Display Technology

Smarter screens start behind the scenes

How AI is turning digital signage and DOOH into coordinated retail intelligence.

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June 10, 2026 by Erin Lutenski — Head of Marketing, Decentriq

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Walk through most retail environments today and you'll see screens everywhere: above checkout lanes, at the end of aisles, in fitting rooms, in parking structures. Many of those screens are running content, but fewer of them are actually "thinking."

That's changing, and AI is the reason why. But the transformation isn't primarily about the displays themselves. It's about what's happening behind them, and whether the data infrastructure supporting them is sophisticated enough to keep up with what AI now makes possible.

From broadcast to intelligence

For most of its history, digital signage operated like a smarter version of a static poster. Content was scheduled, played in a loop, and swapped out when the campaign changed. DOOH networks sold on reach and frequency. The screen was a delivery mechanism as opposed to a decision-making system.

AI is rewriting that logic. Platforms today can analyze foot traffic patterns, time of day, local weather, and audience composition data in real time. Then, they can use those signals to determine not just what plays, but when, where, and for how long. A grocery chain can surface a hot soup promotion when temperatures drop outside. A pharmacy network can prioritize health messaging on Monday mornings when customers are more likely to be thinking about the week ahead.

For the shopper, this translates to a frictionless, highly relevant in-store experience. Instead of being bombarded by generic ads or promotions for items that are out-of-stock, the screens adapt dynamically, showing real-time context that actually matches their localized journey.

Ströer, a German out-of-home operator, reported 36% growth in programmatic DOOH revenue in Q1 2025 and attributed it directly to their AI-powered playout infrastructure: an in-house system that continuously optimizes campaign delivery based on audience and contextual signals.

Data remains the bottleneck to successfully implemented AI

Here's what becomes clear when you look closely at how these systems actually work: the AI is only as good as the data it can access. And in retail media and DOOH, that data is almost always fragmented.

A digital signage network knows about its screens: impressions, locations, dwell times. A retailer knows about its customers: purchase history, loyalty behavior, category affinities. An advertiser knows about campaign performance in digital channels. These are three different data universes, and in most cases, none of them can see the others.

That fragmentation has real consequences. When AI systems are planning and optimizing in real time, they need continuous, high-quality signals. Stale data or mismatched audience definitions produce poor targeting decisions, which produce poor results, and these then erode advertiser confidence in the channel. The IAB has identified lack of data standardization as one of the primary inhibitors of programmatic DOOH growth (and that was true even before AI raised the bar on what good data actually means).

Retail intelligence requires collaboration

What's emerging, and what I think represents the real opportunity here, is a shift from thinking about signage as a media channel to thinking about it as a node in a retail intelligence system. But that system only works if the parties involved can actually collaborate across their respective data environments.

By leveraging privacy-preserving environments like data clean rooms, consider what becomes possible when a retailer's first-party loyalty data can be used — securely, without anyone handing over raw files — to inform which audiences are being reached by in-store screens. Suddenly, campaign planning isn't based on modeled estimates of who walked past a display. It's based on verified purchase behavior, household demographics, and category intent signals that the retailer already has. Measurement becomes a closed loop: exposure connects to transaction, and attribution has real grounding.

Major retail media networks are moving in this direction, and the economics are compelling. US retail media spending is projected to reach $100 billion by 2028. The networks capturing a meaningful share of that figure are the ones that can offer advertisers a combination of first-party audience data, on-site and off-site inventory (including physical screens) and closed-loop measurement. Digital signage is part of that value proposition, but only when the data infrastructure connects it to the rest.

The infrastructure is the strategy

For retailers operating or considering in-store signage networks, the main strategic question shouldn't just be about the hardware. Instead, it should be about what data those screens can generate, what data they can consume, and how securely that data can be shared with advertising partners.

Achieving true retail intelligence means moving away from legacy setups and focusing on three core operational pillars:

• Investing in modern data frameworks: Prioritize the data infrastructure and pipelines that make first-party data securely usable across external partners without risking data privacy.
• Moving toward standardized measurement: Adopt unified audience measurement methodologies that allow performance to be compared apples-to-apples across different networks and channels.
• Closing the gaps honestly: Be transparent about where your measurement story has blind spots.

AI-powered buyers are going to find those gaps faster than human media planners ever did.

The screens are getting smarter. The real work for retail executives today is making the ecosystem around them smart enough to match.

About Erin Lutenski

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