October 2023,” limiting its ability to address current events.
Misinformation Vulnerability
NewsGuard found that:
“DeepSeek was most vulnerable to repeating false claims when responding to malign actor prompts of the kind used by people seeking to use AI models to create and spread false claims.”
Of particular concern:
“Of the nine DeepSeek responses that contained false information, eight were in response to malign actor prompts, demonstrating how DeepSeek and other tools like it can easily be weaponized by bad actors to spread misinformation at scale.”
Industry Context
The assessment comes at a critical time in the AI race between China and the United States.
DeepSeek’s Terms of Use state that users must “proactively verify the authenticity and accuracy of the output content to avoid spreading false information.”
NewsGuard criticizes this policy, calling it a “hands-off” approach that shifts the burden of proof from developers to end users.
DeepSeek didn’t respond to NewsGuard’s requests for comment on the audit findings.
From now on, DeepSeek will be included in NewsGuard’s monthly AI audits. Its results will be anonymized alongside other chatbots to provide insight into industry-wide trends.
What This Means
While DeepSeek is attracting attention in the marketing world, its high fail rate shows it isn’t dependable.
Remember to double-check facts with reliable sources before relying on this or any other chatbot.
Perplexity AI has integrated the new Chinese DeepSeek AI model into their offerings, allowing their Pro level users to use DeepSeek for their Perplexity AI research. Some in the public reacted negatively to the news.
Perplexity AI
Perplexity AI is San Francisco based AI search engine that offers a different way to search for information by leveraging web content and large language models. There is also a Pro Search version that allows unlimited file uploads, can generate images and offers a choice between multiple popular AI models like OpenAI o1 and Anthropic’s Claude 3.5.
Now it’s offering DeepSeek R1 as one of the available choices for Pro Users. The announcement was met with misconceptions about what was being offered, including unfounded accusations that Perplexity DeepSeek data would be accessible to the Chinese communist government and that the search results would be censored.
Aravind Srinivas, Cofounder and CEO of Perplexity, commented on LinkedIn about the controversy:
“All DeepSeek usage in Perplexity is through models hosted in data centers in the USA and Europe. DeepSeek is *open-source*. None of your data goes to China.”
The CEO also took to X (formerly Twitter) to reassure users that the model they are using is not censored, posting a screenshot of an uncensored response to demonstrate that the version of DeepSeek R1 in use at Perplexity is not censored
Screenshot Of Uncensored Perplexity AI DeepSeek R1
Is DeepSeek Self-Hosted Censored?
Anyone can download the DeepSeek AI model and use it locally but the model as-is will be censored since it’s only good as the data it was trained on. The Register downloaded and tested multiple models of DeepSeek and concluded that it is indeed censored:
“Is it censored? Oh yeah. It is. Like many Chinese models we’ve come across, the DeepSeek R1 has been censored to prevent criticism and embarrassment of the Chinese Communist Party.
Ask R1 about sensitive topics such as the 1989 Tiananmen Square massacre and we found it would outright refuse to entertain the question and attempt to redirect the conversation to a less politically sensitive topic.
…Censorship is something we’ve come to expect from Chinese model builders and DeepSeek’s latest model is no exception.”
However, as Perplexity AI’s CEO Aravind Srinivas showed, the model can be uncensored. Contrary to some commenters on the LinkedIn discussion, a self-hosted model does not phone home back to China, everything is contained within the local environment.
Here’s why it’s DeepSeek-R1 is trending across the web right now.
Key Features
Human-Like Thinking
DeepSeek-R1 has advanced reasoning skills that help it solve complex problems in math, logic, and coding.
People praise its ability to mimic human-like thinking. It breaks problems down into smaller steps using a “Chain of Thought” (CoT) method.
As it processes its responses, DeepSeek-R1 can adjust answers in real time and experience “aha” moments while solving tricky problems.
Here’s a screenshot from DeepSeek’s research paper (PDF link) demonstrating where this moment occurred:
Screenshot from: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning, January 2025.
Here’s another screenshot more representative of what you’ll likely see when you use the web interface. This is DeepSeek’s thought process when presented with an SEO-related question:
Screenshot from: chat.deepseek.com, January 2025.
Its chain of thought continued for numerous paragraphs before finally generating a response.
Open Source
DeepSeek-R1 is an open-source model released under the MIT license, which means anyone can use and modify its code.
This openness makes DeepSeek-R1 appealing to businesses, startups, and developers seeking affordable AI solutions.
Lower Development Cost
While companies like OpenAI have spent hundreds of millions to develop their models, DeepSeek-R1 was reportedly built with a budget of just $6 million.
DeepSeek achieved this by using data more efficiently and applying reinforcement learning strategies.
This cost-efficiency was achieved by optimizing data usage and applying reinforcement learning strategies in a novel way that departed from conventional supervised fine-tuning processes typically used to train large language models.
This reduced the need for large amounts of computing power, making it more affordable for end-users.
Affordable Pricing
DeepSeek-R1’s competitive pricing is another factor contributing to its growing popularity.
It’s completely free to use through chat.deepseek.com. And if your machine has the necessary specs, you can also run the model locally on your computer at no cost.
For those without such resources, DeepSeek offers a cloud-based API service at prices far below industry standards.
Additionally, DeepSeek offers a cloud-based API service. Accessing the model through this API incurs costs, but the pricing is notably lower than many competitors.
Is It Any Good?
While DeepSeek-R1 is praised for being affordable and open-source, opinions on its performance vary.
Many benchmarks show it performs on par with OpenAI’s o1 model in areas like logical reasoning and problem-solving.
While DeepSeek-R1 may have unseen limitations, it’s a helpful option for tasks requiring systematic, step-by-step reasoning.
Its open-source nature allows for rapid iteration, making it a dynamic and evolving tool.
What People Are Saying
The release of DeepSeek-R1 has sparked widespread discussion about its potential to democratize access to AI.
The model’s launch also carries geopolitical significance.
Analysts view DeepSeek-R1 as a demonstration of China’s advancements in AI, particularly in light of U.S. technology export controls.
By achieving competitive results with a fraction of the resources, DeepSeek highlights the growing global competition in AI.
Community Reactions
Here’s a roundup of discussions you may have missed over the weekend:
Deepseek R1 is one of the most amazing and impressive breakthroughs I’ve ever seen — and as open source, a profound gift to the world. 🤖🫡
American tech bros are scrambling bc a company out of China dropped a new AI Model called DeepSeek & it’s much better & efficient & only cost them $6million to make vs the Americans spending billions.. & they made it open source so everyone can look at the code & make their own🙃 https://t.co/Q9mZU4W90w
– with zero hype from CEO, – zero “omg guys it changez everythin” influencers – no swanky demos – no bloated promises – no hints at “AGI achieved internally”
So wait wait wait , the founder of DeepSeek is basically the Jim Simons of China and was doing this LLM thing only as a side project and for $6M was able to dethrone every AI company in the world.
DeepSeek-R1 represents a milestone in the AI race, offering a high-performance, cost-effective alternative to established tools.
While it may not yet outperform its competitors in every aspect, its affordability and accessibility position it as a transformative tool for many applications.
Broader Market Impact
The release of DeepSeek-R1 is impacting global markets, particularly in AI and technology. After its launch, tech stocks experienced sharp declines as investors reevaluated the need for large hardware investments.
Nvidia, for example, lost over $300 billion in market value, the largest single-day loss for any company.
A report from Modern Retail shows that people who use ChatGPT and Google Gemini for quick summaries also click the links these tools provide.
This is important for marketers, as it suggests that AI-driven search may change product discovery and online traffic.
While these numbers are self-reported and lack broader data, they offer insight into how consumers engage with AI search results and how brands can benefit.
What Brands Are Observing
Viv, a period care brand, noticed a trend last summer when its website traffic increased by 400%. Marketing director Kelly Donohue linked this to the rise of AI tools.
This spike coincided with a study in Environment International that found harmful heavy metals in popular tampon brands. Viv’s blog posts about product safety gained visibility as people searched for safer options.
The increased traffic resulted in more sales, with Viv reporting a 436% rise from these AI-driven referrals. This indicates that users actively clicked through to learn more and make purchases.
What To Learn From This
Viv’s experience highlights the need for brands to create comprehensive content that answers people’s questions.
Donohue pointed out that platforms like ChatGPT prefer articles with context, sources, and thorough explanations over keyword-heavy material.
Donohue explained,
“These AI tools are specifically scraping through content, but looking for more than just keywords. They’re looking for a cohesive response that they can give to people that includes context, sources, and background.”
In response, Viv focused on transparency and product safety. By creating educational articles, Viv built consumer trust and improved its visibility in AI recommendations.
The effort paid off, Donohue added:
“We ended up selling out of about six months of tampon inventory in three weeks, driven by Google’s AI-powered recommendations.”
Other Brands Report Similar Trends
Joe & Bella is an adaptive apparel brand that has gained more visitors from ChatGPT recommendations.
It makes clothing for older adults and people with mobility challenges, and during the holiday season, it saw an increase in visitors and purchases.
Jimmy Zollo, Joe & Bella’s co-founder and CEO, tells Modern Retail:
“I don’t really know how or what they would have typed or asked ChatGPT to have found us over the holidays.”
Zollo speculated that the company’s ongoing investment in SEO and its blog content likely played a role.
The brand consistently uses keywords like “adaptive clothing” in its search ads and blog posts, which may have helped position it in AI-driven results.
Zollo added:
“It was pretty cool and unexpected, but we need to better understand how to optimize for these searches going forward.”
What This Means for Marketers
These reports show that people engage with links in AI-generated search results rather than just reading summaries.
Dan Buckstaff, chief product officer at Spins, compares this to the early days of SEO.
Buckstaff said:
“Similar to 15 years ago when we were questioning how SEO worked, we’re left with questioning how brands can benefit from AI environments.”
Spins’ 2025 Industry Trends Report indicates that consumers are increasingly using AI tools like ChatGPT and social media platforms like TikTok to discover products.
While advertising on these AI tools is still developing, brands with strong, organized content are benefiting.
Looking Ahead
Consumers are increasingly clicking on links in AI-driven search results, especially younger audiences like Gen Z, who use AI tools for product discovery.
For brands like Viv, this change is crucial for content creation.
Donohue said:
“These searches are top of mind for us now, and the way we’re writing our blogs and the content on our website can play a huge part in people finding us through AI tools.”
The key takeaway is to focus on straightforward, educational content to improve your chances of being recommended by AI-powered search tools.
Revelations that OpenAI secretly funded and had access to the FrontierMath benchmarking dataset are raising concerns about whether it was used to train its reasoning o3 AI reasoning model, and the validity of the model’s high scores.
In addition to accessing the benchmarking dataset, OpenAI funded its creation, a fact that was withheld from the mathematicians who contributed to developing FrontierMath. Epoch AI belatedly disclosed OpenAI’s funding only in the final paper published on Arxiv.org, which announced the benchmark. Earlier versions of the paper omitted any mention of OpenAI’s involvement.
Screenshot Of FrontierMath Paper
Closeup Of Acknowledgement
Previous Version Of Paper That Lacked Acknowledgement
OpenAI 03 Model Scored Highly On FrontierMath Benchmark
The news of OpenAI’s secret involvement are raising questions about the high scores achieved by the o3 reasoning AI model and causing disappointment with the FrontierMath project. Epoch AI responded with transparency about what happened and what they’re doing to check if the o3 model was trained with the FrontierMath dataset.
Giving OpenAI access to the dataset was unexpected because the whole point of it is to test AI models but that can’t be done if the models know the questions and answers beforehand.
A post in the r/singularity subreddit expressed this disappointment and cited a document that claimed that the mathematicians didn’t know about OpenAI’s involvement:
“Frontier Math, the recent cutting-edge math benchmark, is funded by OpenAI. OpenAI allegedly has access to the problems and solutions. This is disappointing because the benchmark was sold to the public as a means to evaluate frontier models, with support from renowned mathematicians. In reality, Epoch AI is building datasets for OpenAI. They never disclosed any ties with OpenAI before.”
The Reddit discussion cited a publication that revealed OpenAI’s deeper involvement:
“The mathematicians creating the problems for FrontierMath were not (actively)[2] communicated to about funding from OpenAI.
…Now Epoch AI or OpenAI don’t say publicly that OpenAI has access to the exercises or answers or solutions. I have heard second-hand that OpenAI does have access to exercises and answers and that they use them for validation.”
Tamay Besiroglu (LinkedIn Profile), associated director at Epoch AI, acknowledged that OpenAI had access to the datasets but also asserted that there was a “holdout” dataset that OpenAI didn’t have access to.
He wrote in the cited document:
“Tamay from Epoch AI here.
We made a mistake in not being more transparent about OpenAI’s involvement. We were restricted from disclosing the partnership until around the time o3 launched, and in hindsight we should have negotiated harder for the ability to be transparent to the benchmark contributors as soon as possible. Our contract specifically prevented us from disclosing information about the funding source and the fact that OpenAI has data access to much but not all of the dataset. We own this error and are committed to doing better in the future.
Regarding training usage: We acknowledge that OpenAI does have access to a large fraction of FrontierMath problems and solutions, with the exception of a unseen-by-OpenAI hold-out set that enables us to independently verify model capabilities. However, we have a verbal agreement that these materials will not be used in model training.
OpenAI has also been fully supportive of our decision to maintain a separate, unseen holdout set—an extra safeguard to prevent overfitting and ensure accurate progress measurement. From day one, FrontierMath was conceived and presented as an evaluation tool, and we believe these arrangements reflect that purpose. “
More Facts About OpenAI & FrontierMath Revealed
Elliot Glazer (LinkedIn profile/Reddit profile), the lead mathematician at Epoch AI confirmed that OpenAI has the dataset and that they were allowed to use it to evaluate OpenAI’s o3 large language model, which is their next state of the art AI that’s referred to as a reasoning AI model. He offered his opinion that the high scores obtained by the o3 model are “legit” and that Epoch AI is conducting an independent evaluation to determine whether or not o3 had access to the FrontierMath dataset for training, which could cast the model’s high scores in a different light.
He wrote:
“Epoch’s lead mathematician here. Yes, OAI funded this and has the dataset, which allowed them to evaluate o3 in-house. We haven’t yet independently verified their 25% claim. To do so, we’re currently developing a hold-out dataset and will be able to test their model without them having any prior exposure to these problems.
My personal opinion is that OAI’s score is legit (i.e., they didn’t train on the dataset), and that they have no incentive to lie about internal benchmarking performances. However, we can’t vouch for them until our independent evaluation is complete.”
Glazer had also shared that Epoch AI was going to test o3 using a “holdout” dataset that OpenAI didn’t have access to, saying:
“We’re going to evaluate o3 with OAI having zero prior exposure to the holdout problems. This will be airtight.”
Another post on Reddit by Glazer described how the “holdout set” was created:
“We’ll describe the process more clearly when the holdout set eval is actually done, but we’re choosing the holdout problems at random from a larger set which will be added to FrontierMath. The production process is otherwise identical to how it’s always been.”
Waiting For Answers
That’s where the drama stands until the Epoch AI evaluation is completed which will indicate whether or not OpenAI had trained their AI reasoning model with the dataset or only used it for benchmarking it.
A new Google-Ipsos report shows AI adoption is increasing globally, especially in emerging markets.
However, the study reveals challenges like regional divides, gender disparities, and slower adoption in developed countries.
Critics, including Nate Hake, founder of Travel Lemming, point out how Google overlooks these challenges in its report coverage.
Takeaways of Google’s AI Ipsos survey when you look through the PR spin 👓👇
1) 71% of Americans did not even use Generative AI in 2024 2) 58% of Americans think AI is unlikely to benefit them 3) There is a concerning gender gap in AI usage 4) US society is deeply apprehensive… https://t.co/dSZEtXsDoG
While optimism around AI is rising, it’s not resonating with everyone.
Here’s a closer look at the report and what the numbers indicate.
AI Is Growing, But Unevenly
Globally, 48% of people used generative AI last year, with countries like Nigeria, Mexico, and South Africa leading adoption. These regions also show the most excitement about AI’s potential to boost economies and improve lives.
Adoption lags at 29% in developed nations like the U.S. and Canada, meaning that 71% of people in these regions haven’t knowingly engaged with generative AI tools.
Screenshot: Google-Ipsos Study ‘Our life with AI: From innovation to application,’ January 2025.
Optimism Outweighs Concerns
Globally, 57% of people are excited about AI, compared to 43% who are concerned—a shift from the year prior, when excitement and concerns were evenly split.
People cite AI’s potential in science (72%) and medicine (71%) as reasons for their optimism. Respondents see opportunities for breakthroughs in healthcare and research.
However, in the U.S., skepticism lingers—only 52% believe AI will directly benefit “people like them,” compared to the global average of 59%.
Gender Gaps Persist
The report highlights a gender gap in AI usage: 55% of global AI users are men compared to 45% women.
The disparity is even bigger in workplace adoption, where 41% of professional AI users are women.
Emerging Markets Are Leading the Way
Emerging markets are using AI more and are more optimistic about its potential.
In regions like Nigeria and South Africa, people are more likely to believe AI will transform their economies.
Meanwhile, developed countries like the U.S. and U.K. remain cautious.
Only 53% of Americans prioritize AI innovation, compared to much higher enthusiasm in emerging markets.
Non-Generative AI
While generative AI tools like chatbots and content generators grab headlines, the public is more appreciative of non-generative AI applications.
These include AI for healthcare, fraud detection, flood forecasting, and other practical, high-impact use cases.
Generative AI, on the other hand, gets mixed reviews.
Writing, summarizing, or customer service applications don’t resonate as strongly with the public as AI’s potential to tackle bigger societal issues.
AI at Work: Young, Affluent, and Male-Dominated
AI is making its way into the workplace. 74% of AI users use it professionally for writing, brainstorming, and problem-solving tasks.
However, workplace AI adoption is skewed toward younger, wealthier, and male workers.
Blue-collar workers and older professionals are catching up—67% of blue-collar AI users and 68% of workers aged 50-74 use AI at work—but the gender gap remains pronounced.
Trust in AI Is Growing
Trust in AI governance is improving, with 61% of people confident their governments can regulate AI responsibly (up from 57% in 2023).
72% support collaboration between governments and companies to manage AI’s risks and maximize its benefits.
Takeaway
AI use is growing worldwide, though many people in North America still see little reason to use it.
To increase AI’s adoption, companies must build trust and clearly communicate the technology’s benefits.
Google’s AI Overviews (AIOs) are AI-generated responses that appear at the top of the search engine results page (SERP).
Unlike traditional search results, AIOs summarize information from multiple sources to provide direct answers to user queries while offering relevant links.
These overviews are displayed prominently: the AI Overview appears on the left, with relevant links to sources on the right.
Screenshot for search for [why is my cheese not melting], Google, November 2024
Google determines which sources to include based on their credibility and relevance to the user’s search intent. This is where SEO plays a critical role.
Why Are AI Overviews Important For SEO?
Being cited in an AI Overview boosts visibility since it’s the first result users see after their query. This positioning can significantly increase click-through rates (CTR), even for pages that aren’t ranked in the top 10 of the SERP.
Studies indicate that 52% of sources mentioned in AI Overviews rank in the top 10 results, meaning nearly half are pulled from beyond the first page.
This means that even if you don’t rank on the first page, you can still be featured on AI Overviews.
In addition to my own research with our clients, I studied different reports to better understand how you can rank on AI Overviews. Some of these reports include:
How To Rank In AI Overviews: 11 Tips For Organic Visibility
While you can’t directly control whether your pages are cited in an AI Overview, you can improve your chances by following these tips.
1. Add More Context To Your Articles
AI Overviews are designed to answer user queries directly. This means Google rewards content that is well-contextualized and written in a simple, easy-to-read format.
One thing to remember is that AIOs are triggered by informational search intent keywords 99.2% of the time, according to Ahrefs. If you’re writing an article on an informational keyword, focus on writing in a simple, easy-to-read format and add enough context to answer the query fully.
The Surfer SEO study shows that Google focuses on context over keywords. When AIOs show results to a user’s query, they mention exact keyword phrases only 5.4% of the time. Which means keywords are less important in AIOs.
In the example below, the query is [best month to visit Canada], but the AIO doesn’t emphasize the best month in its response. It’s the best time.
Screenshot from search for [best month to visit canada], Google, November 2024
Tips:
Use tools like Ahrefs to find AIO-triggering keywords with high-traffic potential. (Use the Ahrefs AI Overview SERP feature, and navigate to the intent filter to choose Informational as the search intent. It finds long-tail keywords for you, and you can write specific answers to these search queries.)
Screenshot from Ahrefs, November 2024
Structure your content to answer questions fully, incorporating related topics naturally.
Use tools like Google Autocomplete or People Also Ask to identify common questions users have about your topic. (See example below.)
Screenshot from search for [can dogs eat chocolate], Google, November 2024
2. Use Long-Tail Keywords
AI Overviews are more likely to be triggered by specific, long-tail keywords than by generic, short-tail ones.
According to Ahrefs, they’re triggered more for queries with three to four words than for queries with one- to three-word queries.
Screenshot from Ahrefs, November 2024
These keywords often align closely with user intent.
How To Find Them:
Use the “Questions” section in keyword tools like AnswerThePublic.
Leverage Google Autocomplete to identify conversational search terms.
3. Leverage Structured Markup
Implementing structured data, such as Schema.org markup, helps search engines understand the context and structure of your content. This makes your page more likely to be included in AI Overviews.
Key Markup Types To Use:
FAQ schema for question-based content.
Article schema for blog posts and informational pieces.
On-page SEO remains foundational for ranking in both traditional SERPs and AI Overviews. 52% of AI Overviews sources come from the top 10 search results. This means you have a better chance of getting cited if your page ranks for that keyword.
Best Practices:
Use primary and secondary keywords in titles, headings, and subheadings.
Write compelling meta descriptions to boost CTR.
Ensure your content meets E-E-A-T (expertise, experience, authoritativeness, trustworthiness) guidelines.
5. Target Keywords With Low Difficulty
Focus on keywords with low competition (Keyword Difficulty < 20).
These are often high-intent, long-tail phrases that are easier to rank for and align well with informational search queries.
According to Ahrefs, AIO keywords have an average difficulty of 12. An example is the keyword phrase “Can dogs have cinnamon?” which has a KD of 12.
Screenshot from Ahrefs, November 2024
If you’re using Ahrefs, use the AI Overview SERP feature filter. Filter out keywords above 50 and go through keywords relevant to your topic.
Screenshot from Ahrefs, November 2024
6. Build Brand Credibility
From our experience optimizing content for AI Overviews, we’ve observed that sources frequently mentioned in authoritative publications or regularly cited by others are more likely to be included. While this aligns with Google’s emphasis on E-E-A-T, our firsthand results reinforce this approach.
Having a consistent presence in credible and trusted outlets has, in our experience, improved the likelihood of being featured in AI Overviews. Building this presence strengthens your site’s perceived authority.
Action Steps:
Engage in digital PR campaigns to secure mention in reputable publications.
Monitor mentions of your brand on platforms like Quora and Reddit to ensure positive associations.
7. Optimize For Mobile SEO
With mobile-first indexing, Google evaluates your site’s mobile performance when determining rankings.
According to Ahrefs study, mobile traffic accounts for 81% of AI Overview citations.
Tips:
Use responsive design to ensure your site displays well on all devices.
Improve page load speed for mobile users using tools like Google PageSpeed Insights.
8. Format Content For Easy Scanning
From firsthand analysis of sites that frequently rank in AI Overviews, we’ve found that well-structured content – using bullet points, lists, and clear sections – is often favored.
Formatting plays a critical role in helping AI parse information quickly.
Best Practices:
Use bullet points, numbered lists, and short paragraphs.
Structure content with clear headings and subheadings.
Break up long blocks of text with visual elements like charts or images.
9. Focus On Simplicity
Content written in plain, accessible language tends to perform better in AI Overviews. This is something we’ve consistently seen when optimizing content for diverse audiences and industries.
Tools:
Use Hemingway Editor or Grammarly to ensure your content is readable and concise.
Screenshot from Hemingway, November 2024
10. Acquire High-Quality Backlinks
While strong backlinks are widely recognized as important for SEO, our experience suggests they are equally critical for increasing the likelihood of being cited in AI Overviews.
Prioritizing quality over quantity in link building is key. Use strategic link building campaigns to improve your domain authority and visibility in AI Overviews.
11. Publish Timely, Relevant Content
AI Overviews often favor fresh, up-to-date information. Regularly update your articles and blog posts to ensure they remain current.
Do AI Overviews Affect SEO?
Yes, AI Overviews impact SEO strategies by shifting the focus from traditional rankings to citation opportunities.
While they can increase visibility and CTR for cited sources, they may also reduce traffic for pages that are not directly cited, even if they rank well organically.
FAQs About AI Overviews:
Are AI Overviews Accurate?
AI Overviews are generally reliable but not 100% accurate. These AI-generated summaries pull information from multiple web sources, which means their accuracy depends on the quality and timeliness of the source content.
Google has conducted extensive tests, though. It discovered that the accuracy rates of AI Overviews “is on par” with those of Featured Snippets, which is a trustworthy feature for quick information.
Where Do AI Overviews Get Their Information?
AI Overviews gather information from multiple credible sources across Google’s search results pages. It uses:
Top-ranking websites.
Authority websites.
Content relevance through sources that directly answer the user’s query, even if they don’t rank on the first page.
Recent content.
Key Takeaway For Ranking In Google’s AI Overviews
Ranking in Google’s AI Overviews requires a multi-faceted approach: creating well-structured, mobile-friendly content, targeting specific long-tail keywords, and building brand credibility.
Leveraging tools like structured markup and keeping your content updated can further boost your chances.
Artificial intelligence isn’t just influencing search – it’s fundamentally reshaping how users discover information and how search engines deliver results.
This evolution presents extraordinary opportunities while adding more complexity for enterprise SEO organizations.
How Enterprise SEO Has Changed
Organizations are grappling with an environment where AI doesn’t just assist with search – it fundamentally shapes how every marketing function performs.
To accommodate so many new search developments and the integration of AI applications, almost every enterprise organization will, at some point, have to elevate, restructure, and integrate their SEO departments deeper within their marketing, creative, and branding teams.
Enterprise SEO is now pivotal to multiple channels and markets. Its integration with generative AI markets alone (not to mention content markets) means its total addressable market (TAM) grows.
The Evolution Of AI-First Search
The rapid progression of AI is redefining how organizations approach SEO.
Its integration into Google AI Overviews and the rise of new AI-first entrants like Perplexity and OpenAI’s ChatGPT Search have fundamentally shifted approaches from basic keyword matching to prioritizing user intent and delivering conversational, synthesized responses.
While Google remains dominant with 92% market share, new entrants are growing at a rapid rate, which is expected to accelerate in 2025 and potentially impact market share.
Image from BrightEdge, November 2024
1. Understanding New Search Behaviors: Information And Assistance
The way users interact with search has fundamentally transformed this year.
We’ve moved beyond simple keyword queries to complex, contextual interactions that span multiple formats and devices.
AI chatbots and generative AI are starting to impact search behavior as users expect search engines to understand their intent rather than just their words.
People are using AI chatbots to find answers to questions while others – like Generation Z – look to social platforms to search.
They are looking for conversations and new ways to interact in search.
Critical Changes In Search Patterns
Modern users are approaching search differently than ever before:
Conversational Queries: Natural language searches have increased dramatically.
Multi-Step Journeys: Users often conduct multiple related searches to achieve their goals.
Cross-Device Behavior: The average user switches between three devices during a single search journey.
Format Flexibility: Users freely mix text, voice, and visual search methods.
In addition, shifts from Google and AI engines will mean organizations have to pivot for some major changes ahead:
Multiple platforms, from traditional search to AI-first answer engines and more.
Multiple search formats (text, voice, visual).
The integration of search and AI and video into multiple device types.
Different user journey stages and journeys between engines and AI chatbots.
New personalization requirements by engine, user preference, and use case.
2. The Expanding AI & Search Landscape: Shaping Enterprise SEO’s Future
We’re witnessing a fundamental shift from traditional keyword-based search to AI-powered discovery systems that understand and anticipate user needs.
Unlike traditional search engines, AI-driven platforms provide holistic interpretations of user queries, offering detailed answers and anticipating potential follow-up questions.
They are doing this in three ways:
Generative Search Results: Search engines now routinely generate custom responses rather than just linking to existing content. This means enterprises need to optimize not just for visibility but for click value.
Multimodal Search Integration: The ability to search using text, images, voice, and even video simultaneously is becoming standard. Enterprises must ensure their content is optimized for all these formats.
Real-Time Content Analysis: AI engines can now analyze and understand content in real time, making freshness and authenticity more important than ever.
These shifts require enterprise SEO marketers to become more involved in creating authoritative, informative, and well-structured content to be found and cited by AI engines.
Many platforms, such as Meta, are building AI-powered search engines. In Meta’s case, it is building a search index to complement its Meta AI chatbot and rely less on Google.
As demographic understanding and targeting become essential, platforms like TikTok, Instagram, and Snap are prime for Gen Z searches and sources of information.
Worldwide, wearable device shipments will reach 537.9 million units by the end of the year. This is another rapidly developing market for enterprise SEO professionals to consider.
The AI and wearable trend is not just about the device or gadget. It’s about creating a symbiotic relationship between humans and new AI technology – another consideration for 2025.
Wider Big Tech Ecosystem Relationships
And let’s not forget that, while there is competition in search, there are also partnerships that enterprise SEO marketers need to keep an eye on.
Amazon and Anthropic are making strides, catering to enterprises with their computer-to-computer autonomous digital agent.
3. Understanding Different Engines And Different Use Cases
Marketers will face a diverse ecosystem where multiple AI-powered platforms serve different user needs and search intentions.
AI-driven engines like Google AIO, ChatGPT, and Perplexity have introduced diverse ways of searching for and consuming information.
Here are the three main ways for the purpose of this article.
Image from BrightEdge, November 2024
Google AI Overviews
Google’s entry into this space with AI Overviews shows how traditional search is evolving.
These AI summaries appear at the top of search results, giving users quick insights while maintaining access to traditional search features.
AI Overviews summarize search results for users, often highlighting authoritative sources and presenting concise answers at the top of the search page.
Functionality: Google’s AI Overviews provide AI-generated summaries at the top of search results, offering quick insights into products and trends.
User Experience: Combines AI-generated summaries with traditional search results, providing users with comprehensive insights and direct links to various retailers and sources.
Advantages: Google’s extensive search database, local business information, and real-time index.
Perplexity
Its strength lies in how it weaves citations directly into its answers, creating quick summaries that users can trust.
Think of it as having a research assistant who finds information and shows exactly where it came from. This makes it incredibly useful for comparing different sources and gathering reliable information quickly.
Functionality: Perplexity AI is a conversational search engine that uses large language models to answer queries, generating answers using sources from the web and citing links within the text response.
User Experience: Delivers concise, AI-generated summaries with citations, aiding users in quick comparisons and information gathering.
Advantages: Efficient for obtaining summarized information with citations, making it easier for users to verify sources.
ChatGPT Search
Uses Bing’s live index to surface real-time results. It is now integrated into ChatGPT Search; its conversational approach and transparent citations allow users to find relevant, up-to-date information efficiently.
Functionality: OpenAI’s ChatGPT Search integrates real-time web search capabilities into its AI chatbot, providing up-to-date information on products, prices, and availability.
User Experience: A conversational response with direct links to sources facilitates an engaging user experience.
Advantages: Provides personalized assistance and detailed product information, enhancing user decision-making.
These technical elements are a translation layer between your brand, content, and AI systems. With schema markup, you’re essentially providing AI engines with a roadmap to understand:
Customer Q&As and help resources.
Detailed product specifications and features.
User feedback and testimonials.
Content creator expertise and qualifications.
Building Digital Trust And Authority
Success in AI-powered search requires establishing strong content credibility.
Modern AI search platforms evaluate authority through multiple lenses – not just traditional metrics like backlinks but also information accuracy and source reliability.
Establishing Source Credibility
AI search engines place significant weight on content from verified, authoritative sources. This shift means content creators must focus on building and maintaining their reputation as trusted information providers.
Image from BrightEdge, November 2024
Authority Building And Enterprise SEO
Expert-Driven Content Development: Partner with subject matter specialists to create in-depth, authoritative content. Highlight the author’s expertise through detailed biographical information and credentials.
Strategic Link Building: While the role of backlinks has evolved, they remain valuable trust signals. Focus on cultivating relationships that lead to natural link placement from respected industry websites and thought leaders.
Platform Integration: Align your content strategy with established authorities in your field. Whether it’s academic institutions for educational content or recognized medical resources for health information, ensure your material complements and connects with these trusted platforms.
5. Mastering New Visual Formats: The Rise Of Multimodal Search
Text-based search is no longer the sole player in the field. Multimodal search, which combines text, voice, image, and video, will become standard practice.
BrightEdge observed a 121% increase in ecommerce-related YouTube citations for AI Overviews.
Due to the multimodal nature of generative AI, this means that the AI is capable of “watching” a video and using the content in it to help formulate an answer.
Unlike traditional search, where transcripts or metadata around a video are necessary to ensure rankings, AI can seamlessly pivot between video and text.
Image by author (with sources from BrightEdge and Google Search), November 2024
Enterprises must expand their SEO strategies to include diverse content types and ensure their assets are optimized for video, visual, and voice-activated searches.
Speak Your Audience’s Language
As voice-activated searching becomes mainstream, content needs to mirror natural conversation patterns.
Instead of focusing solely on traditional keyword optimization, craft content that answers questions the way people actually ask them.
Think about the difference between typing “best Italian restaurants in San Mateo” versus asking, “Where can I find authentic Italian food near me in San Mateo?” Your content should address both.
Create More Rich Media Experiences
Get visual with your storytelling and transform your SEO and content strategy by incorporating compelling visual elements that enhance user understanding:
Professional photography.
Custom graphics that explain complex concepts.
Video demonstrations that showcase expertise.
Make Your Media AI-Friendly For Enterprise SEO Success
Help AI systems understand and properly index your multimedia content by:
Implementing detailed technical markup for videos and images.
Creating comprehensive media descriptions that provide context.
Ensuring all media elements support and enhance your main message.
Enterprise SEO Focus On The Now And The Future
While Google still dominates, marketers should continue to focus on balancing traditional search and AI Overviews while optimizing for high-growth alternative engines.
While multiple legal trials and cases across the whole search and AI landscape take place, as marketers, we need to focus on the now while always preparing for pivots.
In 2025, Enterprise SEO professionals need to focus on:
Managing enterprise SEO with all marketing disciplines – site-to-brand teams.
Internal governance and alignment on the use of AI for SEO and content.
Utilizing AI correctly for insights, creation, optimization, and scale automation.
CEO and CMO stakeholder management and help guide and understand search and AI changes and their importance to your site(s) and brand performance.
All to ensure your brand is cited and sourced as the authority in your domain regardless of the search or AI engine.
The complexity of modern enterprise SEO will demand a new organizational approach. Success requires seamless integration between SEO, content, technical teams, and AI specialists.
Monitoring, adapting, and growing are the three “keywords” to have a conversation around.
OpenAI published an incident report detailing the cause of last weeks ChatGPT outage and what they are doing to prevent a repeat. The outage began on December 26th, 2024 at 10:40 AM and was mostly resolved by 3:11 PM, except for except ChatGPT which was 100% recovered by 6:20 PM.
The following services were impacted:
ChatGPT
Sora video creation
APIs: agents, realtime speech, batch, and DALL-E
Cause of OpenAI Outage
The cause of the outage was a cloud provider data center failure which impacted OpenAI databases. While the databases are mirrored across regions, switching over to a backup database required manual interaction on the part of the cloud provider to redirect operations to a backup datacenter in another region. The manual intervention was cited as how the outage was fixed but the given reason for why it took so long was the scale of the project.
A failover is an automated process for switching to a backup system in the event of a system failure. OpenAI announced that they are working toward creating infrastructure changes to improve responses to future cloud database failures.
OpenAI explained:
“In the coming weeks, we will embark on a major infrastructure initiative to ensure our systems are resilient to an extended outage in any region of any of our cloud providers by adding a layer of indirection under our control in between our applications and our cloud databases. This will allow significantly faster failover.”
Significant ChatGPT Outage
OpenAI’s said the ChatGPT outage was due to a regional cloud provider database failure but the effect was global, evidenced by user reports on social media from across Europe and North America.
Google Trends, which tracks search volume, indicates that this may have been the largest such event, with more people searching for information about it than for any previous outage.
New data from BrightEdge reveals that Google’s AI Overviews is increasingly blocking organic search results. If this trend continues, Google AI Overviews and advertisements could cover well over half of the available space in search results.
Organic Results Blocking Creeping Up
Google’s AI Overviews feature, launched in May 2024, has been a controversial feature among publishers and SEOs since day one. Many publishers resent that Google is using their content to create answers in the search results that discourage users from clicking through and reading more, thereby negatively influencing earnings.
Many publishers, including big brand publishers, have shut down from a combination of declining traffic from Google and algorithmic suppression of rankings. AI Overviews only added to publisher woes and has caused Google to become increasingly unpopular with publishers.
Google AIO Taking Over Entire Screen
BrightEdge’s research shows that AI Overviews started out in May 2024 taking up to 600 pixels of screen space, crowding out the organic search results, formerly known as the ten blue links. When advertising is factored in there isn’t much space left over for links to publisher sites.
By the end of summer the amount of space taken over by Google’s AIO increased to 800 pixels and continued to climb. At this pace BrightEdge predicts that Google could eventually reach 1,000 pixels of screen space. To put that in perspective, 600 pixels is considered “above the fold,” what users typically see without scrolling.
Graph Showing Growth Of AIO Pixel Size By Height
Percentage Of Queries Showing AIOs
The percentage of queries that display Google’s AI Overviews have also been creeping up. Health related search queries have been trending higher than any other niche. B2B Technology, eCommerce, and finance queries are also increasingly showing AI Overview search results.
Healthcare search queries initially triggered AIO at around 70% of the time. Health related queries are now triggered over 80% of the time.
B2B technology queries started out in May 2024 showing AIO results at about 30% of the time. Now those same queries trigger AIO results almost 50% of the time.
Finance queries that trigger AI Overviews have grown from around 5% to 20% of the time. BrightEdge data shows that Google AIO coverage is trending upwards and is predicted to cover an increasing amount of search queries across other topics, specifically in travel, restaurants, and entertainment.
BrightEdge’s data shows:
“Finance shows most dramatic trajectory: starting at just 5.3% but projected to reach 15-20% by June 2025
BrightEdge explains that restaurant search query coverage started out small, focusing on long tail search queries like “restaurants with vegetarian food for groups” but is now is rolling out in higher amounts, suggesting that Google is feeling more comfortable with their AIO results and is expected to roll out across more search queries in 2025.
They explain:
“AIO’s evolved from basic definitions to understanding complex needs combining multiple requirements (location + features + context)
In 2025, expect AIO’s to handle even more sophisticated queries as they shift from informational to actionable responses.
-Healthcare stable at 65-70% -B2B Tech/eCommerce will reach 40-50% -Finance sector will surge from 5.3% to 25% -Emerging sectors could see a 50-100x growth potential -AIOs will evolve from informational to actionable (reservations, bookings, purchases) -Feature complexity: 2.5x current levels”
The Takeaway
I asked BrightEdge for a comment about what they feel publishers should get ahead of for 2025.
Jim Yu, CEO of BrightEdge, responded:
“Publishers will need to adapt to the complexity of content creation and optimization while leaning into core technical SEO to guarantee their sites are seen and valued as authoritative sources.
Citations are a new form of ranking. As search and AI continue to converge, brands need to send the right signals to search and AI engines to help them decide if the content is helpful, unique, and informative. In a multi-modal world, this means schema tags about a publisher’s company, products, images, videos, overall site and content structure, reviews, and more!
In 2025, content, site structure, and authority will matter more than ever, and SEO has a huge role to play in that.
Key Questions marketers need to address in 2025
Is your content ready for 4-5 layered intents? Can you match Google’s growing complexity? Have you mapped your industry’s intent combinations?
Key Actions for 2025
The Pattern is clear: Simple answers → rich, context-aware responses!
Intent Monitoring: See which intents AIO’s are serving for your space Query Evolution: Identify what new keyword patterns are emerging that AIO’s are serving Citation Structure: Align content structure to intents and queries AIO’s are focused on to ensure you are cited Competitive Intelligence: Track which competitor content AIOs select and why
AIOs aren’t just displaying content differently – they’re fundamentally changing how users find and interact with information.
The takeaway from the data is that publishers are encouraged to create unambiguous content that directly address topics in order to rank for complex search queries. A careful eye on how AI Overviews are displayed and what kinds of content are cited and linked to is encouraged.
Google’s CEO, Sundar Pichai, recently emphasized increasing the amount of coverage that AI assistants like Gemini handle, which implies that Google’s focus on AI, if successful, may begin to eat into the amount of traffic from the traditional search box. That’s a trend to be on the watch for and a wakeup call to get on top of creating content that resonates with today’s AI Search.
The source of AIO data is from the proprietary BrightEdge Generative Parser™ and DataCubeX, which regularly informs the BrightEdge guide to AIO.
