AI won't replace OOH creatives in 2026—it will finally set them free

Artificial intelligence in out-of-home advertising will drive a creative renaissance in 2026, but not through the automated content generation dominating other digital channels. Shawn Spooner, Global Chief Technology Officer at billups, outlined on December 10, 2025, a prediction that contradicts conventional assumptions about AI's role in advertising creative development.

The industry has spent a decade transforming out-of-home into a programmatic, data-driven medium. Programmatic digital out-of-home expanded rapidly throughout 2025, with technology providers like Broadsign acquiring supply-side platforms to reach 1.8 million screens globally. This infrastructure buildout succeeded in creating opportunities and inventory for targeted advertisements. However, creative development failed to keep pace with targeting sophistication.

"The industry has spent a decade making out-of-home 'programmatic' and 'data-driven,' which has been great for creating more opportunities and screens for targeted ads, but not necessarily great for creative," Spooner stated in materials distributed December 10. The assessment identifies a fundamental imbalance between technical capabilities and creative execution that has characterized digital out-of-home's transformation.

AI hype throughout 2025 concentrated on other digital advertising channels. Google launched Asset Studio in September, enabling advertisers to generate and edit media assets directly within Google Ads using Imagen 4 for image creation and Veo for video generation. Meta expanded AI creative tools with more than one million advertisers creating over 15 million ads monthly using generative AI capabilities. Meta CEO Mark Zuckerberg articulated in May 2025 a vision where businesses "don't need any creative, you don't need any targeting demographic" because Meta's AI would handle everything automatically.

Spooner's prediction diverges sharply from this automation narrative. "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," he explained. The distinction proves critical—AI serves as operational infrastructure rather than creative replacement.

Manual, repetitive aspects of out-of-home campaign planning will become optimized through AI systems. The wealth of signals and data points involved in planning, iteration, and placement will inform better creative execution rather than replacing human creative judgment. This approach addresses what advertising technology platforms have struggled to solve: maintaining creative quality while scaling automated distribution.

The contextual testing capabilities Spooner described represent the most significant advancement AI brings to out-of-home creative development. "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," he stated. "That's not just testing, it's understanding context at a level human teams never could at scale."

Traditional A/B testing methodologies require live campaigns to gather performance data. Creative teams produce variations, deploy them across inventory, wait for statistically significant results, then iterate. The process consumes weeks or months while budgets fund suboptimal creative during testing phases. AI-powered simulation eliminates this inefficiency by modeling creative performance across environmental conditions before media spend begins.

Spooner holds 12 artificial intelligence and machine learning patents. His background includes cofounding eHealth Innovations and leading research into human-in-the-loop computing systems. At billups, he built a research team exploring deep learning and artificial intelligence applications specifically for out-of-home media planning. The prediction draws on direct experience implementing AI systems in out-of-home environments where technical constraints differ substantially from online advertising platforms.

Out-of-home advertising delivers $7.58 marginal return on investment per incremental dollar, according to research from Keen Decision Systems and Accretive released October 24, 2025. This performance exceeds the average media type marginal ROI of $5.52 and surpasses print, radio, and linear television. Despite these results, OOH accounts for less than 1% of all media spending. The underinvestment reflects historical measurement challenges and creative production limitations that AI-powered optimization could address.

Digital out-of-home represents 41% of the $52 billion OOH market in 2025, according to WPP Media forecasts. The format is expected to reach $31.4 billion by 2030, effectively achieving parity with traditional outdoor formats. Programmatic capabilities enabled this growth trajectory, but creative quality constraints prevent OOH from capturing larger budget shares.

The prediction arrives as platforms across digital advertising implement AI creative automation with mixed results. Innovid launched neural-network optimization systems in August 2025 that process engagement metrics, conversion data, and contextual information for real-time creative selection. Smartly introduced Creative Predictive Potential in November 2025, using computer vision and eye-tracking models to evaluate visual attention patterns before campaigns launch. These tools address creative performance prediction but operate within online advertising's fundamentally different context.

Out-of-home advertising faces unique environmental variables that online channels rarely encounter. Weather conditions, ambient light levels, pedestrian versus vehicular traffic, time of day, and viewing distances all influence creative effectiveness. A billboard creative optimized for evening commuters in clear weather may fail completely during morning rush hour in rain. Digital advertising platforms control most environmental variables through screen standardization and indoor viewing conditions.

Spooner's contextual simulation concept addresses this complexity by modeling performance across the full range of environmental conditions OOH inventory experiences. The system would identify which creative executions work best in specific combinations of time, weather, traffic patterns, and viewing contexts. Creative teams gain actionable intelligence about creative placement strategy rather than generic performance averages across all conditions.

The approach contrasts sharply with AI creative generation tools dominating other channels. Adobe's GenStudio generates content variations aligned with brand guidelines and channel specifications, reducing go-to-market time by up to 70% according to company data. Google's Nano Banana Pro enables advertisers to produce diverse creative materials at velocities manual production cannot sustain. Meta's Advantage+ creative features generated a 22% increase in return on ad spend for advertisers who activated them.

These platforms automate creative production itself. Spooner's vision keeps creative development firmly in human hands while using AI to optimize the strategic deployment of that creativity. The distinction reflects out-of-home's different operational requirements compared to online advertising where rapid creative iteration and programmatic buying occur in milliseconds.

Industry skepticism about AI creative automation has intensified throughout 2025. Digital marketing specialists challenged Meta's campaign consolidation approaches, warning that "reach expands, but impact doesn't follow" when combining broader audiences with more creative combinations. Attribution and incrementality concerns raise questions about whether AI systems create new demand or simply capture existing demand more efficiently.

Harvard Business School research identified five pitfalls specific to AI marketing automation: people blame AI first when failures occur, one AI failure erodes confidence in all AI systems, overstated AI capabilities generate disproportionate blame, humanized AI faces harsher judgment, and deceptive AI practices trigger outrage. These dynamics create risk for platforms promoting full creative automation.

Spooner's approach sidesteps these concerns by maintaining human creative control while automating operational tasks and providing decision support through contextual performance modeling. Creative teams retain responsibility for developing concepts, messaging, and visual execution. AI systems handle planning complexity and provide intelligence about contextual effectiveness that humans cannot generate manually.

The prediction aligns with broader industry trends around AI positioning. Google emphasized during its 25th anniversarythat automation "does not mean ceding responsibility to algorithms" but rather shifting focus "to providing the business-informed guidance and data foundation that AI systems need to succeed." This framing positions AI as enabling technology rather than replacement technology.

Out-of-home's structural characteristics make it particularly suitable for this AI augmentation approach. Creative assets require significant production investment compared to digital banner ads. A billboard design undergoes multiple rounds of stakeholder review and approval before production. The high stakes favor careful human creative judgment augmented by comprehensive performance intelligence rather than rapid automated generation and iteration.

Physical presence in public spaces also demands higher creative standards than online environments where advertisements blend into continuous scrolling. An ineffective billboard occupies premium real estate and represents wasted investment. An ineffective display ad simply gets replaced in the next impression auction. This asymmetry rewards contextual optimization intelligence that helps creative teams deploy the right creative in the right environmental conditions.

The technological infrastructure required for contextual simulation exists within current capabilities. Machine learning models can process historical performance data across environmental variables, weather conditions, traffic patterns, and time periods. Computer vision systems can analyze creative elements and predict attention patterns. The combination enables modeling creative performance across scenarios without requiring live testing.

billups operates globally with infrastructure for analyzing out-of-home advertising performance across diverse markets and inventory types. The company's research team explores deep learning applications specifically for media planning optimization. This operational foundation provides the data and technical capabilities necessary to implement the contextual simulation systems Spooner described.

Recent OOH technology developments demonstrate momentum toward sophisticated automation. Broadsign introduced programmatic guaranteed buying capabilities in November 2025, enabling advertisers to reserve premium inventory months ahead through automated infrastructure. VIOOH expanded programmatic access to over 65,000 screens across the United States generating 13 billion monthly impressions. These platforms handle transaction automation, creating foundation for creative optimization layers.

Programmatic digital out-of-home adoption reached 30% in China according to VIOOH's August 2025 research. Chinese advertisers demonstrated heightened focus on measurable performance outcomes, with emphasis on sales increases exceeding global averages by nearly 20 percentage points. The data indicates demand for accountability and optimization that contextual creative intelligence could address.

The prediction carries implications for creative agencies serving out-of-home clients. Rather than facing disintermediation from AI creative generators as online agencies confront, OOH creative agencies gain sophisticated intelligence tools that elevate their strategic value. Understanding which creative executions work best across environmental contexts becomes competitive advantage rather than operational burden.

Marketing professionals planning out-of-home campaigns would benefit from AI systems that simulate creative performance across conditions before committing media budgets. The ability to test creative strategy virtually eliminates expensive real-world testing phases while improving campaign effectiveness. This capability matters particularly for brands allocating budgets across channels where OOH's historical measurement challenges have hindered investment justification.

The 2026 timeline Spooner specified suggests implementation readiness rather than distant future speculation. Current AI infrastructure, available data, and established programmatic platforms provide the technical foundation. The prediction requires synthesis of existing capabilities rather than technological breakthroughs. Industry adoption patterns determine whether 2026 proves accurate or optimistic.

Out-of-home advertising maintained stable market share better than any other traditional advertising format over the past 20 years, according to WPP analysis. The resilience reflects advantages in reach, attention, and contextual relevance that digital channels struggle to replicate. AI-enhanced creative optimization could accelerate growth by addressing the creative production constraints that have limited OOH's budget capture despite superior return on investment metrics.

The prediction reframes AI's role in advertising from creative replacement to creative liberation. By automating planning complexity and providing contextual performance intelligence, AI systems enable creative teams to focus on strategic creative development rather than operational execution. This positioning avoids the attribution uncertainties and quality concerns plaguing generative AI creative tools while delivering measurable operational improvements.

Whether the renaissance Spooner predicts materializes in 2026 depends on technology provider execution, advertiser adoption, and creative agency adaptation. The conceptual framework addresses real operational challenges while respecting out-of-home's structural requirements for high-quality creative assets. Success would validate an alternative AI integration path focused on augmentation rather than automation.

Timeline

• December 2024: Out-of-home advertising achieves $7.58 marginal ROI, outperforming digital channels despite accounting for less than 1% of media budgets
• May 2025: Mark Zuckerberg outlines vision to replace creative agencies with Meta AI handling all creative production automatically
• August 2025: China's programmatic DOOH adoption reaches 30%, demonstrating growing demand for data-driven outdoor advertising
• August 2025: Innovid launches AI-powered creative optimization tools using neural networks for real-time campaign adjustments
• September 2025: Google launches Asset Studio with Imagen 4 and Veo capabilities for automated creative generation
• October 2025: Google Ads marks 25 years with shift from manual optimization to comprehensive AI automation
• November 2025: Broadsign enables advance DOOH booking through StackAdapt partnership, introducing programmatic guaranteed capabilities
• November 2025: Smartly adds AI creative predictive tools using computer vision to evaluate attention patterns before campaigns launch
• November 2025: Broadsign acquires Place Exchange, expanding programmatic reach to 1.8 million screens globally
• December 2025: Global advertising spending hits $1.14 trillion with digital out-of-home projected to reach $31.4 billion by 2030
• December 10, 2025: Shawn Spooner predicts AI will enhance OOH creative by automating planning tasks and enabling contextual simulation at scale

Summary

Who: Shawn Spooner, Global Chief Technology Officer at billups, a technology executive with 12 AI/ML patents and expertise in human-in-the-loop computing systems designed for out-of-home advertising optimization.

What: A 2026 prediction that artificial intelligence will drive an out-of-home advertising creative renaissance not through automated content generation but by freeing creative teams from manual planning and optimization tasks while enabling contextual performance simulation across environmental conditions including weather, lighting, traffic patterns, and viewing contexts that human teams cannot test at scale.

When: The prediction was distributed December 10, 2025, with implementation expected throughout 2026 as AI systems become capable of simulating creative performance across conditions before media spend begins.

Where: The prediction applies to the global out-of-home advertising industry, which represents a $52 billion market in 2025 with digital out-of-home comprising 41% of total revenue and programmatic capabilities expanding across major markets including North America, Europe, China, and Latin America through platforms like Broadsign, VIOOH, and regional media owners.

Why: Out-of-home advertising spent a decade becoming programmatic and data-driven, scaling targeting capabilities faster than creative development, creating an imbalance where sophisticated distribution infrastructure lacks equally sophisticated creative optimization. AI addresses this gap by automating operational tasks, providing contextual intelligence about creative effectiveness across environmental variables, and enabling creative teams to understand which creative executions belong in specific conditions rather than testing at scale with live budgets.