How AI Is Changing the Business of Data and Measurement
Because so far, measurement of attribution, incrementality and return on investment have not been reliable, billions of marketing dollars have been mis-allocated, new IAB report says
The huge amount of data available to marketers appears to be a double-edged sword.
While a big majority of buyers have adopted various forms of advanced measurement using the data available, most have discovered major shortcomings as they attempt to plug the data into their marketing mix models, according to the IAB’s new State of Data 2026 report, which was released at the group's annual leadership meeting this week.
Because so far, measurement of attribution, incrementality and return on investment have not been reliable, billions of marketing dollars have been mis-allocated, and time is being wasted stitching data together instead of generating insights.
“Advanced measurement is falling short on its core promises, while the cost of failure had never been higher,” the report says.
The report is built around a survey of brand decision makers conducted with BWG Global.
The survey found that about 75% of decision makers said today’s leading advanced measurement approaches underperform in terms of rigor, timeliness, trust and efficiency.
None of the respondents said they believed all paid media channels are well represented today in the systems they use to make decisions. That includes traditional media, with 38% saying that linear TV, broadcast and cable, are not well represented in their measurement systems.
Of course, artificial intelligence has the potential to change that.
“AI can unify data, automate analysis, and increase measurement speed and frequency—but without transparency, governance, and data quality, it risks reinforcing black-box decisioning,” the report said. “Many marketers struggle to distinguish where AI delivers value today, what's achievable in 1-2 years, and what may be a mirage.”
That said, the media buyers surveyed said they believe AI can improve measurement materially within two years.
AI can enable marketers to run models two to three times more often than they do today. That improvement would have a huge impact. They said they can see AI-powered measurement enabling them to increase spending on some channels by $26.3 billion dollars, some from shifting the way money is allocated currently and some from incremental spending.
The adoption of AI is well underway. About half of those surveyed say their measurement systems already have scaled the usage of AI. Among those that have not, about 70% expect to do so within one to two years.
Analytics teams are leading adoption, the report said. This reflects their extensive machine learning background, technical fluency and ability to implement AI capabilities independently.
Just 6% of those surveyed said they do not plan to or are unsure about scaling up their AI usage.
“One of the most important things the report reveals is AI’s potential for improving measurement. But there are major concerns related to legal and security risks, accuracy, and data quality. We need to tackle problems that are systemic and foundational,” added Angelina Eng, VP, Measurement Center, IAB. “Past workarounds and band-aid approaches have allowed the underlying issues to become worse over time.”
The survey found concerns with pushing chips into the AI pot.
About half of those responding said challenges for AI-driven measurement include legal and security risks, accuracy and data quality.
Marketers have only slowly started to address those challenges. Less than 40% report having or planning to put solutions in place to mitigate these issues.
Some are putting AI-related clauses into their measurement contracts to try to minimize their risk. “The industry is at a breaking point: measurement systems are strained, data is fragmented, and AI adoption is accelerating faster than governance, readiness, and standards,” the report said.
To prepare for the way that AI will transform measurement, the report makes five recommendations that marketers should adopt sooner rather than later.
- Strengthen data quality, accessibility and governance.
- Standardize measurement frameworks for rigor and trust.
- Modernize operations to increase speed, frequency and scale.
- Expand measurement coverage across the full media mix.
- Adopt AI responsibly with clear ownership and guardrails.
The IAB, working with BWG, said it surveyed more than 400 senior planning and analytics decision makers at U.S. brands and agencies.
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The IAB proposed its own solution to the issues facing measurement, Project Eidos, which it called a coordinated, industry-wide effort to modernize advertising and marketing measurement.
“While advanced measurement is widely used across the industry, it’s still falling short of its core promise. The time for a single-channel fix or a one-off framework has passed,” said David Cohen, CEO, IAB. “It’s time to address the foundational issues that have quietly undermined measurement for years.”
Project Eidos aims to replace the patchwork of measurement solutions with an interoperable approach based on shared constructs and consistent language that deliver scalable, privacy-resilient measurement across all channels, including clear standards for Marketing Mix Modeling.
The Association of National Advertisers has also been trying to address cross-media measurement with its Aquila project.
"To create great consumer advertising experiences that deliver business outcomes and drive sustainable growth, we must deliver interoperability, transparency, and accountability. IAB's Project Eidos is the kind of coordinated industry effort needed to rebuild confidence in how advertising performance is measured,” said Shenan Reed, global chief media officer at General Motors.
Eidos takes its name from the Greek verb “to see,” the IAB said.
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At the IAB’s meeting on Sunday, NBCUniversal’s Alison Levin was appointed chair of the IAB Board of Directors for 2026, while Alan Moss of Amazon Ads was announced as vice chair.
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