The Biggest Barrier to AI Isn't Technology—It's Standards - TVREV

The Biggest Barrier to AI Isn't Technology—It's Standards

The advertising industry has spent the past year debating how AI will transform media planning, buying, and measurement. But before autonomous agents can seamlessly negotiate campaigns across buyers, sellers, and platforms, Jon Watts believes the industry has a far more fundamental problem to solve.

In this episode of AI and Outcomes in partnership with OpenAP, we sat down with Watts, Managing Director of CIMM,to talk about how he spends his time helping the television ecosystem tackle some of its most complex measurement challenges.

This interview has been edited for length and clarity.

TVREV: Before AI can truly transform the industry, what foundational capabilities still need to be in place?

Jon Watts: The technology itself isn't the hard part. What's difficult is getting an entire industry to agree on common standards.

If we imagine a future where AI agents are planning and buying campaigns across multiple publishers, platforms and data providers, everyone has to be speaking the same language. That means shared protocols, standardized definitions and common semantic structures that allow different systems to communicate with one another.

Without those standards, AI just creates faster confusion instead of faster collaboration.

TVREV: Standards are one challenge. You also spend a lot of time thinking about data quality. Why is that important?

Jon Watts: Because AI can only make decisions based on the information it receives. One of the projects CIMM worked on with Truthset looked at IP-to-household matching across multiple identity providers. What we found was eye-opening: Across a portfolio of providers, average accuracy was only around 13%.

For marketers trying to reach highly specific audiences, that's a major issue. If AI doesn't understand which data is trustworthy and which isn't, it may optimize campaigns around fundamentally flawed assumptions.

Improving data quality isn't just a measurement issue anymore. It's becoming an AI issue.

TVREV: The industry has shifted dramatically toward business outcomes. How is CIMM approaching that conversation?

Jon Watts: I think it's a very healthy shift. At the end of the day, advertisers don't buy media because they want impressions. They buy media because they want business results—sales, awareness, consideration or whatever success looks like for their organization.

The challenge is that today's ecosystem still struggles to consistently connect exposures to outcomes. Unlike closed platforms with complete commerce data, television often involves much longer and more complicated customer journeys.

Take automotive as an example. Someone might see advertising for months before they eventually purchase a vehicle. How should we attribute those exposures? How long should they remain part of the measurement window? The industry still hasn't standardized those answers, and that's exactly the work we're focused on.

TVREV: Where do you think AI can have the greatest impact once those standards exist?

Jon Watts: AI has the potential to simplify an incredibly complex ecosystem. But simplification only works if everyone is working from the same underlying framework. Once we have standardized protocols, consistent measurement methodologies and transparent data quality signals, AI can become incredibly effective at helping buyers and sellers transact more efficiently.

The technology is ready, the ecosystem is still catching up.

TVREV: Finish this sentence: The future of advertising belongs to those who...

Jon Watts: "...understand their data and can consistently connect advertising exposure to business outcomes."

Ultimately, that's where the industry is heading. The companies that can confidently link media investment to measurable business impact—and do so transparently—will be the ones creating the most value for advertisers.