Rohit Laila is a seasoned veteran in the logistics and supply chain sector, bringing decades of hands-on experience in navigating the complexities of global delivery networks. Throughout his career, he has witnessed the evolution from manual tracking to sophisticated automated systems, positioning him as a leading voice on how innovation reshapes the movement of goods. As the industry stands on the brink of a new era where artificial intelligence moves from advisory roles to active decision-making, Laila provides critical insights into the infrastructure required to support this transition. This discussion explores the rise of agentic commerce, the technical demands of real-time order networks, and the strategic shifts necessary for brands to remain visible in an increasingly automated marketplace.
AI agents are moving beyond simple product searches to handle the entire purchasing process autonomously. How does this shift redefine the traditional concept of a “customer,” and what specific metrics should brands track to measure the success of these automated interactions?
The shift toward agentic commerce fundamentally changes our understanding of the consumer because the “buyer” is no longer a human browsing a screen, but an algorithm executing a logic-based command. When we surveyed over 600 enterprise ecommerce leaders, it became clear that the emotional triggers of traditional marketing are being replaced by the cold efficiency of data. For brands, this means success is no longer just about click-through rates or time-on-page; instead, we must track the precision of our API responses and the speed of our fulfillment data. If an AI agent cannot verify a product’s availability in milliseconds, that brand effectively ceases to exist for that customer. We are moving into a world where the technical reliability of the supply chain is the most powerful marketing tool a company possesses.
Many organizations are transitioning from transaction processing to complex order networks that connect suppliers and logistics. What are the biggest technical hurdles when integrating these disparate systems, and how can leaders ensure these nodes communicate in real-time without latency?
The primary hurdle is moving away from “single-point solutions” that only optimize one small part of the chain, such as a solitary warehouse or a specific shipping carrier. According to our findings, 67.2% of enterprise leaders now recognize that order-network capabilities are the most critical element of their infrastructure. The challenge lies in creating a coordination layer that synchronizes inventory, suppliers, and fulfillment systems so they speak the same language instantly. Leaders must invest in unified platforms that eliminate data silos, ensuring that when a supplier updates a stock level, that information vibrates through the entire network immediately. Without this level of deep integration, the latency between a “buy” command and the actual fulfillment becomes a catastrophic point of failure.
When an AI agent commits to a purchase, inventory and pricing data must be flawless at the moment of discovery. What operational changes are required to eliminate data discrepancies across channels, and what are the immediate risks of failing to provide this level of accuracy?
Operational excellence in the era of AI requires a move toward total, transparent inventory visibility that is updated in real-time rather than in batches. Currently, more than 95% of organizations have deployed at least one AI-powered commerce capability, but many still struggle with the underlying data integrity required to make those tools effective. If a shopping agent attempts to finalize a purchase based on outdated pricing or “ghost” inventory, the brand suffers an immediate loss of trust with the platform, leading to a de-ranking in future searches. We are seeing a shift where companies must prioritize the “plumbing” of their data—ensuring that every warehouse and third-party supplier is connected to a single source of truth. The risk of failure is total invisibility; if your fulfillment data is unreliable, AI agents will simply bypass your store for a competitor who can guarantee delivery.
Projections suggest that AI agents will influence a significant portion of online orders within the next few years. How should manufacturers rethink their fulfillment timelines today, and what step-by-step strategy do you recommend for scaling infrastructure to handle this automated demand?
With nearly 91% of enterprise leaders expecting AI agents to influence at least 20% of online orders by 2027, the window for preparation is closing rapidly. Manufacturers must stop thinking of fulfillment as the final step in a process and instead view it as a real-time capability that must be ready before the order is even conceived. I recommend a strategy that begins with auditing current latency in supplier communications and then moves toward automating warehouse operations to match the speed of digital agents. By scaling infrastructure through tighter integration between order management systems and logistics providers, companies can handle the sudden, sharp spikes in demand that automated shopping bots often trigger. This is about building a “connected supply chain” that can breathe and react at the speed of software rather than the speed of human manual entry.
Retailers who cannot provide reliable, real-time fulfillment data risk losing visibility to shopping agents entirely. How can mid-sized players compete with industry giants that have deeper logistical integration, and what trade-offs are involved in prioritizing back-end operations over customer-facing tools?
Mid-sized players must realize that in the agentic era, a beautiful website is far less important than a robust back-end API. While industry giants have the capital to build proprietary networks, smaller retailers can compete by joining open order networks and utilizing shared fulfillment ecosystems that offer high-level visibility. The trade-off is often a reduction in “brand storytelling” budget in favor of deep technical infrastructure, which can feel counterintuitive to traditional retailers. However, if the AI agent is the one making the choice, the sensory appeal of a homepage matters much less than the verified fact that a package can reach a doorstep in 48 hours. Investing in the coordination layer—the systems that connect inventory to shipping—is the only way to ensure they remain a viable option in the automated search results of the future.
What is your forecast for agentic commerce?
My forecast is that by 2027, the distinction between “ecommerce” and “fulfillment” will completely disappear, as the two become a single, unified execution engine. We will see a massive shakeout where the 20% of orders influenced by AI agents will determine the winners and losers based solely on their operational reliability. The brands that thrive will be those that transitioned from simple transaction processors to hyper-connected nodes in a global fulfillment web. Ultimately, we are heading toward a “frictionless” economy where the supply chain is the primary driver of the consumer experience, leaving no room for organizations that rely on disconnected or legacy systems.
