ChatGPT users on the mobile app saw roughly twice as many ads per hour this July as they did in April, according to Business Insider. The jump coincides with a sharp expansion in the pool of advertisers buying those slots.

US data from market intelligence firm Sensor Tower estimates OpenAI has nearly tripled its advertiser count on ChatGPT, from about 300 in April to more than 820 in July. At least 160 advertisers joined in July alone.

The advertiser mix has shifted too. Tech companies including Speechify, Jotform and Natural Intelligence dominated the top ranks in April. By July they had fallen out of Sensor Tower’s top 10, replaced by Booking Holdings, Intuit, Home Depot and L.L.Bean.

Scheels, a sports clothing retailer, was the only company to sit in the top 10 in both months.

The shift extends beyond advertiser count. Retail still accounts for the largest share of ChatGPT ad spending, but its dominance is slipping as financial services, travel and tourism, and jobs and education gain ground.

Financial services has grown the fastest, rising from 2% of ad spend in April to 12% in July.

Sensor Tower identified BestMoney.com as one of ChatGPT’s top advertisers in July, saying the broader mix suggests OpenAI is diversifying its advertiser base — a potentially positive sign for monetization.

The numbers remain a fraction of OpenAI’s ambitions. The company reported $100 million in annual recurring ad revenue in May — a rounding error next to Google’s $81.6 billion and Meta’s $59.3 billion in ad revenue in their most recent quarters.

OpenAI serves ads to users on its free tier and its $8-a-month Go plan, which together account for the vast majority of a user base Sensor Tower estimated at 1 billion monthly app users in May.

OpenAI ads chief Dave Dugan told Business Insider in June that the company initially kept ad placements deliberately limited to protect the user experience. Four months in, he said, the team has grown more confident about scaling up. For now, ads appear beneath ChatGPT’s answers, while OpenAI avoids placing them alongside queries about personal health or politics.

For publishers and media buyers, the bigger story is not today’s ad revenue but where the next wave of attention is forming. A chatbot with a billion users putting ads beneath its answers creates a new pool of inventory competing with search and social for the same budgets.

OpenAI’s self-serve ad platform, launched in May, remains rudimentary compared with the mature systems run by Google and Meta. That makes the early surge in big-brand spending look more like testing than a long-term commitment.

For newsrooms already watching referral traffic decline as readers turn to chatbots instead of clicking links, the stakes are higher. The way OpenAI builds out its ad business could shape where publishers reach audiences — and how they get paid — as search behavior shifts.

OpenAI’s next steps include expanding into new markets and adding targeting tools, both designed to pull more advertising dollars into an app most people still use for free. The bigger question is whether advertisers stick around once the novelty wears off. July’s numbers suggest growing interest, but not yet lasting commitment.

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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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YouTube trust and safety chief Matt Halprin sat down for a Creator Insider video last week to make more explicit what the platform means by “inauthentic content.” The result, rolled out July 16, is a set of clarifications that spell out three specific buckets of video that can no longer earn money through the YouTube Partner Program.

The update isn’t a brand-new rule. As TechCrunch reported, YouTube already moved last year to stop creators from making revenue off mass-produced, repetitive videos that AI tools make cheap and fast to churn out. This latest change adds detail to those existing guidelines rather than replacing them.

The first category is generic, repetitive or template-based content. Halprin described channels stuffed with cookie-cutter clips made through AI, CGI or templates that barely change from one video to the next.

The second targets what YouTube calls off-putting content, meaning videos built to distress or emotionally manipulate viewers into clicking. Halprin’s example: an animal shown in distress before someone conveniently arrives to rescue it.

“We’ve heard from our viewers that that’s not something that they like,” he said. Channels dedicated to this content lose Partner Program access whether or not AI made the videos.

The third bucket goes after AI personas, which are AI-made representations of real people.

Halprin was careful not to frame AI as the villain. “AI can actually allow people to make a lot of videos,” he said. “Sometimes those videos are great, and it really enhances creativity.” The same tools, he added, also let people spit out large volumes of near-identical clips with no narrative arc, which is the content farming YouTube wants out of its monetization program.

The Partner Program, which pays creators through ads and subscriptions, is central to YouTube’s business, and the platform now pulls in more ad revenue than Disney, Paramount and Warner Bros. Discovery. Letting the feed fill with low-quality AI output risks the viewer trust that keeps those ad dollars flowing.

For publishers and newsrooms experimenting with AI-assisted video, the takeaway is about intent, not tools. YouTube isn’t penalizing AI use itself. It’s penalizing volume without originality, manipulation for clicks and synthetic voices on topics where accuracy carries real stakes.

The biggest unanswered question is where YouTube will draw the line. Halprin said channels with too much repetitive, low-effort or manipulative content will lose monetization, but he did not define the threshold. The clarified policy applies immediately to all YouTube Partner Program members.

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beehiiv is expanding beyond email publishing with a suite of new products aimed at keeping independent publishers and news organizations from relying on multiple software vendors to run their business.

At its Summer Release Event on July 16, the newsletter platform introduced four products: Community, a built-in discussion platform; Copilot, an AI agent for audience and business operations; programmatic advertising; and a redesigned visual editor. Together, the launches mark beehiiv’s broadest attempt yet to compete as an all-in-one publishing platform rather than just a newsletter service.

The expansion reflects a shift in digital publishing, where newsletter platforms are increasingly competing to own more of the publisher workflow, from audience engagement and monetization to AI-powered operations.

“We believe the next chapter of the creator economy and content businesses is about consolidation,” co-founder and CEO Tyler Denk said during the event.

For publishers, the most significant announcement may be Copilot, beehiiv’s first native AI product. Rather than serving as a writing assistant, the company describes it as an AI operator capable of analyzing subscriber data, identifying audience segments, drafting marketing campaigns, launching workflows and surfacing revenue opportunities through a chat interface.

The launch builds on beehiiv’s adoption of Model Context Protocol, an open standard introduced by Anthropic that allows AI systems to securely connect with external data and software. As more publishing platforms adopt MCP, AI tools are shifting from generating content to executing operational tasks across newsroom business systems.

beehiiv also introduced Community, a feature designed to let publishers host subscriber discussions inside their own branded websites instead of relying on platforms such as Discord, Slack or Facebook Groups. Paid subscriber communities, moderation tools and podcast integration are built into the feature.

For news organizations, the move reflects a growing emphasis on first-party audience relationships as publishers seek to reduce dependence on social platforms and create additional value for subscribers.

The company also expanded its advertising business with programmatic newsletter ads that automatically match advertisers with newsletters based on audience characteristics and campaign performance. The system is intended to fill unsold inventory alongside direct advertising deals.

beehiiv said publishers on its platform now receive more than $1 million per month through its advertising network and have generated more than $50 million in subscription revenue.

The final launch was a redesigned visual editor that previews how newsletters and website content will appear before publication while supporting email, web pages, automations and recommendations from a single interface.

The announcements highlight how newsletter platforms are evolving into broader publishing infrastructure providers at a time when many news organizations are looking to simplify technology stacks and automate business operations. Rather than stitching together separate tools for newsletters, communities, advertising and audience management, publishers increasingly have the option to consolidate those functions within a single platform.

That consolidation could reduce software costs and technical overhead, particularly for smaller newsrooms and independent journalists. At the same time, it also concentrates more of a publisher’s audience data, monetization and workflow inside a single vendor, raising familiar questions about platform dependence as publishing infrastructure becomes more centralized.

beehiiv also previewed upcoming podcast advertising features, including dynamic ad insertion, signaling that the company intends to expand further into audio publishing as it broadens its reach beyond newsletters.

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The Associated Press has joined SPUR as the coalition’s first U.S. founding member, adding one of the world’s largest news licensing organizations to a publisher-led effort to create standards for how AI companies track, value and compensate journalism.

Founded in March 2026, the Standards for Publisher Usage Rights is a publisher-led coalition aiming to move AI content use away from opaque scraping and toward a usage-based licensing model where publishers can see how their work is accessed and used. Its founding members include the BBC, the Financial Times, The Guardian, Sky, The Times of London and European group MediaHaus. The AP now joins 30 publisher members and six affiliates.

SPUR’s central argument is that publishers need more than the ability to block AI crawlers. They need visibility into what happens after AI systems access their content.

SPUR’s technical foundation is a content telemetry standard announced June 12 and open for public comment through July 24. The framework breaks AI content use into five measurable events: content retrieved, grounded, cited, displayed and engaged. It creates a common format for reporting those interactions back to publishers.

The standard also defines the underlying data schema, allowing publishers, platforms and vendors to integrate with the same system.

SPUR has begun testing the framework beyond its membership. Microsoft and CDN provider Fastly participated in a recent London public comment event, while licensing and infrastructure startups including TollBit, Redpine and MonetizationOS have said they plan to implement the standard.

The effort differs from earlier publisher initiatives because it focuses on measuring usage after content enters AI systems. The IAB Tech Lab‘s Content Monetization Protocols, by contrast, focused more heavily on pre-crawl access controls and bot management.

But adoption remains the biggest challenge. SPUR can define how AI usage should be measured, but it cannot force AI companies to provide that information. No single publisher has enough leverage to compel companies such as OpenAI or Google to adopt publisher-friendly standards.

SPUR’s strategy is collective action. If enough publishers adopt the same framework, they may create enough pressure for AI companies to participate. That collective-action logic echoes other recent moves, from Reuters and Time shifting to bot-blocking whitelists to broader efforts to build a global publisher alliance.

“The key here lies in both parts of this being a collective action,” Scott Messer of Messer Media told Digiday in an email. “A divided set of publishers cannot battle the forces of LLMs.”

The approach reflects a broader shift in the publisher-AI debate. Instead of focusing only on payment, SPUR members are trying to establish permission and transparency as the foundation for future licensing.

Publisher alliances, however, have a complicated history. During the rise of programmatic advertising, shared industry systems often created value for platforms while leaving publishers with limited control.

Alessandro De Zanche, a former News U.K. executive and founder of media strategy consultancy ADZ Strategies, argues SPUR differs because publishers are approaching AI through the lens of content ownership rather than advertising inventory.

“The teams that drove the advertising channel into a wall are not the ones now dealing with content, IP and LLMs,” De Zanche said.

With AI, he said, publishers are not selling volume. They are selling accuracy, provenance and reliability, and the stakes are “completely different.”

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Arc XP, the content platform built by The Washington Post and used by publishers including The Irish Times, Sky News, and Graham Media Group, has integrated TollBit directly into its delivery infrastructure, giving the publishers who use Arc a turnkey way to detect, control, and charge AI bots for access to their content.

The partnership, announced Monday, works through Arc XP’s Edge Integration Framework. Once activated, publishers can monitor AI bot traffic through TollBit’s analytics, classify bots in real time, block them outright, or redirect them to a TollBit Bot Paywall that enforces access rules and pricing. Participation in the monetization program is optional.

The distinction from most bot-management tools is the commercial layer. Most blocking tools stop at blocking, but TollBit connects detection to a licensing marketplace. AI companies that want real-time access to publisher content can pay for it programmatically through TollBit’s agent authentication system. Arc XP handles the edge integration and policy controls; TollBit manages the payments.

“AI companies are extracting value from publisher content at scale,” said Sharad Vivek, Global Head of Partnerships at Arc XP. “Publishers need control and transparency, not guesswork.”

The integration is significant partly because of Arc XP’s footprint. Supporting more than 2,500 sites and billions of pageviews a month, it’s one of the larger CMS platforms in news media. A native TollBit integration means a large chunk of the publisher ecosystem can now flip on AI bot monetization from a single dashboard rather than building custom infrastructure.

Whether that monetization materializes at scale is still an open question. AI licensing revenue models are early and unproven for most publishers, and AI scrapers have shown a consistent pattern of bypassing publisher protections when it suits them. The commercial viability of bot paywalls depends on AI companies choosing to pay rather than route around them, which is far from guaranteed. We’ve also looked at TollBit’s data handling before—worth a read for publishers considering the integration.

Still, the infrastructure is getting built. The fact that a platform the size of Arc XP is embedding this natively suggests the industry is moving from blocking as the default to a more structured access-and-compensation model—even if the economics aren’t settled yet.

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The fight over whether AI companies should pay for news is starting to move out of private deal rooms and into policy. According to Poynter, policymakers in Europe, Brazil and other jurisdictions are exploring statutory licensing models that would require payment for the use of publisher content in AI systems.

That matters because the current market is lopsided. A handful of large publishers have negotiated licensing deals with major AI firms, while many smaller outlets are left with lawsuits, opt-out tools and not much leverage. A statutory regime would not end that fight, but it could change the terrain from bespoke negotiations to rules-based compensation.

For publishers, the appeal is obvious. Licensing laws could offer a cleaner route to payment than years of copyright litigation, especially if courts keep moving slowly on training-data disputes. Poynter reported that the European Parliament was set to vote March 10 on a proposal that could open the door to such a framework. An earlier European Parliament press release shows lawmakers were already pressing for stronger protections around copyrighted works used by generative AI.

The broader pressure is not coming from Europe alone. Poynter said Brazil is weighing a draft bill expected in April that could also require payments to publishers. That suggests the compensation debate is widening beyond the U.S. lawsuits that have dominated headlines. It is becoming a policy question about whether AI systems should be allowed to ingest and monetize journalism without a standard payment mechanism.

That does not mean publishers are aligned on the best route. Danielle Coffey, president and CEO of the News Media Alliance, told Poynter, “If we get the right verdicts, we will have a functional marketplace.” That line captures the split in industry strategy. One camp still wants courts to establish leverage first. Another sees statutory licensing as a faster answer to a market that now favors the biggest companies on both sides.

Why this matters for newsrooms

The practical question for newsroom leaders is not just whether they get paid. It is whether payment systems arrive in time to matter.

Publishers are already dealing with two linked problems: AI answers that may reduce referral traffic and AI training practices that may use newsroom work without clear permission. Reuters reported in February that the European Publishers Council filed an EU antitrust complaint over Google AI Overviews, arguing that AI-generated summaries can harm publisher traffic and revenue. Statutory licensing would not solve the traffic problem on its own, but it would at least create a compensation track when traffic leakage and content reuse happen together.

The industry is also becoming more organized. Poynter pointed to the UK’s SPUR coalition and Danish publishers’ legal action against OpenAI as evidence that publishers are moving beyond isolated complaints. The underlying argument is straightforward: if generative AI depends on journalism as input, journalism should not be treated as a free raw material.

What comes next

The obvious caveat is that statutory licensing still has major unanswered questions. There is no settled model yet for who would collect payments, how rates would be set or how money would be distributed among large and small publishers. That is where many legislative ideas go soft.

Still, the significance of this week’s story is that compensation is no longer just a matter of private contracts and courtroom theory. It is turning into a live policy option. If lawmakers push it forward, publishers may gain a more predictable route to payment. If they do not, the market is likely to remain a patchwork: rich publishers cut deals, everyone else waits on judges.

For newsroom executives, this is one to watch closely. The question is no longer whether publishers want payment from AI companies. It is whether governments are ready to build the machinery to force it.

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On Thursday, the BBC, Sky News, The Guardian, The Telegraph, and the Financial Times announced SPUR—the Standards for Publisher Usage Rights coalition—with an open letter calling on media companies worldwide to join the fight for AI content licensing frameworks.

“Our reporting, our archives, our original content, have become foundational training material for AI systems,” the letter states. “This material has been scraped, copied and reused with no common standards to enable permission or payment, weakening the economic model that supports journalism.”

The coalition’s five signatories—BBC director-general Tim Davie, Sky News executive chairman David Rhodes, Guardian CEO Anna Bateson, Telegraph CEO Anna Jones, and Financial Times CEO Jon Slade—argue that AI systems built on journalistic content lack transparency about how they generate answers. That opacity, they say, risks eroding public trust in both news and the AI tools people use to access it.

SPUR’s mission is explicit: establish shared technical standards and licensing frameworks that let AI developers access journalism legitimately while guaranteeing publishers retain control of their content and receive compensation.

This isn’t just a negotiating tactic. The coalition positions itself as a bridge between media companies and AI labs, promising to create “rights-cleared, accountable channels” for content access—essentially, a middle ground between total lockdown and unrestricted scraping. Interested publishers can contact [email protected] to join.

For newsrooms already investing in AI tools, SPUR’s emergence matters. The coalition is explicitly positioning this as a global challenge, not a UK-only issue. That means the frameworks they develop could influence how AI training operates everywhere.

The open letter doesn’t name specific AI companies, but the timing is pointed: OpenAI has been sued by The New York Times over alleged copyright infringement related to training data. Anthropic and Google face similar legal pressure. SPUR appears designed to create a negotiated alternative to courtroom battles.

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Microsoft announced its Publisher Content Marketplace on Feb. 4, a platform designed to broker licensing deals between AI companies and publishers. The marketplace lets publishers control how their content is licensed for AI training and receive payment based on actual usage.

The platform, called PCM, functions as a central hub where publishers license text, images and other media to AI developers under terms they set. Microsoft positions it as infrastructure for what it calls “the agentic web,” where AI agents will increasingly mediate information access.

The marketplace addresses a friction point in AI development: companies need training data, publishers want compensation, but negotiating individual deals is slow and opaque. PCM standardizes the process with usage tracking and per-use payment models.

Major publishers have already signed licensing deals outside this marketplace. News Corp struck agreements with both Google and OpenAI. The Associated Press, The Atlantic, Vox Media, Axel Springer, The Washington Post and TIME have all licensed content to AI companies in individual negotiations.

Microsoft’s marketplace changes the dynamic from bilateral negotiations to a platform model. Publishers post their content and terms. AI developers browse and license what they need. Microsoft handles the technical infrastructure and presumably takes a percentage, though the company has not disclosed marketplace fees.

The timing matters. Meta signed multiyear licensing deals with CNN, Fox News, USA Today, Le Monde Group and others in December 2025 to bring real-time news into its Meta AI assistant. These deals happened before Microsoft’s marketplace launched, suggesting appetite for systematic content licensing continues to grow.

For newsrooms, the marketplace represents another revenue option in a landscape where direct traffic from AI-powered search threatens existing business models. Digiday reported in December that publishers give Big Tech’s AI licensing deals mixed grades, with concerns about appearing in AI search products that cannibalize their own traffic channels.

The marketplace model could make licensing more accessible to smaller publishers who lack resources for complex contract negotiations. But questions remain about pricing power, usage verification and whether per-use payments will generate meaningful revenue compared to lump-sum deals some publishers have negotiated directly.

OpenAI reportedly plans to retire several models including GPT-4.1 in February 2026, according to Future Tools. That kind of model churn could complicate licensing agreements tied to specific AI systems rather than platform-level deals.

Microsoft’s marketplace is live now, starting with Copilot as the first AI builder using licensed content.

The debate over AI licensing comes as newsrooms grapple with whether to pursue litigation or negotiation with AI companies. Some publishers view licensing as a pragmatic revenue stream, while others worry about AI scrapers bypassing their protections entirely.

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