The concept of AI agents autonomously making purchases is largely hype. The real, current opportunity is in the underappreciated role AI plays in the discovery and consideration phase, where consumers use it for low-risk tasks like product research and recommendations.

While the industry buzzes about sophisticated "agentic AI," the most common real-world applications in e-commerce are far more basic. Retailers are primarily using AI for task-oriented work like optimizing SKU description pages, highlighting a significant gap between current capabilities and future hype.

While many sellers use AI for basic tasks like writing emails, its true power lies in enhancing the buyer's experience. The real competitive advantage comes from leveraging AI to create decision-ready recaps, stakeholder-specific FAQs, and personalized recommendations, thereby shortening the sales cycle by making it easier for the customer to buy.

Stripe breaks down the hyped concept of "agentic commerce" into a practical, five-level framework: 1) Eliminating web forms, 2) Descriptive search, 3) Persistence & memory, 4) Delegation of purchasing, and 5) Anticipation of needs. This provides a clear roadmap for how AI will transform online buying.

The biggest problem in buying a TV isn't the final click to pay, but the hours of research. An effective AI agent should handle all the context-gathering (room size, reviews, deals) to present a highly informed choice, super-charging the user's decision rather than replacing it.

The most likely future of agentic commerce involves AI handling tedious research and checkout execution, while humans remain the final arbiters. Brand preference and advertising will still matter because the human "in the loop" makes the ultimate call based on a few AI-vetted options.

Agentic commerce will progress through stages: first automating web forms; second, enhanced semantic search; and third, using persistent user profiles for recommendations. The ultimate stage will be anticipatory AI, which proactively suggests purchases based on deep user understanding before a need is explicitly stated.

Future marketing must adapt to a world where the "customer" is an AI agent. These agents will bypass traditional persuasive tactics and brand narratives, instead performing objective, data-driven comparisons to find the best product. This forces brands to compete purely on measurable value and utility, fundamentally changing marketing strategies.

Marketers focus on using AI as a new tool, but the more profound shift is that customers now use AI for research, comparison, and even RFP generation, fundamentally altering the buying journey before they ever interact with a brand.