Trade and commerce are critical to the functioning of society. Commerce has undergone a remarkable transformation, from barter and commodity-based exchange to today’s sophisticated ecosystem of digital payments, financial instruments, and global trade platforms. Progression is a constant. Recent advancement in digital technologies means commerce is moving online in unprecedented manner. E-commerce is fast growing with the industry valued at a $7.4 trillion and expected to reach $8 trillion mark by 2027.
Traditional e-commerce is digital facilitated buying and selling with all related transactions performed backed by different value chain management technologies which ensure goods and services are delivered to clients without any face-to-face interaction. The advent of AI has led to the evolution of AI-powered agents, known as agentic AI, which are capable of undertaking tasks autonomously, with minimal or no direct human intervention. When agentic ai is applied to commerce, a new form of e-commerce known as agentic commence is born. Agentic commerce can be described as an autonomous AI agent which research, compare, negotiate, and complete purchases on behalf of users or businesses, often without human intervention. For agentic commerce to work, it is fed structured product or service data backed by standardized protocols so agents can discover items, verify user authorization, and execute payments safely. Think of it this way, a firm or an individual who needs to purchase a number of items will delegate this function to agentic AI, which means the agents does all the related tasks until the item is delivered successfully. The same approach is applicable for services, assuming you want to buy several flight tickets, arrange local transportation and make hotel bookings, instead of doing it yourself or delegating it to your human office assistant or a travel agent, agentic AI does all this for you. In this direction, agentic commerce shifts the buying journey from human-driven browsing activities to AI-driven action. This means instead of spending a lot of time manually searching, comparing, and checking out, users provide intent (e.g., “find business class ticket under 2000 dollars”), and the agent AI handles the entire workflow from start to finish. Agentic commerce can be applied in a number of use cases including but not limited to recurring purchases & subscriptions, Business to Business (B2B) procurement and inventory replenishment, price monitoring and automated deal hunting, travel, ticketing, and digital services and physical retail integrations.
How Agentic Commerce Differs from Traditional E‑commerce
| Traditional E‑commerce | Agentic Commerce |
| User searches, compares, and checks out manually | AI agent performs all steps autonomously |
| UX and storefront design drive discovery | Structured data and protocols drive discovery |
| Human decision points | Continuous automated micro-decisions |
| Reactive chatbots | Proactive, reasoning agents that plan and act |
How Agentic Commerce Works
Agentic commerce can typically be described as a four-part flow. First is intent capture, where the user sets constraints, such as the type of products or services, budget, size, and timing, for the agent to act on. Second is discovery and selection, where the agent scans multiple service providers using machine-readable product data across various sites. Third is authorization, which ensures the agent translates the principal’s intent using cryptographic proof, meaning the principal approves the specific purchase. Finally, the agent completes payment using secure tokens, and the merchant fulfils the order during checkout and settlement.
The key characteristics of agentic commerce include autonomous decision-making, which is the ability of agents to independently evaluate products, prices, and constraints. Another important feature is end-to-end execution, where agents are able to perform tasks across the commerce journey, including product discovery, comparison, cart building, authorization, and payment. Furthermore, agents are equipped with reasoning and planning capabilities, enabling them to adapt to changes such as price fluctuations, stock availability, and user preferences, among others. Lastly, an important characteristic of agentic commerce is interoperability, where agents can integrate across retailers and platforms through open APIs and relevant commerce protocols. Agentic commerce comes with a number of advantages such as greater personalization, faster purchasing, lower transaction costs, improved decision-making, and seamless end-to-end shopping experiences.
The Challenges of Agentic Commerce
Age-old principal-agent problem rears its head, albeit in a digital environment, typically the principal delegates a task to an agent, whose interests, information, or actions may not fully align with those of the principal. This situation can create risks of information asymmetry, moral hazard, and opportunistic behavior. In terms of agentic commerce, AI agents increasingly act on behalf of consumers or firms by searching for products, comparing prices, negotiating, and completing transactions. Therefore, the principal-agent problem means changes from “Can I trust the seller?” to “Can I trust my agent to act in my best interests?”. An AI agent may be optimized for speed, price, or commissions rather than the principal’s actual preferences. In this direction, agentic commerce requires mechanisms for alignment, transparency, accountability, consent, and oversight to ensure that delegated AI decision-making genuinely represents the principal’s interests to deal with principal-agent problem.
Trust & Alignment is another critical problem facing agentic commerce that is ensuring AI agents genuinely act in the consumer’s best interests rather than optimizing for sellers, platforms, commissions, or other incentives. Other challenges include privacy and data security issues; accountability and liability; interoperability and standards; fraud, manipulation and competition.
Agentic commerce is now emerging due to several factors, including advancements in AI and autonomous agents, standardized commerce protocols (e.g., MCP, ACP, UCP), and growing consumer adoption, with IBM reporting that 45% of consumers already use AI in parts of the buying journey today. It is projected that AI agents could mediate $3 trillion to $5 trillion of global consumer commerce by 2030, according to Mckinsey.
In conclusion, agentic commerce is a radical shift from optimizing human checkout flows to enabling AI agents to transact safely and autonomously on behalf of users, that is, the principal. However, it is confronted with emerging risks and challenges, and the ability of the industry to deal with these challenges will set agentic commerce on a rapid path of growth while becoming an integral part of global commerce.
Dr Kwami Ahiabenu is an AI and technology consultant. He can be reached at [email protected].
