A thin-margin sector is spending like a tech buyer
FMI, the food industry association, published The Food Retailing Industry Speaks 2026 on July 21, and the headline figure reframes how much grocery now leans on technology. Food retailers dedicated more than 20 billion dollars to technology budgets in 2025, close to 2 percent of total sales and roughly double the prior year's share. In an industry that runs on net margins measured in low single digits, committing 2 percent of sales to technology is an aggressive allocation. It signals that grocery leaders no longer treat digital and AI investment as discretionary experimentation. They treat it as core operating cost on par with real estate and labor.
The report carries weight because of its base. It reflects input from more than 42,000 grocery stores, which makes it one of the more credible sector-wide reads on where food retail is actually putting its money. Leslie G. Sarasin, FMI's president and chief executive, framed the findings as evidence that technology has become central to how the industry competes. For a category historically slow to modernize, spending at this level is a structural shift. The dollars are large enough that they will reshape vendor markets, talent demand, and the competitive gap between operators who invest and those who stall.
AI adoption crossed from minority to majority
The most striking data point is the speed of AI adoption. Among food retailers, use of AI climbed from 47 percent to 68 percent in a single year, a jump that moved the technology from a minority experiment to a majority standard in twelve months. On the supplier side the shift is complete: every responding food supplier now uses AI in some form. That pace is faster than most enterprise technology transitions, and it reflects both the maturity of available tools and the competitive pressure operators feel once a rival demonstrates a working use case in forecasting, pricing, or fulfillment.
Generative AI specifically has moved from novelty to normal. More than half of grocers and every food manufacturer surveyed now use generative AI somewhere in their operations, whether in merchandising content, customer service, or internal knowledge work. The significance for technology leaders is that generative AI in grocery has passed the point where a pilot is a differentiator. When two-thirds of the sector and all of your suppliers are already using it, the strategic question shifts from whether to adopt toward where you deploy it for measurable operating leverage rather than as a checkbox on an innovation slide.
The returns question is still open
Adoption is running ahead of proven payback, and the report is honest about the gap. More than half of responding retailers and suppliers say their technology investments are already yielding returns, which is encouraging but leaves a large share that cannot yet make that claim. That split mirrors what other cross-industry surveys have found, where enthusiasm for AI outpaces demonstrated revenue impact. For a sector spending 2 percent of sales on technology, the difference between a majority and a supermajority reporting returns is worth real money, and it is the number executives should watch in next year's edition.
The honest read for a retail CTO is that the sector has bought in faster than it has proven out. That is a normal phase in a technology transition, but it carries risk when budgets are this large and margins this thin. The operators who convert spend into return will be the ones who tied each investment to a specific operating metric, out-of-stocks, shrink, labor hours, or basket size, rather than funding broad AI initiatives on faith. The report's real message is that the spending decision is settled, and the discipline decision, proving return on it, is where competitive advantage now gets made.
Talent follows the budget
The spending has a workforce consequence that leaders should plan for now. More than half of surveyed retailers anticipate increased staffing for AI-related roles such as data analytics and digital technologists. That is a notable statement from an industry better known for cashiers and stockers than for data scientists, and it will collide with a tight market for exactly those skills. Grocers competing for analytics and machine-learning talent against technology firms and better-paying sectors face a real constraint, and the ones who solve it will likely rely on a mix of hiring, partnerships, and upskilling rather than recruitment alone.
For technology leaders, the talent signal is as important as the spending figure. A 20-billion-dollar technology budget produces little return without the people to design, deploy, and operate the systems it buys. The gap between capital committed and capability in place is where many grocery AI programs will stall. The practical response is to treat talent as a first-order constraint in the roadmap: decide which capabilities must be built in-house, which can be bought as managed services, and where a vendor relationship substitutes for a hiring plan the labor market will not support at the pace the budget assumes.
Conversational commerce is the next line item
The report also captures where grocers think the customer-facing shift is heading. Nearly one in five food retailers anticipate that conversational commerce will reshape how people shop. That aligns with the wave of shopping assistants and shopper agents launching across the industry, from grocery cart builders to retailer-branded assistants wired into large language models. A fifth of the sector naming conversational commerce as transformative is early-majority signal, enough to indicate direction without yet being consensus, which is precisely the stage where an operator can still build a lead before the capability becomes table stakes.
The implication is that grocery technology roadmaps now need to account for a new front-end paradigm alongside the back-office AI already in flight. Conversational interfaces change how catalog data, inventory truth, and personalization must be structured, because an agent answering a shopper needs clean, machine-readable product information and a live read on availability. That connects directly to the shelf-intelligence and data-quality investments elsewhere in the sector. Grocers treating conversational commerce as a standalone chatbot project will underinvest in the plumbing that makes it work, and the plumbing is where the competitive difference will show up.
How to read this against your own budget
For a retail technology leader, this report is a benchmark to hold your own plan against. If peers are spending close to 2 percent of sales on technology and two-thirds are running AI, an operator materially below those levels is making an implicit bet that its other advantages will cover the gap. That bet may be sound, but it should be deliberate rather than the accidental result of underinvestment. The value of a 42,000-store data set is that it lets you calibrate your spending and adoption against the sector rather than against a handful of headline-grabbing competitors.
The sharper use of the data is to separate the two decisions it exposes. The first, whether to spend heavily on technology and AI, the sector has already made, and lagging it is increasingly hard to justify. The second, how to convert that spend into demonstrated return, remains genuinely open and is where advantage is available. Leaders should benchmark their spending against the sector to avoid falling behind, then compete on the return metric where most peers have not yet proven themselves. The budget question is settled. The execution question is the one worth your attention.
