Agentic Commerce: Closing the Readiness Gap
New RetailX research: agentic AI is rewriting the buying journey — and only one in ten retail leaders feel ready for it.
Shoppers are already handing orders to AI agents that compare, choose, and buy on their behalf — and those agents only surface retailers whose data they can read and trust. That puts infrastructure in the spotlight: stale batch data, order and inventory systems too slow for machine-paced demand, and catalogs built for screens, not agents. Leaders expect AI to reshape their business within five years, but readiness hasn’t caught up.
Free, from KIBO Commerce.
What’s inside the Blue Paper
What the research found.
Why retailers must act now to harness AI, streamline operations and elevate customer experience.
The strategic context
The RetailX Leadership Barometer on the readiness gap: 70% of leaders agree AI will fundamentally change their business model within five years, just 10% say they're fully prepared — and the boardroom AI skills gap sitting behind it.
The rise of the AI shopper
ConsumerX research on shoppers and their agents: 42.5% already comfortable with an agent placing regular orders, two-thirds preferring their own assistant, SEO evolving into GEO — and why a “ghost” out-of-stock listing means the retailer, not the customer's agent, takes the reputational hit.
The Infrastructure Reality Check
What operational readiness looks like before a retailer can credibly support agentic commerce: order and inventory systems that keep pace with machine-paced demand, a modern OMS as “a foundational technology”, real-time data streaming, and core inventory data formatted for AI agents to read.
An expert perspective
Lawrence Roycroft, VP EMEA at KIBO Commerce, on why readiness for agentic commerce starts with your data model, not the model.
Plus the look-ahead chapter - What will we do tomorrow? — the agnostic, composable approach (MACH, MCP) as the defence against vendor lock-in, US/EU regulatory divergence, and AI-market volatility.
Why retailers are reading this now
The storefront is no longer the only surface a retailer has to serve, or the only one that has to be right. AI agents are comparing, choosing, and buying on the customer’s behalf, and they only surface retailers whose availability, pricing, and delivery promises they can read and trust. SEO is evolving into GEO, and when an agent finds a “ghost” out-of-stock listing, it is the retailer, not the agent, that takes the reputational hit.
The readiness gap is the story behind the hype. Retail leaders expect AI to change their business models within five years, yet only one in ten say they are fully prepared, and agentic demand will not wait for the boardroom to close the gap.
The retailers who win the next five years will not be the ones with the boldest AI marketing. They will be the ones whose operations can keep the promises their agents make.
“An AI agent acting on stale or partial data will confidently make promises the business cannot keep. The same agent, working from one accurate, real-time data model, can actually fulfil them.”
Agentic AI can only promise what your operations can keep
“AI marketing tools make promises that siloed backend systems cannot fulfil.”
Agentic AI can only promise what your operations can keep. KIBO runs commerce and order management on one platform and one data model. You get a single, real-time view of inventory, pricing, and fulfilment shared across every surface. That’s what lets AI agents confirm availability, calculate pricing, and commit to delivery dates within the same flow, with no API lag between the system that knows and the screen that sells.
And with KIBO AI, the model is yours to choose:
your key, your data, your spend.
Results from KIBO’s own deployments
Analyst recognition
