The Rise of Agentic Commerce: Revolutionizing the Buying Process with Autonomous AI Agents

Accra: 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. According to Ghana Web, progression is a constant. Recent advancements in digital technologies mean commerce is moving online in an unprecedented manner. E-commerce is fast-growing, with the industry valued at $7.4 trillion and expected to reach the $8 trillion mark by 2027. Traditional e-commerce involves digitally facilitated buying and selling, with all related transactions performed and backed by different value chain management technologies that 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 appli ed to commerce, a new form of e-commerce known as agentic commerce is born. Agentic commerce can be described as an autonomous AI agent which researches, compares, negotiates, and completes 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 do all the related tasks until the item is delivered successfully. The same approach is applicable for services; if 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 h uman-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 and subscriptions, Business to Business (B2B) procurement and inventory replenishment, price monitoring and automated deal hunting, travel, ticketing, and digital services and physical retail integrations. Agentic commerce differs from traditional e-commerce in several ways. In traditional e-commerce, users search, compare, and check out manually, with user experience and storefront design driving discovery and human decision points. In contrast, agentic commerce involves AI agents performing all steps autonomously, with structured data and protocols driving discovery and continuous automated micro-decisions. Proact ive, reasoning agents plan and act, rather than reactive chatbots. 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 fulfills the order during checkout and settlement. The key characteristics of agentic commerce include autonomous decision-making, 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 discover y, 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. However, the challenges of agentic commerce include the age-old principal-agent problem, which rears its head 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 t erms 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?'. 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.