State of AI in Consumer & Retail 2026: Key Findings and What They Mean

Marqo's State of AI in Consumer and Retail 2026 report draws on responses from more than 500 retail and commerce leaders across North America, Europe, and Asia-Pacific. The findings reveal an industry at an inflection point: AI adoption in ecommerce has moved from experimental to operational, but the gap between leaders and laggards is widening faster than most anticipated.

Finding 1: AI Search Has Crossed the Mainstream Threshold

Sixty-seven percent of respondents reported that AI-powered search was either fully deployed or in active implementation at their organization — up from 41% in the prior year's survey. The shift is most pronounced among mid-market retailers with catalogs between 10,000 and 500,000 SKUs, where AI search adoption grew fastest. Among those who had deployed AI search, 78% reported that it outperformed their previous system on at least one revenue metric within the first 90 days of deployment.

Finding 2: The ROI Gap Is Accelerating

Retailers that deployed AI-native search at least 18 months ago are reporting compounding returns that late adopters cannot replicate quickly. The advantage is not just in initial conversion lift — it is in the accumulation of behavioral data, model refinement, and catalog enrichment that occurs over time. Leaders who deployed early now have search systems that are measurably more accurate than those just beginning implementation, and the distance is growing. This dynamic is creating urgency among the 33% of respondents who have not yet deployed: they are not just behind today, they are falling further behind with each passing quarter.

Finding 3: Multimodal Capabilities Are the Next Competitive Frontier

Among retailers who had already deployed AI search, the top-ranked investment priority for the next 12 months was multimodal capability — specifically, the ability to search by image, combine text and image queries, and interpret visual aesthetic intent. This was cited by 61% of AI search leaders as their primary search investment. The driver is clear: as more shoppers arrive with visual intent shaped by social media, multimodal becomes the capability that separates the next generation of search leaders from those still catching up.

Finding 4: Personalization Integration Remains the Unsolved Problem

Despite high satisfaction with AI search relevance, only 34% of respondents described their personalization and search systems as fully integrated — meaning that individual shopper profiles meaningfully influenced search result rankings. The majority reported parallel systems that operated independently. This represents the largest untapped opportunity in the current landscape. Retailers that close the gap between search relevance and shopper personalization will see outsized gains in conversion and average order value.

Finding 5: Organizational Readiness, Not Technology, Is the Primary Barrier

When respondents who had not yet deployed AI search were asked about their primary barrier, the top answer was not cost or technology availability — it was organizational readiness. Specifically, they cited challenges in catalog data quality, lack of internal ML expertise, and unclear ownership between engineering and merchandising teams. The technology exists and is accessible, but retailers must invest in data foundations and cross-functional processes required to deploy it successfully. Those who address these organizational prerequisites will capture more value faster when they do deploy.