Retailers embrace agentic commerce but warn AI shopping still faces major execution gaps

Enterprise Leaders Bet Big on Agentic Commerce Despite Execution Challenges

The retail industry is racing toward an AI-powered future, but the path to agentic commerce remains more complex than many anticipated. According to Logicbroker's "The State of Agentic Commerce Adoption" report surveying over 600 enterprise e-commerce leaders, more than 90% expect AI agents to influence at least 20% of online orders by 2027, with over a third believing AI shopping could shape more than half of all transactions 1

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. The momentum is undeniable: 95% of enterprises have already deployed at least one AI-driven commerce capability, while 47% plan to invest $1 million or more in AI-driven commerce initiatives over the next 12 months 1

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More than half of organizations plan to roll out AI-shopping agents within the next six months, with nearly half expecting returns within the first year and three-quarters predicting ROI within two years 1

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. DIY retailer Kingfisher exemplifies this enthusiasm, announcing plans to roll out agentic AI shopping capabilities based on Google Cloud's Vertex AI across its B&Q, Castorama, and Brico Depot France brands following "meaningful results" from pilot trials 1

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. With e-commerce already accounting for more than 20% of Kingfisher's Group sales, CEO Thierry Garnier sees AI-powered shopping as delivering "a fully personalised and easy shopping experience" 1

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Major Retailers Urge Caution as Technology Remains Nascent

Not all retail leaders share the same unbridled optimism. BestBuy CEO Corie Barry says the firm has "taken our time working our way into agentic commerce," emphasizing the need for a strategic plan around what data should be universally available versus what remains unique to a brand's experience 1

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. Barry points to specific challenges in consumer electronics, where AI agents frequently provide wrong answers due to the sheer volume of models and rapidly changing data. Retailers need "a real solid plan" around data ownership and site optimization, including potentially creating hidden pages specifically for bots to scrape for more accurate information 1

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Wayfair founder and CEO Niraj Shah echoes this measured approach, noting that "this notion that LLMs and AI agents can do everything is not the case, but they can do a lot" 1

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. Shah points to lessons learned by Google Shopping, which attempted to complete transactions within its platform but ultimately found that consumers prefer to go lower funnel to retailer sites for final purchases.

The Product Discovery Gap: Research Excels But Transactions Lag

The behavioral shift toward AI answer engines for product discovery has accelerated faster than industry observers anticipated. PYMNTS Intelligence research from January 2026 found that 41% of consumers have already used dedicated AI platforms for product discovery, with a third saying they have fully replaced their prior methods 3

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. Among AI power users, reliance on native AI interfaces as the primary method for shopping discovery jumped from 22% in November 2025 to 34% by December 2025, while light users saw their adoption surge from 5% to 16% in the same period 3

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Yet a critical infrastructure gap persists. What is billed as a revolution in online shopping remains, for now, "mostly a highly intelligent search bar," according to PYMNTS analysis 3

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. While LLMs excel at helping consumers research and shortlist options through conversational interfaces that explain tradeoffs between competing products, they cannot confirm actual prices, verify stock availability, or complete transactions. Consumers still must navigate to merchant sites to finalize purchases, often defaulting to trusted platforms like Amazon where the transaction loop is seamless.

How Answer Engine Optimization Is Reshaping the Buyer Journey

The rise of AI answer engines like ChatGPT, Google Gemini, and Perplexity is fundamentally altering how software and products get discovered. Tim Sanders, Chief Innovation Officer at review platform G2, notes that studies show B2B buyers now spend half their buyer journey on chat platforms 2

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. While this initially decreased traffic for review sites in 2023/24, G2 saw traffic increase in 2025, with over 1 million human visitors coming from AI chatbots during the buying process 2

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The key insight: LLMs provide fast answers, but for high-risk B2B purchases, buyers "trust but verify." Citations from answer engines have click-through rates sometimes 10x higher than traditional search results 2

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. G2 discovered that its Best Software Awards report and related content comprises around 60% of G2 citations on Large Language Models, signaling that LLMs seek sentiment at scale to confidently provide recommendations 2

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. This has made Answer Engine Optimization (AEO) central to G2's strategy, with the company focusing on freshness updates, frontier content that answers previously unanswered questions, and double verification to ensure reviews come from real users 2

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Google Faces Structural Challenges as Search Monetization Model Shifts

The structural fracture in search behavior poses significant challenges for Google, despite strong headline numbers. In Q4 2025, Google Search revenue grew 17% year-over-year, Gemini reached 750 million monthly active users, and Alphabet crossed $400 billion in annual revenue for the first time 3

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. Yet the highest-value part of the funnel is shifting. Consumers who once opened Google to research products now open ChatGPT, Claude, or Perplexity instead, representing "a structural fracture of the search function that Google has monetized for two decades" 3

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Google has attempted to become a commerce destination since launching Froogle in 2002, rebranding multiple times and embedding capabilities into Gemini. Despite these efforts, Google Shopping remains a listing service that sends consumers elsewhere to complete purchases. While Google may retain transactional queries from consumers ready to buy, the research and comparison phase where consumer intent is shaped is moving to conversational AI platforms. This represents not a marginal behavioral shift but a fundamental change in how the buyer journey unfolds, with implications for every player in the e-commerce ecosystem trying to establish trust and capture value in an AI-mediated marketplace.