The rise of agentic commerce in numbers
42%
of consumers reported using AI tools for shopping within a single month.
40%
of agentic traffic now flows directly to e-commerce sites, bypassing traditional search.
83%
of successful AI shopping interactions leading to purchases start with unbranded queries.
The intelligence behind the transaction
AI is no longer just a search tool. It is becoming an autonomous agent, researching, comparing and purchasing on behalf of consumers. Agentic commerce is moving from speculative capability to market reality, reshaping brand strategy, data infrastructure, and customer relationships.
Understanding how agentic commerce works
Agentic commerce is not a single technology. It is a fundamental shift in how consumers discover, evaluate and buy.
Discovery
Traditional search engine usage is falling by 20 to 40% among AI adopters. AI agents are becoming the first point of contact between consumers and products.
Evaluation
Successful AI shopping hinges on three check-ins: scope, shortlist, final approval. Consumers lean on AI most in unfamiliar categories, where human-AI crossover can hurt performance. Meanwhile, product information requirements are expanding three to ten times.
Transaction
Universal checkout protocols are enabling commerce anywhere, across social platforms, influencer content and embedded experiences. But full autonomous purchasing remains the exception, not the rule.
The forces rewriting the rules of buying and selling
Brands matter more, not less
Agentic commerce increases commoditisation risk. When consumers can no longer evaluate products directly, brand recognition becomes the decisive factor. Brands relying solely on distribution or SEO face the risk of becoming invisible.
Platform power is redistributing
Marketplaces may lose power as AI agents efficiently comparison shop across sites. Direct merchant-to-AI relationships could strengthen, though logistics capabilities remain a powerful moat.
GEO is the new SEO
Organisations are shifting from traffic-based metrics to visibility-focused KPIs. GEO is becoming the successor to traditional search optimisation, requiring fundamentally different content strategies and data infrastructure.
The barriers to agentic commerce
Trust & autonomy
Consumers remain hesitant to fully automate high-stakes decisions. Shopping serves psychological and social needs beyond pure acquisition, and the assumption that consumers want to eliminate routine tasks does not always hold.
Data & visibility
Retailers are losing direct customer intent data as AI intermediates transactions, compounded by platform privacy rules that conceal conversational context. Meeting the 3–10× surge in product info demands requires entirely new content and data strategies.
Organisational readiness
Only one to two percent of senior managers are building agentic workplaces with ROI measurement. Context engineering is emerging as a critical organisational capability that most businesses have yet to develop.
How far will autonomy go?
"Agentic commerce is arriving faster than most organisations are prepared for, but full autonomous purchasing remains further away than technology capabilities alone would suggest, due to human psychological, social and experiential needs that transcend pure efficiency."
Insights from London Business School Industry Roundtable Research.
Data richness
Clean, comprehensive product data including unstructured content, video, detailed Q&As and long-tail specifications. Product information requirements are increasing three to ten times compared to traditional e-commerce.
Early positioning
Optimising for AI discovery, not just traditional search. Brands that build visibility in AI systems now will have a structural advantage as agentic commerce scales.
Brand differentiation
Moving beyond features and price to build communities, distinctive experiences and emotional connection. When AI commoditises product comparison, brand becomes the last meaningful differentiator.
Logistics excellence
Fulfilment and delivery capabilities remain an enduring competitive moat. Convenience continues to outweigh small price differences, even as AI makes comparison shopping frictionless.
A Business School perspective on agentic commerce
The implications of agentic commerce extend far beyond retail. From B2B routine purchasing and supply chain management to financial services models where frictionless switching threatens traditional customer lifetime value, AI agency touches every sector. London Business School's Data Science and AI Initiative brings together researchers, practitioners and policymakers to examine these questions at every level, from consumer psychology to corporate strategy and regulatory policy.
Key questions:
How should organisations restructure their content and data strategies for AI-mediated discovery?
What does brand building look like when the consumer journey is increasingly invisible?
Where does human judgement remain essential in an agentic commerce world?
