The out-of-home advertising industry has arrived at a critical juncture, with the powerful force of artificial intelligence standing ready to completely redefine its long-established creative landscape. A compelling vision, articulated by Shawn Spooner, Global Chief Technology Officer at the advertising technology firm billups, projects that by 2026, AI will not usurp the role of human creatives but will instead act as the primary catalyst for a widespread creative renaissance. This perspective presents a significant departure from the prevailing narrative of full creative automation that has come to dominate discussions in other digital marketing channels. The central thesis suggests a collaborative future where AI functions as a powerful augmentation tool, liberating creative professionals from immense operational burdens and equipping them with unprecedented contextual intelligence. This allows them to enhance, rather than cede, their strategic work, positioning AI not as the artist, but as the ultimate assistant that empowers human ingenuity to reach new heights.
The Widening Chasm Between Technology and Creativity
Over the last decade, the out-of-home sector has been consumed by a profound technological transformation, successfully evolving into a highly programmatic and data-driven medium. This extensive infrastructure buildout, highlighted by the rapid expansion of programmatic digital out-of-home (DOOH) in 2025 and strategic consolidations like Broadsign’s acquisition of supply-side platforms to amass a global network of 1.8 million screens, has been remarkably effective. It has created a vast and sophisticated inventory with advanced targeting opportunities that were unimaginable just a short time ago. The industry has effectively built a powerful engine for ad delivery, capable of reaching specific audiences at precise moments with unparalleled efficiency. This technical progress has fundamentally modernized the channel, making it more flexible, measurable, and integrated within the broader media ecosystem, laying a crucial foundation for its next evolutionary step.
However, this relentless focus on programmatic infrastructure has starkly outpaced the evolution of creative development and optimization, resulting in a critical and growing imbalance. As Spooner notes, the focus on building this technological backbone has not been “necessarily great for creative.” This has produced a perplexing paradox where advanced distribution capabilities are not matched by equally advanced creative strategies. The industry finds itself in a situation where it possesses a high-performance vehicle but is still learning how to fuel it with the most potent creative content. This gap has constrained the medium’s ability to capture a larger share of advertising budgets, despite its proven effectiveness. Research highlighted this disconnect in late 2025, revealing that OOH advertising delivers an impressive $7.58 marginal return on investment per incremental dollar—significantly higher than the media average of $5.52—yet it commands less than 1% of total media spending. AI-powered creative optimization is now presented as the essential key to bridging this gap and finally unlocking the medium’s full economic potential.
Charting a Course Different from Digital Titans
Throughout 2025, the narrative from mainstream digital advertising has been overwhelmingly focused on generative AI and the promise of complete automation. Technology giants like Meta and Google heavily promoted a vision where businesses would no longer require dedicated creative or targeting expertise, as the platform’s AI would handle all facets of campaign creation and execution. Meta’s CEO, Mark Zuckerberg, articulated a future where AI would seamlessly generate ad variations, write copy, and optimize placements, effectively disintermediating the traditional creative process. This vision saw significant adoption, with over one million advertisers using Meta’s generative AI tools to create more than 15 million ads monthly, reportedly leading to a 22% increase in return on ad spend for users of its Advantage+ features. Similarly, Google launched its Asset Studio, empowering advertisers to generate and edit media assets directly within Google Ads using advanced models like Imagen 4, further cementing the industry’s trajectory toward creative replacement.
In stark contrast, the predicted role of AI in OOH stands in direct opposition to this narrative of creative obsolescence. Spooner’s prediction for OOH clarifies this distinction, stating, “It won’t be because AI is doing the creative work, but because it is taking on the other work that is sapping the creative energy of the teams.” In this model, AI serves as an operational and strategic infrastructure, not a content creator. Its function is to automate the thousands of manual, repetitive tasks involved in planning, selecting, and placing OOH media across countless variables and locations. By shouldering this logistical weight, AI frees human talent from the drudgery of spreadsheets and complex scheduling, allowing them to redirect their focus toward high-level conceptual work, big-picture strategy, and the kind of resonant storytelling that forges genuine connections with audiences. This positions AI as an enabler of human creativity, not a substitute for it, marking a fundamentally different philosophical approach to its integration.
The Transformative Potential of Contextual Simulation
The most significant and transformative element of this vision is the concept of AI-driven contextual simulation, which represents the core of how AI will empower OOH creatives. Traditional creative testing in the out-of-home space is a notoriously cumbersome, expensive, and inefficient process. It requires creative teams to produce multiple ad variations, deploy them in live campaigns across different markets, and then wait for weeks or even months to gather enough performance data to make informed decisions. This entire process consumes significant budget on what often amounts to educated guesswork, with a high potential for spending on suboptimal creative while better-performing alternatives sit on the shelf. The logistical complexity and high cost of this method have historically limited the scope of testing, preventing a truly granular understanding of which creative works best and, more importantly, why.
The new paradigm outlined by Spooner leverages AI to model and simulate creative performance across a vast spectrum of environmental and contextual variables before any media spend is committed. This capability moves far beyond simple A/B testing into the realm of predictive intelligence. He paints a vivid picture of this future: “Imagine AI giving you contextual signals that simulate how your ad performs by the light of a morning commute versus in the evening, in the rain versus the sun, when people are walking versus when they’re driving.” This is not merely testing; it is achieving a profound understanding of context at a scale and depth that is humanly impossible to replicate. This “pre-flight intelligence” would allow creative teams to know which specific execution will be most effective in a precise combination of time, weather, traffic patterns, and viewing context, enabling a far more strategic, efficient, and impactful deployment of creative assets across a diverse DOOH network.
A Tailor Made Solution for a Unique Medium
The unique structural characteristics of the out-of-home medium make it particularly well-suited for an AI augmentation model rather than one of full automation. Unlike online advertising, which occurs in the controlled and standardized environment of a digital screen, OOH advertising is subject to a host of uncontrollable real-world variables. Factors such as dynamic weather conditions, shifting ambient light levels from day to night, the nature of the audience (pedestrians versus fast-moving vehicle traffic), and varying viewing distances all dramatically influence the effectiveness of a creative. A design that is visually compelling on a clear, bright afternoon may become illegible during a rainy morning rush hour or nearly invisible on a poorly lit street at night. The contextual simulation capability directly addresses this inherent complexity by providing the intelligence needed to match the right creative to the right conditions, ensuring optimal impact at all times.
Furthermore, the stakes in OOH advertising are considerably higher than in its digital counterparts. The production of OOH assets, such as a major billboard design or a full-motion digital video, represents a significant financial and creative investment that typically undergoes multiple rounds of stakeholder approval. Its physical presence in public spaces means that an ineffective creative is not just a wasted impression, as it might be online, but a prominent and costly failure occupying premium real estate. This high-stakes environment naturally favors a model that uses AI to de-risk investment and maximize impact through sophisticated intelligence, rather than one that relies on the rapid, low-cost generation and iteration of automated creative. This approach also cleverly sidesteps the growing industry skepticism surrounding full AI automation, which has been hampered by pitfalls such as the erosion of trust from single negative experiences. By keeping human creatives firmly in control of the final output, Spooner’s model maintains human accountability while leveraging AI for powerful decision support.
The Dawn of a New Creative Era
The technological foundation required to realize this vision is already being established, making the 2026 timeline both plausible and realistic. Existing machine learning models are already capable of processing vast amounts of historical performance data and correlating it with environmental variables like weather and traffic. At the same time, advanced computer vision systems can analyze creative elements—such as color contrast, font size, and object placement—to predict attention patterns and viewability in different contexts. The maturation of programmatic OOH platforms, such as those operated by Broadsign and VIOOH, has already automated the complex transactional layer of media buying. This automation has created a solid foundation upon which a sophisticated creative optimization layer can now be built, turning the promise of contextual intelligence into an operational reality for advertisers and agencies.
The implications of this shift were profound. For creative agencies, it represented an opportunity not for disintermediation, but for an elevation of their strategic value, transforming them from simple content producers into indispensable partners armed with powerful predictive insights. The ability to leverage contextual intelligence became a powerful competitive advantage. For marketers, it offered a clear path to eliminating expensive and inefficient testing phases, dramatically improving campaign effectiveness, and building a stronger, data-backed business case for increasing investment in the high-performing OOH channel. Ultimately, the prediction reframed the role of AI in advertising from one of creative replacement to one of creative liberation. By handling the immense complexity of planning and providing deep contextual performance intelligence, AI enabled creative teams to focus their energy on developing more strategic, impactful, and resonant advertising, ushering in the creative renaissance that the industry had long awaited.
