AI agents interact on behalf of shoppers, engaging with thousands of stores and catalogues in a matter of seconds to find the best deal, bringing unprecedented speed and convenience to the consumer. On the other hand, merchants face the risk of losing brand loyalty, proximity to customers, or worse, seeing their products and services reduced to commodities in the sea of AI-driven recommendations. In this article we will review the latest developments in agentic commerce from a merchant perspective. We will compare user journeys, potential challenges, implementation models and value creation opportunities.
Whether Agentic commerce will help unlock a new and powerful acquisition channel for merchants boosting sales or end up cannibalizing them relies on intricate technical underpinnings, including API endpoints, data pipelines, and cross-platform connectors that determine how agents access and transact with merchant inventories. Nonetheless, it is certain that the customer journeys will be radically compressed compared to traditional e-commerce (see figure 1). There are some key differences between human and machine behaviors that will impact buying journeys and consequently conversions:
Information absorption & processing: Machines can consume and compare vast amounts of product data. Detailed comparisons between brands, product quality, warranties etc. can be made at the click of a button.
Speed and time: Machines can read at the speed of light and be active in hundreds of funnels simultaneously 24/7/365. Example: when booking flights, agents can simultaneously test full checkout flows across multiple airlines to surface the true total cost (including add-ons like baggage and seat selection).
Insensitivity to intangibles: Human shopping behavior is directed by feelings around a brand, the quality of the product imagery or the website experience. These are all poor proxies for product quality. Agents are likely to ignore these intangible proxies and more likely to leverage processing power to assess the actual product quality.
AI agents interact on behalf of shoppers, engaging with thousands of stores and catalogues in a matter of seconds to find the best deal, bringing unprecedented speed and convenience to the consumer. On the other hand, merchants face the risk of losing brand loyalty, proximity to customers, or worse, seeing their products and services reduced to commodities in the sea of AI-driven recommendations. In this article we will review the latest developments in agentic commerce from a merchant perspective. We will compare user journeys, potential challenges, implementation models and value creation opportunities.
Whether Agentic commerce will help unlock a new and powerful acquisition channel for merchants boosting sales or end up cannibalizing them relies on intricate technical underpinnings, including API endpoints, data pipelines, and cross-platform connectors that determine how agents access and transact with merchant inventories. Nonetheless, it is certain that the customer journeys will be radically compressed compared to traditional e-commerce (see figure 1). There are some key differences between human and machine behaviors that will impact buying journeys and consequently conversions:
Information absorption & processing: Machines can consume and compare vast amounts of product data. Detailed comparisons between brands, product quality, warranties etc. can be made at the click of a button.
Speed and time: Machines can read at the speed of light and be active in hundreds of funnels simultaneously 24/7/365. Example: when booking flights, agents can simultaneously test full checkout flows across multiple airlines to surface the true total cost (including add-ons like baggage and seat selection).
Insensitivity to intangibles: Human shopping behavior is directed by feelings around a brand, the quality of the product imagery or the website experience. These are all poor proxies for product quality. Agents are likely to ignore these intangible proxies and more likely to leverage processing power to assess the actual product quality.