IAB's new AI marketing standards

Advertising trade group IAB is helping build the measurement infrastructure for AI marketing.

Yesterday, Caroline Giegerich, IAB’s VP of AI & Marketing Innovation, announced the IAB’s “Measuring Visibility in the AI Era” framework, which addresses both advertiser and publisher interests.

Download the framework (August 3) – IAB (PDF)

Emphasizing that the IAB is not creating a measurement product, Giegerich said on LinkedIn that the framework begins with the “4 P’s”:

Presence: Are you mentioned?
Prominence: Where do you appear?
Portrayal: Is the model describing you positively or negatively?
Persuasion: Does it actually influence behavior?

Additional framework elements include:

“Directional vs. Decision-Grade Measurement: Is the data useful for watching a trend OR rigorous enough to inform budget and strategy?”
“Provider Disclosure Standards: What measurement companies should disclose about their platforms, prompts, data collection, methodology, and historical baselines.”

She adds, “IAB is not building a measurement product or rating the companies that do. We’re defining what good measurement looks like so that brands, publishers, agencies, and measurement providers can operate from common ground.”

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Developments

Alibaba unveils its largest AI model yet, DeepSeek’s latest model is ultra-low cost (August 3) – Reuters
White House to Host AI Companies on Tuesday to Review AI Framework (August 3) – The Information (subscription)
Visa to Buy Fraud Defense AI Platform BioCatch in $2.4 Billion Deal (August 3) – The Wall Street Journal (subscription)

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AI recommendations meet paid media

For marketers, AI optimization is becoming both an organic and a paid media discipline.

Ad Age’s Garett Sloane writes:

“At Japan Airlines, it’s getting more challenging to acquire new customers. Website traffic is down since AI search diverts consumers from direct visits. Also, the makeup of consumers who visit the site has changed—they are more loyal customers, arriving later in their research, already informed and further along toward a purchase decision, according to Minako Kent, VP of global brand marketing at Japan Airlines.”

Read: How Japan Airlines will track its new ChatGPT ad strategy (August 3) – Ad Age

The Brandtech Group’s Jellyfish is supporting Japan Airlines’ initiative through the agency’s new AI Ads Optimization product and Share of Model platform.

Jellyfish says the product “brings AI visibility and AI media optimization together, helping brands identify opportunities across AI platforms and turn those insights into smarter campaign optimization.” Read more on LinkedIn. (August 3)

More: “Jellyfish Launches AI Ads Optimization in Share of Model” (August 3) – Jellyfish

From tipsheet: Brands are beginning to optimize AI recommendation share with a combination of generative engine optimization and paid media informed by AI visibility. Jellyfish says its latest Share of Model update “extends beyond the existing Google Ads integration for Performance Max to generate media optimizations with AI insights for ChatGPT, TikTok, DV360, YouTube and Reddit.”

GEO startups like Profound (Ads Studio) and Evertune (ChatGPT Ads Manager) have also expanded into paid media, suggesting some AI optimization platforms are combining organic visibility and advertising.

To be clear: This isn’t just SEO + SEM. It’s a new marketing layer built around influencing how AI models understand, recommend and advertise brands. And that’s before ads for agents at scale enter the picture.

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AI agents create new curation opportunity

AI agents are beginning to give publishers a new way to activate and monetize first-party data.

AdExchanger’s Anthony Vargas reports that publishers are beginning to use agentic workflows to generate campaign-specific audience segments on demand, reducing the manual work traditionally handled by ad operations and sales teams.

One example is the integration between PubMatic and Optable, first announced in March, which connects publisher audience creation with buyer-side AI agents. Publishers are now beginning to put those capabilities to work.

Co-CEO Indy Khabra of gaming media company Livewire tells AdExchanger:

“A lot of the AI narrative is very much demand-oriented. But I think you’re going to see more conversations balancing the demand and the activation side with the supply side going forward. Speaking of demand, agentic approaches are helping publishers tap incremental revenue streams.”

Read: AI Agents Are Giving Publishers A New Way To Monetize Their Data (August 3) – AdExchanger

From tipsheet: AI agents let publisher data become responsive rather than static. Publishers can move beyond relying on prebuilt audience segments and generate campaign-specific audiences in response to buyer prompts, making first-party data easier for buyers to discover and for publishers to activate.

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OpenAI builds marketplace capabilities

OpenAI has added two new advertising roles that provide another window into how its ad business is evolving.

From the OpenAI Careers website:

Data Scientist, Ads Demand focuses on marketplace health. The role “will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace. You will partner closely with Ads Sales leadership and Ads Product leadership — along with Marketing Science and product and sales teams — to diagnose advertiser performance, define benchmarks, identify growth opportunities, and turn advertiser feedback into product priorities. Your work will shape demand strategy, improve advertiser outcomes, and help OpenAI build for its most valuable advertisers.” More.
Data Scientist, SMB Ads Growth listing says the role “will architect the analytics function end-to-end—driving strategy across targeting, funnel optimization, and performance forecasting. You will work directly with the SMB Ads Marketing team and your insights will be the primary catalyst for high-stakes decisions across marketing, product, and sales engineering.” So, no pressure. More.

From tipsheet: OpenAI is hiring around the economics of an advertising marketplace rather than simply the mechanics of selling ads. Together, these roles suggest the company is building the data science needed to run a marketplace at scale.

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eMarketer: How people use AI

From eMarketer analyst Nate Elliott on LinkedIn yesterday: “… our new eMarketer survey and framework doesn’t lead with platform or feature adoption. Instead, it leads with the human motivations that drive people to use AI in the first place”:

He concludes, “The pattern is clear: Problem solving and personal utility drive the vast majority of AI usage. Shiny technology might create trial, but human motivation drives lasting habits.”

IAB’s new AI marketing standards

LLMs & CHATBOTS

Developments

LLMs & CHATBOTS

AI recommendations meet paid media

SELL-SIDE

AI agents create new curation opportunity

LLMs & CHATBOTS

OpenAI builds marketplace capabilities

LLMs & CHATBOTS

eMarketer: How people use AI

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