Ally Bank and the Project Management Institute have become two of the first brands to buy an ad meant to be read by a machine, not a person. Time began serving ads to AI agents this month, formatting them as sponsored FAQs stuffed with brand messaging and dropping them into stripped-down copies of its pages, according to Digiday.

The move follows Time’s decision last month to convert all its webpages into markdown, text-only versions that strip out design and images, making them easier for AI systems to crawl and process. The publisher’s bet is that greater accessibility will boost its visibility. By placing ads within those markdown files, Time also hopes to monetize the growing volume of AI bot traffic while that strategy plays out.

To build the ads, Time is working with an AI ad tech platform called Mobian, which converts the pages and generates the agent ads from a brand brief. The output gets turned into a PDF for humans to approve, much like a standard branded content deal. Mobian then feeds the same FAQ questions to AI search engines and tracks visibility, favorability and accuracy over time.

Mobian co-founder and CEO Jonah Goodhart said the shift reflects a growing reality: publishers and brands increasingly need to optimize for AI systems as much as human audiences.

“Maybe it’s more important to influence the agent than even the human, because with a human you influence one person. When you influence ChatGPT, you’re influencing potentially all of ChatGPT,” he told Digiday.

Goodhart said roughly 15% of brands now run their own markdown pages for AI crawlers, a figure he expects to grow as companies adapt to what he describes as a two-track internet.

Time COO Mark Howard declined to disclose traffic figures but pointed to TollBit data showing the publisher receives more AI crawler requests than most of the roughly 7,000 sites in the company’s network. During major events such as the Time100 franchise, bot activity surges so dramatically that AI crawlers outnumber human visitors on most days. The trend mirrors Cloudflare’s finding that automated bots now account for more than half of all web traffic.

Time is positioning those AI visits as a new source of advertising revenue, selling one
“agent ad” per markdown page. The ads are part of a broader generative engine optimization offering that reflects publishers’ growing focus on AI discovery over traditional search traffic.

The approach comes with uncertainty. No major AI company has explained how its models handle ads embedded in markdown files—or whether they recognize them as ads at all. Rob Derow, a managing director at BCG X, told Digiday the lack of standards is the biggest risk. If AI companies ultimately treat the practice like cloaking—showing crawlers content different from what humans see—the pages could be devalued, much as Google penalized similar SEO tactics.

To reduce that risk, Time labels each placement as sponsored content and identifies the advertiser, despite no current requirement to do so. “We don’t know yet because this is brand new, and we believe that we are paving the first path forward here,” COO Mark Howard told Digiday.

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UK publisher digital revenue fell 4.55% in the first quarter of 2026, ending four straight quarters of growth, according to the Digital Publishers’ Revenue Index run by the Association of Online Publishers and Deloitte.

The survey, reported by Press Gazette, covered 13 publishers, nine business-to-consumer and four business-to-business. Richard Reeves, managing director at the AOP, called the drop the “first tremors in an earthquake being felt across the industry” as AI-generated answers and shifting audience habits keep readers from clicking through to source sites.

The decline was uneven. Some 62% of respondents still reported revenue growth, the highest share in a year, which the AOP said points to the heaviest losses being concentrated among a minority of publishers most exposed to changes in the information ecosystem.

The numbers that fell fell hard. Recruitment classified revenue dropped 44.84%, other classified was down 38.17% and off-platform revenue fell 20.27%. The AOP attributed much of that to people getting what they need from AI answers without visiting a publisher. Digital audio revenue sank 46.98% year on year for the second quarter running.

The click-through data backs up the concern. Separate AOP research found only 26% of ChatGPT users say they would click at least one media link in a response, rising to 34% for a Google Search carrying an AI Overview. Users are 18% less likely to click through to a source when an AI Overview sits at the top.

The “miscellaneous” category, covering revenue that doesn’t fit the main buckets, posted the single biggest decline. The AOP suggested AI substitution of publisher content across referral channels was a factor. It also flagged agencies Dentsu and WPP pulling out of The Trade Desk’s OpenPath initiative over concerns about ad placement and hidden fees.

Not everything went down. Digital display advertising rose 5.06%, likely on the back of more direct-sold premium deals. Every respondent now ranks advertising a high business priority, up from 75% a year earlier. Online video grew 1.29%, sponsorship 0.91% and subscriptions a thin 0.63%.

Reeves said the display turnaround “must be commended and demonstrates the quality of the advertising product that premium publishers provide.” Andy Cowen, lead partner for telecoms, media and entertainment at Deloitte, said the display growth shows the value premium content still holds but warned the drops elsewhere point to an “urgent need for publishers to adapt.”

For newsrooms, the report reads as a warning about cost. Every publisher in the index now says it will prioritise cost reductions, up from 50% a year ago, and every one says acquisitions are a priority, up from 25%. That mirrors wider pressure across the sector, where journalism’s workforce is shrinking as AI and new consumer habits reshape the industry.

There is one thread publishers can pull on. AOP research found a reader’s trust in an AI answer depends on their perception of the news brand cited in it, which underlines how much AI companies still rely on verified publisher content even as they starve those publishers of clicks. Whether that dependency translates into deals or dollars is the next thing the revenue index will measure.

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Reuters treats AI as a research assistant that must show its work. The BBC requires a human sign-off before any AI-assisted story runs. The Guardian will only let staff use it once a senior editor has approved the specific task. Three of journalism’s most prominent outlets, three distinct answers to the same question — and together they show there is no single blueprint for the AI-powered newsroom.

A new comparative study published by Nieman Lab examined how Reuters, the BBC and The Guardian have approached AI deployment, finding that each outlet has built its own framework around editorial priorities, governance and audience trust rather than embracing a uniform set of tools. The research analyzed public AI policies, editorial guidelines, trial reports and industry presentations released through 2025.

The study suggests AI adoption in journalism is increasingly less about whether to use the technology and more about how news organizations establish controls over its use.

Reuters has positioned AI as a reporting assistant that speeds journalism without replacing editorial judgment. Its in-house tools include Lynx Insight, which analyzes financial data in real time, and Fact Genie, which helps reporters process corporate press releases. Journalists must independently verify AI-generated claims before publication under its standards. Market reporting also provides unusually fast error-correction signals, since traders spot bad information quickly — a less forgiving model than political reporting or investigations, where a factual error can sit unnoticed far longer.

Reuters Editor-in-Chief Alessandra Galloni has described AI as a “force multiplier” that helps journalists analyze large document collections and identify patterns more efficiently, with governance checkpoints built in at each stage to preserve editorial accountability.

The BBC has taken one of the industry’s most cautious approaches, prioritizing transparency over rapid deployment. It permits AI for specific tasks such as At a Glance, which summarizes long articles, and BBC Style Assist, which reformats local stories in house style — a task the broadcaster says can otherwise take about 30 minutes. No AI-assisted material runs without an editor’s sign-off first.

That caution is evidence-led: in October 2025, the BBC and the European Broadcasting Union published research showing AI assistants misrepresented news content 45% of the time through faulty sourcing, fabricated details and outdated information. The broadcaster later introduced AI disclosure labels at the top of stories.

The Guardian revised its guidance in March 2026 to permit limited use of generative AI for tasks such as generating image alt text, analyzing parliamentary documents and transcribing audio, provided the tools meet editorial standards and a senior editor approves where required.

The policy reflects the outlet’s broader philosophy that AI should support, not replace, journalists. “Our generative AI framework is designed to support our journalists’ expertise, never replace it,” the outlet said in a statement. “Our journalists are always accountable for the journalism they create, and use of these tools requires absolute rigor and responsibility.”

The Guardian’s reader-funded trust ownership model has also shaped its strategy, allowing the publisher to prioritize editorial independence over commercial pressure even as the newsroom gradually expands its use of the technology.

The findings illustrate an industry shift away from viewing generative AI primarily as a content-generation tool. Leading publishers are increasingly deploying it behind the scenes — for research, document processing, transcription, translation and newsroom efficiency — while keeping journalists responsible for editorial decisions.

The divergent strategies also reflect broader debates across the news industry over governance, transparency and the economics of AI. As publishers negotiate licensing agreements with technology companies while pursuing litigation over unauthorized use of copyrighted reporting, many are simultaneously developing internal policies governing how AI can be used inside their own newsrooms.

Nieman Lab’s analysis concludes that newsroom AI adoption is evolving into an organizational question rather than simply a technological one. Success, the report argues, depends not only on selecting AI tools but on establishing editorial policies, accountability mechanisms and workflows that preserve journalistic standards as AI becomes part of everyday reporting.

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What content do we actually need to come up in AI search?

It’s a question businesses ask every day. As more customers turn to ChatGPT, Gemini, and other AI platforms to research products, services, and providers, marketers know AI search matters. The challenge is knowing which content investments are most likely to improve visibility and ultimately bring customers to your website.

To answer that question, WebFX analyzed nearly 600,000 AI sessions across 2,500 URLs spanning businesses in 15-plus industries between May 2025 and May 2026.

These findings provide a practical blueprint for the content businesses should prioritize to earn more visibility, website traffic, and customers from AI search.

What types of content earn the most AI traffic?

The data revealed several clear winners.

Homepages generated the largest share of AI traffic by a wide margin (31.3%), followed by product pages (16.8%), service pages (11.4%), blog articles (11.3%), and FAQ/resource pages (7.2%).

These “big five” page types accounted for more than two-thirds of all AI traffic in the dataset.

Looking across the distribution, three findings stood out.

Key finding 1: Homepages drove nearly one-third of all AI traffic

Homepages generated 31% of all AI sessions, more than any other page type in the analysis.

This reflects how people increasingly use AI. Instead of navigating through multiple search results, users often ask AI to recommend businesses, products, or providers. Once AI identifies a strong match, the homepage naturally becomes the starting point for learning more.

For example, when researchers asked ChatGPT for the best AC repair company in Hershey, PA, every recommendation pointed directly to a company’s homepage, where visitors could explore services, reviews, and decide whether to take the next step.

Key finding 2: Product, service, and resource pages are AI traffic magnets

After homepages, product pages (16.8%), service pages (11.4%), blog articles (11.3%), and FAQ/resource pages (7.2%) generated the largest share of AI traffic.

Although these pages serve different purposes, they all help users move forward. Some answer detailed questions. Others compare solutions or explain services. Many help users evaluate whether a business is the right fit. AI platforms consistently referred users to pages that supported those next steps.

Key finding 3: AI rewards comprehensive websites

Homepages drove the largest share of AI traffic in the study, but they weren’t the whole story. Product pages, service pages, blog articles, FAQs, industry pages, and tools all earned meaningful AI referrals.

The highest-performing websites weren’t relying on one standout page. They built a portfolio of content that answered different questions and supported different stages of the customer journey, giving AI multiple opportunities to recommend their business.

Business takeaway: Build a content ecosystem that establishes authority in your niche

Every page contributes a signal about your business:

• A homepage introduces who you are
• Commercial pages explain what you offer
• FAQs answer common questions
• Educational content demonstrates expertise

Together, they create a digital fingerprint that helps AI understand where your business has authority and when it’s the right recommendation for a customer’s next question or next step.

Why AI traffic is more bottom-of-funnel than you think

More than 9 in 10 AI sessions landed on consideration or decision-stage content, while awareness pages accounted for just 2.3% of AI traffic.

That finding aligns with another WebFX study showing AI traffic converts 1.2 times higher than traditional organic search. Together, the data suggests AI is increasingly connecting businesses with customers who have already moved beyond initial research and are actively comparing options, evaluating providers, and preparing to make a decision.

Key finding 1: AI users are evaluating, not just learning

Decision-stage content accounted for 55.3% of all AI traffic, while consideration pages generated another 36.7%.

Combined, 92% of AI traffic landed on content designed to help users compare providers, evaluate solutions, or make purchasing decisions.

That paints a very different picture than many marketers and business owners might have.

Key finding 2: AI is shortening the research process

Traditional search often encourages users to research one question at a time. AI changes that experience.

Instead of bouncing between multiple websites, users can ask AI to compare providers, summarize reviews, explain tradeoffs, and narrow their options before ever clicking a link. By the time they visit your website, they’re often looking for validation rather than an introduction.

That helps explain why service and product pages, FAQs, and comparison content consistently appear among the strongest AI performers.

Key finding 3: Transactional content drives the majority of AI traffic

The content intent data tells a similar story.

Nearly 7 in 10 AI sessions landed on transactional content, while informational pages accounted for just 18% of AI traffic. Both the funnel stage and commercial intent data point in the same direction: The majority of AI traffic reached pages supporting evaluation and decision-making.

Business takeaway: Prioritize content that helps customers make decisions

For years, many organizations invested heavily in top-of-funnel educational content to grow organic visibility. That foundation remains important. Educational resources build authority, earn citations, and help AI understand your expertise.

The WebFX research suggests the biggest opportunity for AI traffic often comes later in the customer journey. Businesses that invest in strong service pages, comparison content, pricing resources, FAQs, and other decision-stage assets are better positioned to capture users after AI has already helped narrow their options.

As AI becomes a larger part of the buying process, some of the highest-value content on your website may be the content that helps customers confidently take the next step.

What content performs best in AI vs. organic search?

For decades, content strategy has largely been shaped by one question: What content performs best in Google Search?

As AI search becomes a growing source of discovery, a new question is emerging: Will the same content continue to perform as customers shift from search engines to AI assistants? The answer has important implications for where businesses invest their time, budget, and content strategy over the next several years.

The answer? Both yes and no. Many of the same page types perform well across both channels, but AI platforms don’t distribute traffic the same way Google does. Comparing the two reveals where AI is creating new opportunities and where traditional search continues to have the upper hand.

Key finding 1: AI creates the biggest opportunities for product, blog, and resource content

The largest AI lift came from blog articles (+7.3 percentage points), product pages (+7.1 points), and FAQ/resource pages (+5.3 points).

These pages all serve a similar purpose. They help users compare options, answer detailed questions, and continue evaluating solutions after AI has narrowed the field. For businesses looking to grow AI traffic, they are some of the clearest opportunities in the dataset.

Key finding 2: Google still leads branded and local discovery

While homepages generated the largest share of AI traffic overall, they accounted for an even larger share of organic traffic (44% vs. 31.3%). The same pattern appeared with location pages (-4.7 AI lift) and tools/calculators (-3 AI lift).

That suggests traditional search continues to play a larger role in branded, navigational, and local discovery, while AI increasingly connects users with deeper content that supports evaluation and decision-making.

Key finding 3: Service pages consistently perform across both channels

One result stood out for a different reason.

Service pages generated nearly identical shares of AI and organic traffic (11.4% vs. 10.9%), resulting in an AI lift of just +0.5 percentage points.

That’s encouraging because it suggests investments in high-quality service pages continue to pay dividends regardless of how customers discover your business.

Business takeaway: Invest where AI lift is highest without losing sight of your strongest SEO assets

Comparing AI and organic search reveals that homepages, service pages, and product pages consistently perform well across both channels, making them some of the strongest long-term investments.

Blog articles, FAQ/resource pages, and industry pages generated the highest AI lift, signaling opportunities to grow AI traffic beyond traditional SEO.

At the same time, location pages and tools continue to be important drivers of organic search visibility and remain worth protecting.

Knowing where to invest is only part of the equation. The next question is what makes those pages successful enough for AI to recommend them in the first place?

Content playbook for winning AI traffic

The research provides insights into the pages earning AI traffic, where users enter the buying journey, how AI search differs from traditional organic search, and where businesses have the biggest opportunities to invest.

Those findings naturally lead to one final question: What does content that consistently earns AI traffic have in common?

Looking across the 2,500 URLs generating the highest levels of AI referral traffic, five trends emerged. No single tactic guarantees AI visibility, but together they provide a practical playbook for creating content that AI systems are more likely to recommend and customers are more likely to visit.

1. Start with a trusted homepage

Homepages generated 31.3% of all AI traffic, making them the single largest destination in the dataset.

That reinforces the important role homepages play in AI search. Before recommending a product, service, or resource, AI often introduces users to the business itself.

A clear, trustworthy homepage gives users a place to validate that recommendation and continue exploring. Make sure your homepage clearly communicates:

• Who you are
• Who you serve
• What makes your business different
• Why people trust your business (think reviews, awards, certifications, and other trust signals)

2. Build commercial depth

Product and service pages accounted for 28.2% of AI traffic, helping users move from discovery to evaluation.

Rather than stopping at a homepage, AI frequently recommends commercial pages that answer buying questions, explain services, and help customers compare solutions.

Expand your service and product pages beyond basic descriptions by addressing pricing, implementation, comparisons, FAQs, and the questions prospects ask before contacting sales.

3. Help customers make decisions

The report found that 92% of AI traffic landed on consideration and decision-stage content.

That indicates AI is often introducing users after much of their early research is complete. The strongest-performing pages reduced uncertainty and helped customers confidently take the next step.

Content types that help support the decision-marketing process include:

• Comparison pages
• Buyer’s guides
• Pricing resources
• FAQs
• Industry-tailored content

For example, a quick search in ChatGPT for “what’s a good price for a new garage door” yields content geared toward helping searchers evaluate pricing and what’s worth the investment.

4. Answer specific questions completely

Pages most likely to be cited by AI-generated answers averaged a 4.76 out of 5 specificity score, which measures how specific a page’s content is based on the presence of concrete details such as facts, named entities, dates, statistics, pricing, and product names. Those same pages averaged a 4.15 out of 5 completeness score, which measures how thoroughly a page answers its primary topic and addresses related questions and context. The pages most likely to be cited by AI-generated answers outperformed other pages on both measures.

The strongest-performing pages focused on clearly defined:

• Audiences
• Industries
• Services
• Customer questions

These pages also backed up their content with:

• Specific facts
• Named entities
• Statistics
• Product names
• Pricing details
• Real examples

They also anticipated the next question a user might ask, addressed common objections, and expanded beyond the initial answer with comparisons, FAQs, implementation guidance, and other supporting information that helped users continue making decisions without returning to AI or Google.

Businesses looking to increase AI visibility should create focused content around specific customer needs, then build those pages into comprehensive resources that:

• Answer related questions
• Explain tradeoffs
• Provide examples
• Support the entire decision-making journey

5. Demonstrate authority and expertise

Trust signals consistently appeared across the strongest-performing pages in the study.

More than two-thirds included expert credentials, 52.6% featured original research or first-party data, and pages with citations averaged 26% more AI traffic than those without.

Rather than relying on a single trust signal, the highest-performing pages built confidence from multiple angles. You can do the same with your content by:

• Publishing original research
• Incorporating subject matter experts
• Supporting claims with credible citations
• Identifying authors

All these steps help reinforce expertise.

Business takeaway: Become the source AI wants to recommend

Looking across nearly 600,000 AI sessions, the strongest-performing pages all shared the same goal: Helping users confidently take the next step.

That’s ultimately what AI search is trying to do.

Businesses don’t need a completely different content strategy for AI.

They need content that’s trustworthy, specific, comprehensive, and genuinely useful throughout the customer journey. Those are the pages AI consistently recommended throughout the study, and they’re the pages most likely to earn visibility, traffic, and customers as AI search continues to evolve.

Do different AI platforms recommend different content?

Most discussions about AI search treat it as a single channel. In reality, businesses are competing for visibility across multiple AI assistants, each with its own user experience and recommendation patterns.

Looking across the data, one platform currently stands apart: ChatGPT accounts for 97.5% of AI referral traffic in the dataset.

That doesn’t mean Gemini, Perplexity, Claude, or Copilot aren’t important.

AI search is evolving rapidly, and today’s platform mix will almost certainly change over time. But it does mean the broader trends throughout this report largely reflect how users interact with ChatGPT today.

Although traffic volumes remain much smaller outside ChatGPT, the study included a platform-level breakdown to provide additional context on where those referrals are landing.

The differences are subtle, but a few early patterns emerge:

• ChatGPT sends traffic across a broad mix of page types.
• Perplexity directs a relatively larger share of traffic to blog content.
• Gemini appears to over-index on tool and calculator pages as well as homepages.

Given the relatively small volume of traffic outside ChatGPT, it’s too early to draw broad conclusions about platform-specific optimization strategies. As adoption grows, however, these referral patterns will be worth monitoring.

Business takeaway: Prioritize the content, not the platform

Rather than building separate content strategies for individual AI assistants, focus on creating high-quality content that serves users well regardless of where the recommendation originates.

As the AI search landscape evolves, businesses should build strong homepages, commercial pages, educational resources, and decision-support content.

Insights to action: What this study means for your AI content strategy

AI search is becoming an increasingly important part of how customers discover and evaluate businesses. Looking across nearly 600,000 AI sessions, one theme appeared repeatedly. The pages earning AI traffic made it easy for both customers and AI systems to:

• Understand who the business served
• What made the business credible
• Why the business deserved a recommendation

That gives businesses a practical direction for the years ahead.

Investing in trusted homepages, stronger commercial pages, deeper educational resources, and first-party expertise creates more opportunities to earn visibility across both AI and traditional search.

Those investments improve the customer experience while strengthening the signals AI systems rely on when deciding what to recommend.

Methodology

This study measures AI referral traffic, not AI citations. WebFX analyzed visits sent from AI platforms rather than how frequently brands appeared in AI-generated responses. The dataset focuses on high-performing AI pages. Findings reflect characteristics commonly shared by the pages generating the most AI traffic, rather than the average webpage.

This story was produced by WebFX and reviewed and distributed by Stacker.

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Just 34% of North American consumers view advertising in AI chat platforms positively, according to a new global study from ad verification company DoubleVerify, suggesting brands still face an uphill battle as they look to monetize generative AI experiences.

The findings suggest consumers aren’t rejecting AI advertising, but rather judging its execution. While people are generally comfortable with AI-powered experiences, they respond differently to AI-generated ads depending on their quality and placement. Marketers, meanwhile, remain concerned about brand safety and transparency.

The report, based on surveys of 22,000 consumers across 22 markets and 2,020 marketers and advertisers across 21 markets, found that 46% of consumers globally view advertising in AI chat platforms positively, compared with just 34% in North America, the least receptive region surveyed. Consumers responded most favorably to ads that were contextually relevant, while advertising alongside negative, emotionally sensitive or highly personal conversations drew the strongest negative reactions.

“AI is rapidly reshaping how content is created, how consumers experience media and how advertisers reach audiences,” DoubleVerify CEO Mark Zagorski said. “Our research confirms that AI itself is not what determines engagement. The quality of the output does.”

Consumers also distinguished sharply between high- and low-quality AI-generated advertising. While 56% said they cannot consistently identify AI-generated content, 42% said a brand’s use of low-quality or “uncanny” AI ads would hurt their opinion of the brand. By comparison, 40% said polished AI-generated advertising would improve their perception.

Marketers expressed many of the same concerns. More than half (53%) said they worry about ads appearing alongside low-quality AI-generated content, while 48% said they are concerned about using AI to produce advertising creative. Half also expressed concern about advertising within AI platforms, with those figures rising to 63% among North American marketers.

“Advertisers need the same confidence and clarity in emerging AI environments that they expect across every other digital channel,” Zagorski said, arguing that media quality, transparency and independent measurement will become increasingly important as AI advertising expands.

The study also found consumers in Latin America and Asia-Pacific were the most enthusiastic about AI, with roughly seven in 10 saying AI-generated content has improved their online experience and more than half expressing positive views of advertising inside AI platforms.

For publishers, the research reinforces that AI-powered experiences will need to earn advertisers’ trust before becoming premium ad inventory. As AI becomes a larger part of news products, publishers may be better positioned than AI-native platforms if they can pair trusted content with transparent, independently verifiable advertising environments.

More broadly, the research suggests the future of AI advertising will depend on trust as much as technology. As conversational AI evolves into a potential advertising channel, platforms, publishers and verification firms will be under pressure to show that AI-generated environments can deliver the transparency, brand safety and measurement that marketers expect from traditional digital media.

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ChatGPT has begun refusing requests to write in the style of named authors, marking a notable change in how OpenAI’s chatbot handles imitation prompts. As reported by Ars Technica, the system now steers users toward describing literary traits rather than directly invoking a writer’s style.

The Media Copilot was able to replicate the result on July 28. After asking ChatGPT to write a short story in the voice of Ernest Hemingway, the chatbot replied, “I can’t write in the exact style of a specific author or closely imitate a copyrighted work’s voice. I can, however, write an original passage that draws on some broad characteristics often associated with Ernest Hemingway—plain language, understated emotion, concrete observation, and spare dialogue—without closely imitating his distinctive expression.”

The change is less about the output than the prompt. Requests that explicitly name an author may now be refused, but prompts describing the same stylistic traits—such as minimalist prose, clipped dialogue or a gothic mood—can still generate comparable writing without invoking a specific writer.

The apparent shift comes as OpenAI continues to face multiple copyright lawsuits over its AI models and outputs. While those cases primarily concern training data rather than stylistic imitation, they have intensified scrutiny over how AI systems reproduce or emulate copyrighted creative works, prompting companies to adopt more cautious safeguards around requests that closely mimic identifiable authors.

Other chatbot makers have drawn the line differently. Ars Technica cites a No Latency study that found Google’s Gemini complied consistently with author-imitation requests, while Perplexity refused and redirected them. Anthropic’s Claude and Microsoft Copilot fell between those positions, complying while adding qualifications. The uneven treatment means a refusal in one product does not prevent a writer or editor from trying the same prompt elsewhere.

For newsrooms and publishers, ChatGPT’s new author-style restrictions underscore the need for AI policies that govern editorial practices rather than any single technology provider. Internal guidelines should define whether staff may request imitation of living authors, deceased writers, competing publications or an organization’s own house style, while requiring disclosure and human review before AI-generated text is incorporated into published work.

OpenAI has not, based on the material cited here, announced a formal written-text policy that matches the chatbot’s current behavior. Until it does, publishers should expect the boundary to be defined largely by the product itself: prompts that explicitly name authors may be declined, while requests describing the same stylistic qualities in broader terms can still generate a response.

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Newsmax’s current and archived reporting will feed Meta’s AI-powered search and discovery tools under a licensing agreement announced Tuesday, giving the social media company another publisher partner as it builds news answers into its products.

The agreement reported by The Desk covers Meta services including Facebook, Instagram and WhatsApp, and extends to current and future consumer devices sold by the company. Meta will use the material to train its AI-supported search and discovery tools, while those tools will also link users to Newsmax stories and videos and generate short summaries from written work.

Christopher Ruddy, Newsmax’s chief executive, welcomed the deal in a statement to The Desk: “Newsmax applauds the significant resources Meta is putting into AI to keep America at the forefront of this emerging technology.” He added that the publisher wanted to help users reach timely, high-quality journalism through AI technologies.

The reported terms do not include a price or other financial details. That leaves a central question unanswered for publishers weighing similar deals: what compensation reflects the value of an archive, a daily reporting operation and traffic that may be intercepted by an AI-written answer before a reader reaches the original article.

Newsmax joins a growing group of right-of-center outlets that have signed Meta agreements, including Fox News Media, the Daily Caller and the Washington Examiner. The Desk also reports that Meta has reached content arrangements with News Corp, Warner Bros. Discovery, USA Today Company and People Inc.

Meta’s stated aim is broader than adding another political perspective. In comments cited by The Desk from December, the company said it wants Meta AI to become more responsive, accurate and balanced, particularly during breaking news events when its AI systems struggle to keep pace. Meta is integrating the assistant across its consumer products, placing search, recommendations and conversational answers inside the same ecosystem.

That goal remains untested. Licensing news publishers gives Meta a clearer legal basis to use their reporting than scraping the web or relying on unresolved fair-use claims. But it does not answer how Meta AI will choose sources, attribute reporting, summarize competing accounts or weigh conflicting information. Adding more publishers expands the pool of reporting. It does not, on its own, ensure balanced results.

For newsrooms and publishers, the Meta-Newsmax agreement underscores how AI licensing has become as much a distribution strategy as a rights negotiation. As more publishers strike AI licensing agreements, attention is likely to shift from financial terms to attribution, referral traffic, transparency and the distinction between training rights and real-time content use.

Meta’s next test is execution. The company will need to show that licensed journalism makes Meta AI faster, more reliable and better sourced without reducing publisher reporting to an invisible input. Newsmax has secured a place in that effort. The success of the agreement will ultimately be measured less by how much Newsmax content appears in Meta AI than by whether AI-generated answers still create an economic incentive to produce the original reporting.

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MIT Technology Review’s paywalled articles will now be available through Muck Rack‘s monitoring platform under a licensing deal that expands communications teams’ access to artificial intelligence and emerging technology coverage. In its announcement of the deal, Muck Rack said it is the first communications platform to license the publication’s content.

The agreement gives Muck Rack customers access to the publication’s full editorial output, rather than only material visible on the open web. That helps eliminate a blind spot created by paywalls, giving companies a fuller view of coverage, competitors and reputational risks.

Muck Rack has been building a roster of direct publisher deals, recently adding Bloomberg Media and STAT, according to the announcement. MIT Technology Review, founded at MIT in 1899, covers the business, policy and social effects of technology as well as technical developments.

Natan Edelsburg, Muck Rack’s chief partnerships officer, said the arrangement reflects the company’s effort to work directly with publishers while giving users access to trusted AI reporting. Ted Hu, senior manager of licensing at MIT Technology Review, said the deal takes the publication’s reporting to communications professionals beyond its usual journalist and technologist audience.

Muck Rack is pitching the deal as a way to help communications teams track how brands appear in both AI-generated answers and traditional news coverage. The company said earned media, referring to unpaid editorial coverage such as news articles, accounts for 84% of citations in responses from ChatGPT, Claude and Gemini, while journalism makes up 27% of sources cited by those AI systems. Muck Rack did not disclose its methodology, time frame or underlying dataset, so the figures could not be independently verified.

The licensing model is more concrete than those numbers. It gives Muck Rack permission to distribute and search reporting that would otherwise be restricted, while giving a publisher a commercial route into enterprise monitoring. It also differs from the unresolved question of whether AI companies need permission to train on publishers’ archives.

For publishers, the deal reflects a broader effort to monetize journalism beyond subscriptions and advertising. As news organizations challenge search engines and AI companies over the use of their reporting, licensing agreements provide a way to generate revenue while ensuring their content is available through enterprise platforms. The arrangement also highlights the growing value of credible journalism as AI systems and communications professionals increasingly rely on it.

Muck Rack’s next challenge is proving customers will pay for licensed access when many media monitoring tools still rely on publicly available content. If more publishers sign similar agreements, media monitoring could become a new licensing channel for news organizations rather than another way their content is used without compensation.

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James Allen of Billpin was quoted as a finance expert by outlets including CBS News, the New York Post and Business Insider. Qwoted later barred his account after flagging repeated AI-generated submissions and finding that he had failed its verification process, according to Press Gazette’s investigation.

The case is a stark warning about the source pipeline behind everyday newsroom copy. Qwoted, a U.S. platform that connects journalists with sources, says it has banned hundreds of agencies, executives and experts for conduct ranging from fabricated identities to AI-generated pitches and false claims of expertise.

Billpin’s website is now blank, and Allen’s LinkedIn profile has disappeared, Press Gazette reported. The publication said Allen did not respond to requests to verify his identity. Press Gazette concluded the operation appeared designed to win media mentions that could boost search rankings, or backlinks.

A quote in a respected publication can generate a link that helps an otherwise obscure website gain visibility in search results. That creates an incentive to manufacture expert identities that appear credible enough to earn media coverage.

Qwoted CEO Dan Simon said generative AI has dramatically accelerated an already difficult problem. “AI has just poured petrol on the disinformation fire,” he told Press Gazette.

The platform says it now handles more than 15 violations a day and blocks about 50 prospective clients from registering each day. Shelby Bridges, Qwoted’s head of user experience, said the volume of low-quality pitches began rising rapidly after ChatGPT’s public release in November 2022.

Simon described a source ecosystem that increasingly blurs the line between legitimate expertise and fabrication. “You’ve got real agencies representing fake experts with fake expertise. You’ve got real agencies with fake experts and real agencies with real experts with fake expertise, and fake agencies with fake experts with fake expertise.”

One recurring pattern is a purported expert responding to queries on subjects with no obvious connection to their background. Press Gazette identified examples of sources offering commentary on finance, cleaning, human resources, pet sitting and mental health.

Qwoted combines human review with signals such as unusually high pitching volumes. It also uses Pangram, an AI-content detection service, to flag potential abuse. But AI detection is only one signal. A model score cannot establish that a person is fictional, that a quote is false or that an expert lacks relevant experience. Qwoted’s reported checks therefore matter more than a detector’s output alone.

Simon said some reporters have told him they do not object to real experts using ChatGPT to polish their responses. The bigger risk comes when AI helps conceal a fabricated identity or invented credentials, allowing a bogus source to slip into print before anyone questions its legitimacy. Platforms can suspend accounts after the fact, but the final responsibility still rests with newsrooms.

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Trust in AI answers rises and falls with the credibility of their sources. More than 90% of people trusted an AI response when they completely trusted its cited source, but that figure plunged to about 10% when they completely distrusted the source, according to new findings reported by Press Gazette.

The figures come from an Ipsos survey of 1,000 UK adults for the Association of Online Publishers’ Artificial Intelligence Publisher Impact Study. The findings show that AI can distill reporting into a polished answer, but users ultimately judge that answer by the credibility of the news organization it cites.

The effect extended even to publishers respondents felt neutral about. Trust in the AI answer was only about 25% when the cited source was rated neither trusted nor distrusted. The survey measures correlation, not causation, and reflects stated attitudes rather than observed behavior. Even so, the pattern is unmistakable.

Trust also affected reported willingness to visit the underlying publisher. Nearly half of people who somewhat or completely trusted a cited source said they would click at least one link in an AI response. That finding fits a wider pattern covered in The Media Copilot’s reporting on news brands and AI clicks: the publisher’s name may still be what persuades users to leave the chatbot, even as AI interfaces give them fewer reasons to click elsewhere.

There is an uncomfortable counterpoint. Even when users completely trusted the cited source, nearly a third said they would stop at the AI answer rather than click through. That figure was similar among those who completely distrusted the source. A citation alone can make an AI answer more credible without delivering the visit, subscription opportunity, or advertising impression that paid for the original reporting.

The study also found that 37% of respondents did not know AI tools can fabricate information or sources. That rose to about 45% among 45- to 54-year-olds. The result matters because a polished answer can borrow authority from reputable citations while still getting a claim wrong, omitting context or inventing a detail.

AI companies have good reason to seek current, attributable reporting. OpenAI’s partnership with News Corp is one public example of the licensing deals that give chatbots access to professional journalism. Yet the confidentiality of many licensing deals makes it difficult for publishers to know whether they are being fairly compensated for the credibility their reporting brings to AI answers.

For newsrooms, the immediate task is less about winning back every lost referral than preserving the conditions that make their reporting worth citing. Clear attribution, strong archive pages, distinctive analysis and direct audience relationships matter when an AI answer becomes the first read. Publishers also need to decide which crawlers and products earn access.

The survey’s implication is clear. AI platforms are borrowing trust that publishers spent decades building, while publishers risk capturing only a fraction of the value it creates. As AI answers become the default gateway to information, the rules governing licensing, attribution and publisher control will determine whether publishers can still turn trust into revenue.

The post Citing trusted news brands increases confidence in AI responses, UK Ipsos survey finds appeared first on The Media Copilot.