The Adoption Curve Just Went Vertical
Grocery has never been the sector that rushes into new technology, which is what makes the latest FMI research striking. The share of food retailers using artificial intelligence has climbed to 68 percent, up from 47 percent only a year earlier. A more than twenty point jump in a single year in an industry known for thin margins and operational conservatism is not the slow diffusion we usually see. It is the signature of a technology crossing from optional experiment to competitive necessity, the point at which not adopting starts to feel like the risk.
We read this as the moment grocery stopped asking whether AI belongs in the business and started asking where it belongs first. The categories are familiar: demand forecasting, inventory and shrink reduction, pricing, labor scheduling, and increasingly customer facing recommendation and search. What has changed is the posture. A year ago these were pilots owned by an innovation team. Now they are line items owned by operators, which is precisely the transition that separates technologies that stick from those that quietly get shelved after the pilot budget runs out.
Technology Spending Doubled in a Year
The spending data tells the same story with more force. Food retailers allocated nearly 2 percent of total sales to technology in 2025, roughly double the share they committed in 2024. In a business where net margins are frequently in the low single digits, doubling technology spend as a proportion of sales is an aggressive reallocation of scarce capital. It is the kind of number that only appears when boards have concluded the cost of standing still exceeds the cost of investment, and it puts real weight behind the adoption figures.
The forward looking signal is just as clear. Seventy one percent of retailers expect to spend more on technology in 2026 than they did last year, and nearly one in ten expect their technology expenses to rise a lot. This is not a one time catch up. It is the beginning of a sustained shift in where grocers put their money, away from purely physical assets and toward the software and data capabilities that increasingly determine who wins. For suppliers and technology vendors, the message is that grocery has become a growth market rather than a laggard.
Generative AI Moves From Pilot to Platform
Generative AI specifically has followed the same steep curve, with use rising to 59 percent of food retailers from 43 percent a year earlier. More telling is that 40 percent report deploying generative AI tools organization wide rather than in isolated corners. Enterprise wide deployment is the harder milestone. It implies that a retailer has moved past a single team's experiment and built the governance, integration, and change management required to put generative tools in front of many employees, which is where the operational payoff and the operational risk both live.
We would temper the enthusiasm with a note on maturity. Organization wide deployment is a measure of reach, not of value realized, and the history of enterprise technology is full of tools that were widely rolled out and lightly used. The retailers who convert this adoption into durable advantage will be those who redesign processes around the technology rather than layering it on top of existing workflows. Reworking how buyers plan assortments or how stores manage labor is far harder than switching on a generative feature, and it is where the real separation will happen.
The Consumer Adoption Gap Is Real
For all the retailer momentum, shoppers have not kept pace. Separate research from Dunnhumby finds only about 15 percent of US consumers use AI when buying groceries. That gap between how fast retailers are adopting and how slowly customers are changing behavior is the most important tension in the data, and it should shape where grocers point their investment. When adoption on the supply side races ahead of demand, the safest returns come from internal operations, forecasting, replenishment, and labor, where the retailer controls both the input and the outcome.
The customer facing bet is riskier and slower to mature. Agentic shopping, conversational assistants, and AI driven recommendations may well reshape grocery buying, but a 15 percent consumer adoption rate says that day is not here yet. We would caution grocery leaders against over indexing on flashy shopper facing features while the audience remains small and skeptical. The retailers who quietly wring cost and accuracy out of the back of the store today will be better positioned to fund the customer experiences that pay off once shoppers are actually ready for them.
Hiring Data Analysts, Not Cutting Staff
One finding cuts against the dominant narrative that AI arrives to eliminate jobs. Only around 10 percent of grocers believe these systems will let them reassign staff, while more than half anticipate hiring data analytics specialists. In other words, the near term employment effect of AI in grocery is additive. The technology creates demand for people who can build, tune, and interpret it faster than it displaces existing roles, at least in this sector and at this stage of the curve.
This has a practical consequence that CIOs underestimate. The binding constraint on grocery AI will not be model access, which is cheap and getting cheaper, but the scarcity of people who can turn data into decisions the business trusts. Retailers competing for the same limited pool of analytics talent will find that the differentiator is not which model they use but whether they can attract and retain the humans who make it work. The organizations that plan for that talent gap now will move faster than those who assume the software runs itself.
What This Means for Grocery CIOs
Taken together, the FMI numbers describe an industry that has decided, collectively and quickly, that AI is core infrastructure rather than a science project. Adoption at 68 percent, technology spend doubling as a share of sales, and generative tools going organization wide are the marks of a sector past the point of debating the premise. For grocery CIOs, the strategic question has shifted from whether to invest to how to sequence investment so that spending translates into margin rather than into stranded pilots.
Our guidance is to let the consumer adoption gap set the priorities. Anchor the near term program in operational use cases with measurable returns, build the analytics talent bench that everything else depends on, and treat customer facing AI as an option to be scaled when shopper behavior catches up, not a race to be won today. The retailers who spend with that discipline will convert a doubling of technology budget into durable advantage. Those who chase headlines will simply have doubled their spend.
