The Rise of Agentic Commerce: When machines become buyers

Commerce has evolved from barter systems to today's complex digital landscape. E-commerce now boasts a $7.4 trillion valuation, projected to surpass $8 trillion by 2027. Traditional e-commerce relies on digitally facilitated transactions, while AI-powered agents, or agentic AI, are taking commerce to the next level. When applied to commerce, agentic AI creates a new e-commerce phenomenon: agentic commerce.

Agentic commerce involves autonomous AI agents researching, comparing, negotiating, and completing purchases without human involvement. These agents require structured product or service data and standardised protocols for safe execution. For instance, a user can delegate tasks like buying multiple flight tickets, arranging transportation, and booking hotels to agentic AI, eliminating the need for manual intervention.

Agentic commerce streamlines the buying journey, shifting it from human-driven browsing to AI-driven actions. Users provide intent, such as "find a business class ticket under $2,000", and the AI agent manages the entire process from start to finish. This approach benefits various use cases, including recurring purchases, B2B procurement, price monitoring, travel, and retail integrations.

Agentic commerce differs from traditional e-commerce in several ways. While traditional e-commerce relies on manual user searches and human decision points, agentic commerce employs proactive, reasoning agents that continuously make micro-decisions. Agentic commerce also differs in its use of structured data and protocols for discovery, as opposed to UX and storefront design in traditional e-commerce.

The four-part flow of agentic commerce includes intent capture, discovery and selection, authorisation, and payment completion. Key characteristics of agentic commerce include autonomous decision-making, end-to-end execution, reasoning and planning capabilities, and interoperability. These features enable greater personalization, faster purchasing, lower transaction costs, and seamless shopping experiences.

However, agentic commerce faces challenges, such as the principal-agent problem. AI agents may optimise for factors other than the principal's preferences, raising concerns about trust and alignment. Additionally, privacy and data security issues, as well as the need for transparency, accountability, and oversight, must be addressed to ensure agentic commerce genuinely benefits consumers.