New research from Tidio reveals a significant disconnect between artificial intelligence's actual influence on consumer purchasing decisions and how that influence is measured through standard web analytics. According to the report, AI in E-Commerce in 2026: The New Shopping Funnel, half of consumers now rely on AI as their primary or preferred source for product research, based on McKinsey data, yet analysis of retail web traffic by Contentsquare shows AI-referred sessions account for only 0.2% of total visits.
The report identifies this discrepancy as evidence of what it terms dark AI influence that is commercially real but analytically invisible. The mechanism involves consumers asking AI assistants for product recommendations, receiving a shortlist, and then navigating directly to recommended brands via new browser tabs or branded searches. These sessions register as direct or organic traffic in standard attribution models, leaving the initiating AI with no credit for the referral.
Conversion data from the small percentage of sessions that are properly tagged as AI-referred suggests the undercounting is substantial. Similarweb's analysis of U.S. retail data finds ChatGPT-referred sessions convert at 11.4%, the highest rate of any measured channel, surpassing direct traffic at 10.2%, paid search at 9.3%, and organic search at 5.3%. This conversion premium implies that tagged AI referrals represent only a fraction of a much larger pool of AI-influenced consumer journeys.
The attribution gap appears to be widening, presenting growing challenges for marketers. TollBit's analysis of AI bot behavior across publisher sites shows click-through rates from AI applications dropped nearly threefold during 2025, from 0.8% in the second quarter to 0.27% by year-end, as AI platforms consume more content while generating proportionally fewer outbound clicks.
Tytus Gołas, Founder and CEO of Tidio, noted that brands making budget decisions based on last-click attribution are optimizing for a measurement system that cannot see what is actually driving demand. The inputs determining AI visibility, including feed completeness, structured data, and review coverage, typically exist across multiple organizational teams with no clear ownership because the return on investment remains invisible.
The financial implications of this measurement gap are substantial. McKinsey projects $750 billion in U.S. revenue will flow through AI-powered search by 2028, with brands that fail to prepare risking 20 to 50 percent of their traditional search traffic. Morgan Stanley estimates AI agents will influence between $190 billion and $385 billion in U.S. e-commerce spending by 2030.
The report also documents emerging protocol infrastructure designed to formalize AI's role in transactions. Google's Universal Commerce Protocol, OpenAI's Agentic Commerce Protocol, and Visa's Trusted Agent Protocol are creating standardized frameworks for AI agents to complete purchases on behalf of consumers. Consumer readiness for such transactions is building rapidly, with Omnisend's longitudinal research finding reluctance to allow AI to complete purchases dropped from 66% to 32% between February and July 2025.
The full report is available for download at https://www.getlyro.ai/reports/ai-in-ecommerce.
