Media Briefing: The IAB finds AI measurement standards elusive for publishers amid platform data gaps

The Interactive Advertising Bureau spent months trying to determine how the industry should attribute and credit conversions influenced by AI. But it ran into a problem: you can’t standardize what you can’t see.

Digiday first reported in August that the IAB was developing an AI attribution framework to standardize measuring and crediting AI’s role in conversions, and the signals to quantify AI’s influence on purchase decisions. The IAB’s working group included tech companies, publishers, agencies, measurement vendors and brands — including People Inc., Walmart, WPP Media, Emberos, Criteo, Bluefish, Microsoft, Brandlight, Tinuiti and Prudential Financial. The resulting “AI-Era Attribution Blueprint,” was published today.

The blueprint addresses some of the questions behind the effort, but it also underscores how much remains unmeasurable. Recommendations, consumer decisions and even transactions may happen inside AI platforms, but that data isn’t yet accessible to advertisers or measurement providers.

“Going in, I thought that we were going to help figure out how credit was assigned through the process. I realized actually what this document was starting to become was more of a call to action to the industry,” Caroline Giegerich, the IAB’s vp of AI said during a virtual IAB roundtable on Monday. “There are evidence layers that are missing. We’ve started to have conversations on that, but there’s still room to go. But without remarking on what’s missing, what we want to see, and AI’s influence in the purchase funnel, I don’t think we’re going to get there. So it kind of started in one place, and over the course of four months, ended in another.”

As Digiday previously reported, the measurement gap has prompted a growing number of startups to pursue solutions.

The IAB’s blueprint offers a framework for understanding AI’s role in driving business outcomes, while acknowledging that data gaps make its influence difficult to reliably measure and attribute. It also underscores a broader challenge for the industry: as publishers expand their GEO offerings to brands, measurement remains a major obstacle.

But publishers are experimenting with ways to address parts of the measurement gap. Time is working with Mobian to measure the performance of the ads it serves to AI agents, for example, and Bustle Digital Group is working with Profound to measure its GEO campaign performance for brands. Those efforts offer visibility into specific activity, but they don’t yet solve the broader challenges of tying AI’s influence to sales. 

AI search makes it more difficult for brands to measure how LLMs influence consumer purchases, because impressions, clicks and referral data aren’t always available when an AI assistant guides consumers from product discovery to purchase decisions. And even when an AI recommendation does lead to a sale, those conversions can be incorrectly attributed to search, direct traffic, or other channels, according to the IAB’s report.

That attribution gap can distort marketing investment decisions, with spend going to channels that capture conversions rather than those that influenced them. Similarweb data cited in IAB’s report found consumers who received a brand recommendation from an AI assistant are 2.5 times more likely to visit that brand’s website within seven days, but only 8.8% of those visits come directly from AI referrals. Instead, 55.9% are attributed to search and 19.9% to direct traffic.

The IAB framework focuses on three areas. It classifies who or what created the intent, made the decision, and executed the transaction. It defines additional claims AI involvement creates, and the evidence each one requires. And it highlights the transparency and measurement gaps that make those claims difficult to verify. (More detail is available in the framework).

The clearest case of this gap is when publisher content is behind an AI recommendation, the IAB noted in its report. If a consumer asks an AI answer engine for the best option in a category, and the answer draws on a publisher’s review, the consumer may not click the citation (a link to the publisher’s review), and it gets reported as a search or direct sale by the retailer.

“The review shaped the sale, and the publisher is eligible for a contributory claim. The evidence differs depending on how publisher content informed the answer. Content used in model training is generally not traceable from outside the model. Grounding and citation are more observable: publishers may be able to see when their content is cited or reflected in an AI response, although citation alone does not establish how much that content influenced the answer. What remains largely missing is the connection between those sourcing signals and downstream conversions. Until that link exists, the contributory claim cannot be fully substantiated,” the IAB report reads.

The IAB’s recommendations span AI platforms, brands, agencies and publishers. Platforms should disclose whether recommendations are paid or organic, which sources inform them and label AI-originated traffic consistently.

Brands and agencies should apply the framework’s claim-and-evidence standards across platforms, while publishers should identify claims about their content’s influence and the evidence needed to support them, per the report.

“Publishers are feeding the answers but they don’t have the receipts,” said Jaime Schultheis, head of global data partnerships at Bombora, where she leads a network of B2B publishers, brand sites and data providers.

The IAB framework does accomplish defining the parts of the AI measurement journey, which can help publishers compare these between vendors and their different measurement structures, Jon Roberts, People Inc.’s chief innovation officer, said during the roundtable.

“Everyone’s pitching you on their custom proprietary measurement solution, and they’re all using the same terms, and the terms all mean something different because they’ve all designed these in a silo and are racing to get your business, and they’re all unique,” he said.

There are some signs that the measurement gap may narrow soon. The U.K.’s Competition and Markets Authority (CMA) is requiring Google to provide U.K. publishers with clickthrough data for its AI search features by Dec. 3. OpenAI is also testing an analytics dashboard that counts how often a business shows up in ChatGPT’s answers and how many clicks those appearances send to its site.

“We’re waiting [with] bated breath,” said Graham Howes, svp of distribution and AI intelligence at BDG, adding that this data from OpenAI and Google would be incredibly valuable for its GEO offering.

During the roundtable, Roberts noted that without this data, publishers are effectively “flying blind.” Sharing analytics benefits both publishers and AI platforms by helping them identify business opportunities, improve products and better serve their users, he said. Third-party measurement would still be important for independently verifying platforms’ own data, Roberts added. 

Brands want this measurement gap solved just as much as publishers. Ross Bucholc, associate media director at Prudential, said in the roundtable that the lack of first-party data from AI platforms is holding back his ability to unlock more ad budgets going to LLMs.

Even with better visibility into AI activity, connecting that activity to sales remains difficult. Josh Blyska, head of insights at Profound, told Digiday that existing attribution tools struggle to connect AI search’s influence on consumer purchase decisions to conversions. Platforms like Profound can measure AI visibility, citations and how brands appear in AI answers, but can’t reliably track whether those interactions lead to purchases.

In a recent analysis of browser-session data, Profound found one in three consumers had a relevant AI conversation about their purchase within a month that went unattributed, Blyska said. (The dataset didn’t include Google’s AI Mode or AI Overviews.)

“It’s a really tricky problem right now,” he said.

Ultimately, the challenge is not just measuring a brand’s visibility within AI platforms but proving that visibility drives business results. John Sills, head of sales, North America at The Guardian, said the industry needs a more consistent way to understand how AI patterns surface and answer questions. 

“We’re not measuring CTRs here. There’s no way of really understanding where the attribution is coming from,” he said. “These LLMs are in the ad business now… In the same way you can call your account manager at Facebook and try to optimize a social campaign or on YouTube, we need that level of account management to help guide the best practices.”

What we’ve heard

“We are capable, and AI companies are capable of reaching deals that give us fair compensation for content and referring to our site. Ninety-five percent of the AI referrals we get now come through OpenAI. So to me, that’s a win for them and a win for us if that’s how people want to access the news. So when people say deals like that aren’t possible or we don’t deserve compensation, I don’t really buy it.”

— Matt Murray, Washington Post executive editor, speaking about its deal with OpenAI, at Web Summit in Lisbon, Portugal.

Numbers to know

$330 million: The reported price under consideration for The New York Times Company’s potential acquisition of Letterboxd, an online community for film enthusiasts.

2.7 billion: The number of times Ziff Davis’ content was cited in Google’s AI Overviews and AI Mode in Q3, nearly 10 times the clicks from Google Search those sites received.

37%: Ziff Davis’ YOY decline in Google referrals.

44%: BuzzFeed’s total YOY revenue decline in Q3 2026.

4,000: The number of new subscribers The Washington Post gained over the course of the U.S. midterms election day and the following day, Semafor reported.

What we’ve covered

As publishers await click data, Google’s AI visibility push complicates the opt-out decision

• Google is introducing new controls that let publishers opt out of having their content used in AI search features, following pressure from the U.K.’s Competition and Markets Authority. 
• But publishers are hesitant to use them without AI-specific click data showing how much traffic Google’s AI features actually send to their sites. Google is required to provide that data to U.K. publishers by Dec. 3. Google is also making publisher links more prominent in AI Overviews and AI Mode, potentially making opting out less appealing. 

Read more here.

WTF is the AI training opt-out policy token?

• Anthropic, Google, Microsoft and OpenAI have agreed to support a proposed AI training “policy token” that would let publishers opt out of having their content used to train AI models through a few lines of text in their robots.txt files. 
• The mechanism aims to simplify how publishers express their preferences to multiple AI companies at once, but it has yet to become an official internet standard. The proposal also offers no way to enforce compliance, raising doubts about its effectiveness. 

Read more here.

ChatGPT is about to show brands their mention count

• OpenAI is testing an analytics dashboard that would let businesses track how often they appear in ChatGPT’s responses and how many clicks those appearances drive to their websites. 
• While the dashboard would provide brands with first-party visibility data, it wouldn’t reveal individual prompts, user data or competitor rankings, leaving room for third-party GEO measurement companies.

Read more here.

Creators see promise in Instagram’s long-form push, but question whether exposure is enough 

• Instagram is allowing creators to post videos up to 90 minutes long, in a bid to compete with YouTube for long-form content. 
• While the platform is reportedly offering select creators between $50,000 and $500,000 to participate, it has yet to establish a broader monetization model, leaving creators questioning whether increased exposure alone is enough to justify producing original content.

Read more here.

By the numbers: Ad tech’s widening divide, as AppLovin surges and rivals struggle in Q3

• Third-quarter earnings from six publicly traded ad tech companies revealed a widening gap between winners and losers. AppLovin’s revenue surged 55% year over year to $2.19 billion, exceeding the combined revenue of the other five companies, while Unity grew 32% and Magnite rose 14%. 
• Meanwhile, Criteo, Taboola and Teads reported revenue declines of 11%, 6.9% and 26%, respectively, highlighting the growing divide between mobile advertising platforms and companies more exposed to the open web.

Read more here.

What we’re reading

Meta pauses terms of service change

Meta indefinitely paused controversial changes to its terms of service that would have allowed it to scrape publishers’ websites, following widespread backlash from news organizations, legal challenges and regulatory scrutiny, Nieman Lab reported.

Yahoo expands AI search engine Scout

Yahoo is overhauling its search engine with Scout, an AI-powered experience that blends traditional search results with conversational answers. It’s expanding Scout across Yahoo News, Finance, Sports and other services to compete with Google and other AI search platforms, Fast Company reported.

ONA pauses events business citing costs and shrinking sponsorships

The Online News Association is canceling its 2027 annual conference and pausing all in-person events amid mounting financial pressures, rising event costs and shrinking sponsorship budgets. Its longtime staff are set to depart this month as the organization restructures, A Media Operator reported.

Press Forward invests nearly $600 million in news orgs

Press Forward, a philanthropic initiative supporting local journalism, has invested nearly $600 million in news organizations two years ahead of schedule and plans to expand its funding, the AP reported.

Anthropic and AP strike content licensing deal

Anthropic struck its first content licensing deal with a news publisher, the Associated Press, to provide real-time election data in Claude during the U.S. midterms, signaling a potential shift in the AI company’s longstanding reluctance to pay publishers for their content, Adweek reported.

— Jessica Davies contributed to this briefing.