Research shows that nearly 91% of retail IT leaders are prioritizing AI as the top technology to implement this year. Yet far fewer are seeing meaningful results from their investments.

The gap between spending and returns comes down to one thing: data access. Brick-and-mortar teams, e-commerce teams, and supply chain teams often work from different versions of the truth. They lack the real-time data sync that would keep AI-powered inventory, shipping, and customer support workflows efficient and aligned. Critical information gets stuck in silos, slowing decisions and blunting impact.

Retailers that remove this friction unlock the value of AI, with faster time-to-value across every use case.

Retailers Are Taking Control of Their Data

When everyone works off the same information, decisions get easier and faster. Teams stop arguing over whose numbers are right. Merchants make faster calls on promotions and pricing. Operations teams spot inventory issues and act sooner. Consumers start trusting AI chatbots and personalized experiences. And AI can take on more responsibility.

But realizing these gains starts at the foundation. By connecting data across store locations, digital channels, and supply chains, critical information becomes usable across teams, even when systems and processes remain fragmented underneath.

In 2026, retailers will not win AI by experimentation alone—those without unified, real-time data will stall, while those fixing data access first unlock faster decisions, trusted automation, and scalable operational resilience.

Building Resilience in an Unstable Market

Industry leaders like Walmart are shrinking projects that once took months down to weeks by automating fulfillment details and optimizing workflows at the individual store, department, and truckload level.

This kind of speed matters more than ever. In 2026, reduced consumer spending increases warehousing costs as inventory sits on shelves. Inflation is quietly increasing rates of theft. Shipment disruptions around the world are threatening supply security. With such rapidly shifting conditions and consumers who expect near-instant responses, operational resilience is no longer optional.

AI gives retailers an opportunity to build real-time operational responsiveness that keeps them one step ahead of these pressures.

The Fastest Retail Teams Win

Gartner predicts that 75% of analytics will use generative AI to contextualize answers, dramatically improving access to insights across organizations. That shift broadens both the quality of results and who can act on them.

AI is pushing decision-making out of centralized teams and into the hands of merchants, marketers, and operations leaders who need answers in real time. But that only works when teams share access to the same trusted data. Without it, speed stalls, confidence erodes, and AI’s promise collapses under the weight of conflicting inputs.

But here is the catch. Agentic AI demands even more from your data infrastructure than traditional AI. An agent making autonomous decisions needs complete, accurate, real-time information from across the business. Feed it conflicting data from siloed systems and it will make conflicting decisions. The Kyndryl 2025 Retail Readiness Report put it plainly: progress on agentic AI is blocked by data silos and organizational resistance.

My prediction for 2026: the retailers who have not unified their data by year-end will find themselves locked out of the agentic economy. They will watch competitors deploy autonomous systems that optimize pricing, inventory, and customer experience in real time while they are still reconciling spreadsheets.

What Comes Next

AI is everywhere in retail, but its impact is not. What will continue to separate the leaders from laggards will come down to fundamentals: shared visibility, real-time access, and the ability to move quickly when conditions change.