AI commerce upends retail media as outcome-obsessed ad wars escalate

By early 2026, AI-driven agentic commerce powered by large language models (LLMs) is poised to fundamentally disrupt traditional retail media, which currently allocates over 75% of its investment to search-based advertising formats. This shift threatens to reroute consumer discovery and purchase journeys away from retailer sites, as LLMs facilitate direct conversions that bypass upper funnel touchpoints, thereby diminishing retailers' ability to capture valuable impressions and behavioral data. Kir Masters' illustration of a 'product detail page only retail journey' encapsulates this emerging paradigm, where discovery occurs entirely within AI environments, potentially undermining the dominance of search ads despite retail display advertising's continued double-digit growth in categories like alcoholic beverages and cosmetics.

The encroachment of AI shopping assistants is already prompting strategic defensive moves from major retailers such as Amazon, which has restricted AI platforms like Perplexity from accessing its inventory to protect on-site retail media revenues. This protective stance underscores the risk that fewer consumer visits to retailer sites could erode traditional retail media's revenue base. Meanwhile, mid-tier retail media platforms—exemplified by Etsy and eBay—face heightened vulnerability, with industry analysts predicting significant consolidation within this 'messy middle' segment throughout 2026 as advertising spend potentially migrates away from these networks.

Although AI-driven commerce advertising remains nascent, tech giants are actively integrating AI to reshape the advertising landscape. Google leads this charge by embedding AI modes and overviews into search ads, signaling a gradual but impactful evolution. The anticipated entry of OpenAI into advertising services promises to further disrupt ad revenue dynamics, though industry insiders caution that building advertiser relationships and robust technology infrastructure will require time, indicating a transformative but measured shift in retail media spend over the coming years.

By early 2026, the media measurement landscape is undergoing a profound transformation, shifting away from traditional exposure-based metrics like reach, frequency, and last-click attribution toward AI-enabled frameworks that directly link advertising efforts to tangible business outcomes such as app downloads and product purchases. Industry leaders including ITV's Sameer Modha and Kate Brinkley from The Specialist Works emphasize that this evolution is reshaping campaign planning and budget allocation, as brands increasingly prioritize outcome-driven insights over retrospective and often insufficient exposure data.

Despite the clear advantages of outcome-focused measurement, a significant cultural and practical divide persists within the marketing community. Many practitioners remain anchored to legacy metrics, creating a 'force of friction' that slows adoption, while a lack of hands-on experience with AI-powered media buying platforms—such as Google Ads’ outcome-oriented options like 'store visits' or 'online sales'—further hampers progress. As one industry voice lamented, few marketers have truly engaged with these tools, underscoring the need to move beyond preaching traditional brand measurement philosophies toward embracing and operationalizing AI-driven, business-impact-centric approaches.

AI is not only enabling a shift in what is measured but also accelerating how quickly insights are delivered, allowing media planners to receive near-real-time feedback linked directly to business outcomes rather than waiting months or years. This rapid feedback loop is a game-changer, as highlighted by experts who note that AI-driven models aggregate data across hundreds of brands—such as a shared dataset encompassing 600 brands over multiple years—to provide consistent, transparent, and scalable outcome measurement tools that planners can actively use for campaign optimization.

The industry is also recognizing the futility of old measurement debates, such as panel versus device-based methodologies, advocating instead for collaborative innovation focused on transparent, contribution-based frameworks that reflect the full customer journey. This call to action, exemplified by calls to 'measure better, not lecture harder,' signals a collective push toward a commons of large-scale, AI-powered models that transcend platform silos and deliver unified, outcome-driven insights essential for the future of retail media measurement.

By early 2026, the retail media landscape is witnessing a decisive shift toward integration and unification, as exemplified by The Trade Desk’s strategic embedding of its DSP within Skai and Pacvue platforms. This move allows advertisers to manage programmatic ads alongside search, social, and retail media campaigns seamlessly, fostering holistic campaign management and attribution that directly links ad delivery with purchase data across both open web and walled garden environments. Smaller vendors, facing competition from retail giants who control both media and sales data, are compelled to embrace interoperability and data partnerships rather than consolidation, signaling a future where collaborative integration is key to competitiveness.

The launch of a unified retail media platform by Kevel, Dollar General, and The Trade Desk marks a pivotal step in bridging onsite and offsite advertising within a single interoperable framework, directly addressing longstanding ecosystem fragmentation. This collaboration integrates Dollar General’s onsite retail media inventory with offsite activations powered by The Trade Desk, while Kevel provides the technological backbone to connect inventory, activation, and measurement. Advertisers benefit from the ability to plan, execute, and measure campaigns across channels in one system, supporting both managed and self-service activation, and enabling enhanced full-funnel measurement that moves beyond last-click attribution—setting the stage for future self-serve onsite ad buying.

The convergence of retail media and shopper marketing into a unified, adaptive channel is reshaping how brands influence both digital and physical retail environments. Retailer apps have emerged as critical integration points, bridging ecommerce and brick-and-mortar by guiding navigation, delivering personalized offers, and enabling real-time inventory and fulfillment updates, thereby facilitating unified measurement and attribution that links digital engagement with in-store behavior. This evolution supports closed-loop attribution and adaptive audience management models that connect media exposure directly to purchase behavior across channels, effectively addressing fragmentation and enabling truly holistic campaign management.

By early 2026, major Australian retailers including JB Hi-Fi, Woolworths, and Coles have aggressively expanded their in-house Retail Media Networks, leveraging technologies like Broadsign to capture advertising dollars traditionally allocated to free-to-air TV, radio, and billboards. This direct-to-brand model, combined with sophisticated 'closed-loop' measurement that ties advertising exposure directly to sales outcomes, creates highly accountable and profitable platforms that legacy media cannot easily replicate, fundamentally reshaping advertising spend and media ownership.

This transformation is not isolated to Australia; globally, retail and commerce media overtook total television advertising spend in 2025, signaling a profound budget shift from traditional media to retailer-owned ecosystems. In Australia specifically, retail media is projected to surpass total TV advertising revenue by 2027, underscoring the accelerating migration of brand budgets away from free-to-air TV and other legacy channels toward retail media networks that offer measurable ROI and direct consumer targeting at the point of purchase.

Traditional media companies are grappling with steep revenue declines and structural challenges as they lose control over advertising dollars to retailer-controlled ecosystems, prompting industry consolidation. Meanwhile, the rise of AI-driven consumer journeys poses emerging risks to retail media networks, especially smaller and mid-tier players in the 'messy middle,' as these journeys increasingly bypass retailer sites altogether—leading giants like Amazon to restrict AI platforms from accessing their inventory to protect on-site media revenue.

Retailers with substantial brick-and-mortar footprints, such as Walmart, maintain a critical share of advertising budgets due to their offline sales dominance, which insulates them somewhat from AI-driven commerce disruptions. Walmart's strategic partnership with OpenAI exemplifies how these retailers are adapting to the evolving landscape, ensuring that manufacturers and CPG companies continue to invest in advertising within their ecosystems despite the shifting digital dynamics.

By early 2026, digital giants like Meta and Google have deeply integrated AI-driven solutions to optimize ad delivery in real time, shifting the traditional post-campaign measurement paradigm to one where incremental outcomes actively guide optimization. Meta's incremental Attribution product exemplifies this trend by using machine learning to maximize incremental conversions, with platforms asserting these AI tools outperform manual campaign management. However, advertisers are advised to focus less on deciphering the opaque inner workings of these algorithms and more on externally evaluating overall platform effectiveness through independent experiments, ensuring that platforms remain incentivized to deliver genuine incremental conversions.

Despite the sophistication of AI-powered marketing tools, independent external validation frameworks are indispensable to counteract inherent biases in platform-reported metrics and guarantee accountability. As highlighted repeatedly, even though Meta and Google's data scientists implement reasonable measurement frameworks, these remain skewed toward their own platforms, necessitating advertisers to establish their own external measurement systems. Such frameworks not only provide unbiased assessments of true incremental impact but also align incentives so that platforms prioritize delivering authentic business outcomes rather than inflated self-reported success.

The evolution of marketing measurement now demands holistic incrementality testing frameworks that transcend single platforms to accurately capture cross-media effects across diverse retail channels. This approach generalizes seamlessly across e-commerce stores, Amazon sales, and brick-and-mortar outlets alike, enabling marketers to holistically validate whether advertising efforts are genuinely propelling business growth. While providing platforms like Facebook, Meta, or Google with comprehensive data enhances their AI optimization capabilities, ultimate measurement and accountability rest firmly on robust independent evaluation frameworks that stand apart from the platforms’ black-box algorithms.

By early 2026, legacy media, particularly television, is undergoing a critical transformation to reclaim performance budgets lost to digital platforms by embracing outcomes-based measurement. This shift addresses a longstanding complacency where advertisers spent heavily without clear insight into business impact. As one insider observed, it was 'crazy' that large advertisers lacked understanding of how legacy media drove their bottom line. Now, trust is being reframed as a measurable outcome, but one that must demonstrably link to sales to satisfy CFOs and justify marketing spend.

Warner Bros. Discovery exemplifies this evolution by integrating standardized conversion APIs through OpenAP and launching real-time attribution dashboards, signaling TV's emergence as a bona fide performance marketing channel. Their 2026 upfronts highlighted a blend of premium content with digital measurement frameworks tracking brand lift, engagement, and sales conversions. Additionally, AI-powered tools like shoppable pause ads and agentic AI support human decision-making, enhancing targeting efficiency without replacing human oversight, underscoring a nuanced approach to technology adoption.

Across the legacy media landscape, companies such as NBCUniversal and Fox are aggressively deploying outcomes-based measurement hubs and reporting tools to meet the growing demand for accountability and transparency in a data-driven advertising environment. The collective message at 2026 upfronts was clear: 'the big screen on the wall is, in fact, a performance marketing channel,' with Amazon leveraging purchase data and dynamic creative optimization to tailor calls to action. Cross-publisher collaborations, notably OpenAP’s initiative including Paramount, NBCUniversal, and A+E, aim to unify impressions and outcomes data via conversion APIs, enhancing measurement comprehensiveness.

Despite these advances, challenges remain as legacy media grapples with the lack of cohesive measurement tools to definitively prove advertising impact, a problem industry leaders acknowledge is 'not settled.' Premium content is being redefined to deliver both cultural impact and measurable business results, reflecting evolving buyer expectations. Meanwhile, economic uncertainties are driving agencies to demand greater deal flexibility during upfront negotiations, influencing how legacy media allocates budgets amid cautious spending, especially outside resilient categories like sports.