Agentic commerce (also referred to as agent-based commerce) describes a form of electronic commerce in which autonomous artificial intelligence (AI)agents independently execute purchasing and payment processes on behalf of users or organizations. Unlike conventional digital commerce systems, which require direct human interaction at key decision points, agentic commerce systems are designed to search for products or services, evaluate options, make purchasing decisions, and complete payments with limited or no real-time human involvement.
The concept is associated with advances in generative AI, autonomous agents, application programming interfaces (APIs), and digital payment infrastructures. Agentic commerce is considered an emerging development within the broader fields of e-commerce, fintech, and artificial intelligence.
Characteristics
A defining feature of agentic commerce is the delegation of end-to-end commercial activities to software agents. These agents typically operate according to predefined user preferences, rules, or constraints, such as price limits, quality criteria, delivery times, or preferred payment methods. Based on these parameters, an agent can autonomously perform tasks including product discovery, price comparison, contract selection, order placement, and payment execution.[1]
In contrast to decision-support systems, which provide recommendations to human users, agentic commerce systems are designed to act independently. Human involvement may be limited to initial configuration, periodic supervision, or exception handling.[2]
Comparison with traditional and AI-assisted commerce
Traditional e-commerce requires users to manually browse products, select offers, and authorize payments. Generative AI systems used in commerce commonly assist users by answering questions or suggesting options but do not complete transactions autonomously.
Agentic commerce differs in that decision-making authority is partially or fully transferred to AI agents. As a result, the conventional customer journey, characterized by conscious decision points, may be replaced by continuous, automated micro-decisions performed by software.[3]
Applications and business use cases
Potential applications of agentic commerce include recurring purchases, subscription management, business-to-business procurement, inventory replenishment, and price monitoring. In such contexts, transactions are often predictable and standardized, making them suitable for automation. From a business perspective, agentic commerce systems may be used to optimize supply chains, manage inventory levels, negotiate prices algorithmically, or execute transactions across multiple platforms.[citation needed]
Payments and technical infrastructure
Agentic commerce relies on digital payment systems capable of supporting automated, machine-initiated transactions. This typically involves API-based payment processing, tokenization, real-time authorization, and continuous risk monitoring. In such systems, traditional user interfaces such as shopping carts may be replaced by backend integrations between AI agents, merchants, and payment service providers.[citation needed]
For merchants, participation in agentic commerce may require products and services to be presented in structured, machine-readable formats to ensure discoverability and interoperability with autonomous agents.[4]
Universal Commerce Protocol (UCP)
In January 2026, Google announced the Universal Commerce Protocol (UCP), an open-source web standard intended to enable interoperability between AI agents and retail systems across the shopping journey, from discovery and checkout to post-purchase support.[5][6][7][8] UCP makes use of REST, JSON-RPC transports, and support for Agent Payments Protocol (AP2), Agent2Agent (A2A), and Model Context Protocol(MCP).[9]
Legal, regulatory, and security considerations
The use of autonomous agents in commerce raises legal and regulatory questions, particularly regarding authorization, liability, consumer protection, and fraud prevention. Existing payment and contract frameworks are generally based on human decision-makers, and their applicability to autonomous agents remains an area of active discussion.[10]
Open issues include responsibility for unauthorized or erroneous transactions, mechanisms for dispute resolution, standards for agent authentication, and compliance with data protection and financial regulations. Continuous, automated transaction patterns may also require new approaches to security and risk assessment.[11]
Ecosystem and implementation
The adoption of agentic commerce typically requires changes in commerce architecture, data modeling, identity and permissions, and API-based orchestration of checkout and post-purchase workflows.[12] As a result, an ecosystem of technology vendors, systems integrators, and consulting firms has emerged to help merchants implement agent-enabled shopping capabilities and align with interoperability standards such as UCP.[13]
Management consultancies have identified agentic commerce as a structural evolution of digital commerce, emphasizing the role of AI-driven agents in automating discovery, decision-making, and transaction processes across commerce systems. McKinsey & Company has described agentic commerce as a significant shift in how consumers interact with brands and how enterprises design their commerce operating models.[14]
In Europe, this ecosystem also includes digital commerce consultancies specializing in the adoption of agentic commerce. Consulting firms such as Horrea support brands in understanding and implementing the technological and organizational shifts associated with agentic commerce. [15]
Market development and outlook
Agentic commerce is generally regarded as an early-stage development. Industry analysts have projected that AI-driven agents could account for a small but growing share of digital payment transactions within the coming years. Due to the scale of global digital commerce, even limited adoption could represent substantial transaction volumes. Analysts expect that by 2029, AI agents could handle between 1% and 4% of all digital payment transactions. With a projected total transaction volume of over $36 trillion a year, even a small share translates into a market worth up to $1.47 trillion.[2] According to a McKinsey study from October 2025, agentic commerce projects that by 2030, the *U.S. business-to-consumer retail market alone could see up to $1 trillion in revenue orchestrated through agentic commerce. On a global scale, the opportunity could range from $3 trillion to $5 trillion.[3]
Early experiments and pilot projects have demonstrated both the potential and current limitations of the technology.[16] Major payment networks and technology providers have announced initiatives related to AI-enabled commerce, including agent-based tokenisation, data protection, and automated transaction management platforms.[17] Among them are Mastercard,[18]Visa,[19]Stripe,[20] Mollie[21] and Unzer.[22]
News coverage of UCP (Universal Commerce Protocol) characterized it as a foundational layer for scaling agentic commerce, positioning it as a standardized mechanism for AI assistants and conversational interfaces to initiate and complete purchases without requiring bespoke integrations for each merchant or agent system.[13][23][24]
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