While AI agents could shift sales away from traditional retailers, companies with extensive physical infrastructure and forward-positioned inventory have a defense. AI agents prioritizing speed and efficiency for physical goods will likely still favor these established networks, preventing full disintermediation in the new agentic commerce landscape.
In the fast-evolving AI space, traditional moats are less relevant. The new defensibility comes from momentum—a combination of rapid product shipment velocity and effective distribution. Teams that can build and distribute faster than competitors will win, as the underlying technology layer is constantly shifting.
While AI fragments shopping channels, it also enables hyper-personalization of the fulfillment experience. By integrating external data like weather, transit times, and regional issues, brands can proactively communicate with customers about their orders, creating a deeper, more valuable connection.
The next frontier in e-commerce is inter-company AI collaboration. A brand's AI will detect an opportunity, like a needed digital shelf update, and generate a recommendation. After human approval, the request is sent directly to the retailer's AI agent for automatic execution.
AI makes the technical 'doing' of business, like coding, accessible to everyone. The durable competitive edge is no longer the ability to build a product, but the ability to reach and acquire customers. Audience and distribution channels are the new defensible assets.
AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.
As AI agents automate day-to-day e-commerce optimization, the primary role for humans evolves. Core competencies will shift from data analysis and execution to high-level decision-making and managing the complex, collaborative joint business planning process with retail partners.
A few dominant consumer platforms are capturing the majority of retail sales, creating a winner-take-all market. These companies leverage their scale and cash flow to reinvest in technology and advertising, widening their competitive moats much like the largest tech companies.
Creating a basic AI coding tool is easy. The defensible moat comes from building a vertically integrated platform with its own backend infrastructure like databases, user management, and integrations. This is extremely difficult for competitors to replicate, especially if they rely on third-party services like Superbase.
AI will fragment the customer journey across countless platforms, moving purchases away from brand-owned websites. Retailers must build systems to manage inventory and product information across this decentralized landscape, not just focus on perfecting their own site experience.
New technology like AI doesn't automatically displace incumbents. Established players like DoorDash and Google successfully defend their turf by leveraging deep-rooted network effects (e.g., restaurant relationships, user habits). They can adopt or build competing tech, while challengers struggle to replicate the established ecosystem.