AI is changing local TV advertising, but who holds the best data still decides who wins

Jul 6, 2026

The window for AI to serve as a true competitive differentiator will be short. What remains is the thing AI runs on: data. Specifically, the kind of proprietary, market-level data that can’t be licensed, averaged, or approximated. The question for marketers isn’t which AI to use. It’s whether your partner has the data to make it work.

“As AI adoption accelerates, proprietary data, not proprietary technology, will become the true source of value. AI is leveling the technology playing field, and it’s only going to level it further,” said Michael Collins, Chief Executive Officer of Locality, a local TV advertising platform built for the converging world of broadcast and streaming.

Effective TV campaigns depend on a connected end-to-end dataset by which AI models can continually enhance planning, targeting and measurement throughout the campaign lifecycle.

Why national data falls short in local TV

Many platforms still attempt to retrofit national solutions for local campaigns. This doesn’t work because national campaigns offer standardized datasets that lack sufficient market granularity.

“Generic AI tends to give you a statistically correct answer, whereas local intelligence gives you the contextually correct answer for that market,” said Locality Chief Technology Officer, Kouros Esfahany.

As consumers generate more digital signals, marketers have access to a richer picture of local behavior than ever before. This includes identity data from both households and devices, cross-platform media exposure data, campaign outcome data such as conversions and sales, and market context, including DMA, local behavior and historical performance. When unified into a single intelligence layer rather than fragmented across different tools, this becomes data AI can optimize for real business outcomes, not just impressions or proxy metrics. When AI models are trained on national averages, they rarely fail visibly. They optimize confidently toward the wrong outcome.

Each DMA, zip code and neighborhood exhibits its own distinct behavior. When AI models are trained on market-level exposure, performance and behavioral data, they can detect differences in engagement across channels at each level. The key is not just identifying these variations but translating them into different models or media strategies that matter for that particular area. When marketers use location data reflecting what’s happening around the target consumer, they get a powerful, far more personalized signal.

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