The State of AI in Grocery Facilities Management: Trends and Predictions for 2026 & Beyond

Too many grocery facilities and operations teams spend their days trapped in reactive cycles — chasing work orders, filling out forms, coordinating vendors across large store networks, and responding to critical equipment failures that directly threaten food safety and revenue. These teams are left with little time for strategic thinking about rising operational costs, shrinking labor pools, tightening margins, and rapid technological change across the grocery industry.

Artificial Intelligence is helping grocery facilities professionals break out of these cycles. In just a few short years, AI has moved from theoretical promise to practical application, delivering measurable impact on store uptime, food safety compliance, energy efficiency, and operational consistency. Early adopters report that AI has fundamentally changed how grocery operations and facilities teams approach daily work.

According to Fexa CEO Kurt Smith, “AI is a fundamental paradigm shift for facilities management. The productivity and efficiency of the industry is going to 10x in the next five years.”

This transformation is already underway. The question for grocery and food retail facilities leaders is no longer whether to adopt AI, but how to implement it effectively and responsibly. At the Fexa Flex: AI Roadshow event on September 30, 2025, in New York City, executives from grocery, retail, and multi-site brands shared insights into how AI is reshaping operations and how they are leading adoption across complex store portfolios.

What’s driving the rise of AI in grocery facilities management right now?

Three converging factors have created ideal conditions for AI adoption in grocery facilities and operations environments.

1. Cloud infrastructure providers such as Amazon Web Services, Microsoft Azure, and Google Cloud have made advanced computing resources accessible at scale. Grocery chains no longer need massive capital investments in on-premise hardware to deploy AI across hundreds or thousands of stores.
2. Advanced language models developed by companies like OpenAI and Anthropic can understand and generate natural language, enabling conversational interfaces that are intuitive for store managers, facilities teams, and technicians without technical training.
3. Consumer-grade AI tools have democratized access to AI. What once required specialized software and expertise is now available through simple chat and voice interfaces. This aligns closely with how grocery store teams already report issues from the floor: quickly, informally, and often during high-traffic periods.

AI itself is not new. The term “artificial intelligence” was coined in 1956, and machine learning gained traction in the 1990s. What’s different today is widespread adoption and real-world application. Bill Gates has compared ChatGPT’s significance to the personal computer and the internet—technologies that transformed access to information.

Just as smartphones made digital tools intuitive and ubiquitous, conversational AI is making sophisticated facilities technology approachable for grocery teams managing refrigeration uptime, energy costs, vendor coordination, and regulatory compliance.

The urgency behind AI adoption in grocery operations

The pressure on grocery facilities teams is measurable and immediate. Data shared at the Fexa Flex AI Summit highlights challenges that grocery operators face daily:

• A single refrigeration failure can lead to product loss, food safety risk, and lost customer trust
• Skilled trades face approximately 20 job openings for every new hire, increasing response times for refrigeration and HVAC issues
• Non-compliance with EPA refrigerant regulations can result in fines of up to $60,000 per day
• Grocery operators often capture only 60–70 cents of value for every R&M dollar spent due to inefficiencies, duplicate dispatches, and reactive maintenance

At the same time, AI adoption is accelerating rapidly. Gartner predicts that 33% of enterprise software will include agentic AI by 2028, up from less than 1% in 2024, and that 85% of enterprises will implement AI agents by the end of 2025.

Grocery brands that adopt AI are responding faster to equipment issues, protecting cold chain integrity, reducing waste, and delivering more consistent in-store experiences across locations.

The accessibility breakthrough and the responsibility it creates

AI has reshaped expectations for how grocery teams interact with technology. Store-level staff increasingly expect systems that understand natural language and deliver direct answers rather than requiring navigation through complex menus or rigid forms.

However, this accessibility introduces new risks. At a recent Fexa event, Brian Haines, Senior Director of Strategy and Business Development at Johnson Controls and an IFMA Top Global FM Influencer, illustrated this balance with a personal story. When his donkey experienced a medical emergency late at night, Haines consulted ChatGPT for immediate guidance, but did not act on that advice alone. He also consulted a veterinarian and an experienced neighbor.

“I didn’t fully trust the AI answer with an animal’s life,” he explained. His guidance was clear: “Always, always check your results.”

For grocery operators, this lesson is critical. As AI becomes more confident and conversational, teams must ensure that AI recommendations, especially those affecting food safety, compliance, or major financial decisions, are validated by humans.

How is AI changing grocery facilities work day-to-day?

The most immediate impact of AI in grocery environments is in work order management.

Traditional CMMS platforms require store managers to complete structured forms, often while balancing customer traffic and operational demands. AI-powered systems replace these forms with conversational interfaces.

A grocery store manager can now type or speak naturally:

“The walk-in freezer in aisle three isn’t maintaining temperature.”

The AI agent gathers additional context, identifies the appropriate trade, checks warranty status, detects duplicate issues, and routes the work order to the optimal service provider automatically.

As Kurt Smith explains:

“Forms are dead. AI is replacing them with seamless, chat- and voice-based experiences.”

This shift eliminates administrative busywork while improving data quality for facilities teams.

AI also supports technicians by referencing historical maintenance data, equipment specifications, and prior resolutions across similar stores. This reduces repeat service visits and improves first-time fix rates which is critical for protecting perishable inventory.

Duplicate work orders (which are common when multiple employees report the same refrigeration or HVAC issue) are automatically detected, preventing unnecessary truck rolls and wasted labor. In some cases, AI can identify issues that store teams can resolve safely without dispatching a vendor.

Why data and infrastructure are critical to AI success in grocery

Here is an essential truth about working with AI: AI systems are only as effective as the data they rely on. Poor data hygiene leads to poor outcomes.

In grocery operations, this often means asset data spread across spreadsheets, inconsistent store records, and incomplete maintenance histories. AI cannot deliver accurate insights if years of refrigeration, HVAC, and energy data are fragmented or missing.

Structured data (such as asset IDs, store numbers, and service dates) is easy for AI to process. Unstructured data, including technician notes, photos, invoices, and emails, contains valuable context but must be centralized and accessible. Modern AI excels at extracting meaning from this unstructured information when it is properly connected.

Building data lakes for AI applications

Centralized data repositories, often referred to as data lakes, provide a foundation for AI success. These environments bring together work orders, sensor data, energy usage, and vendor performance metrics.

Brian Haines described how Johnson Controls deployed hundreds of thousands of occupancy sensors globally, generating data streams far too large for humans to process, but ideal for AI analysis.

Interoperability is essential. Grocery chains often operate disconnected systems: refrigeration monitoring, CMMS platforms, energy management tools, and vendor portals. AI requires integration layers that normalize this data into consistent formats. Without this foundation, even advanced AI tools fail to deliver value.

What problems is AI actually solving in grocery facilities today?

AI is already solving real problems in grocery facilities management, including:

• Automated work order creation that reduces manual entry
• Fault detection and diagnostics for refrigeration and HVAC systems
• Energy optimization based on occupancy, weather, and rate structures
• Occupancy analytics to optimize store layouts and labor planning
• Sentiment analysis of post-service reviews
• Speech recognition for hands-free technician updates
• Visual inspections using image recognition
• Automated vendor dispatch based on warranty and performance history

These use cases are delivering tangible efficiency and cost savings today.

How are grocery brands turning AI into real ROI?

AI adoption requires disciplined ROI evaluation. At the Fexa Flex AI Roadshow, Tarik Makota of Amazon Web Services introduced the DVF model (Desirability, Viability, and Feasibility) to assess AI investments.

While some use cases may be technically possible but economically impractical today, many grocery-focused applications, especially those tied to refrigeration uptime, waste reduction, and labor efficiency, are already generating strong ROI.

Identifying high-value AI use cases

High-impact AI use cases in grocery operations typically:

• Consume significant staff time without requiring deep expertise
• Occur frequently across stores
• Have clear, measurable outcomes

Kurt Smith describes Fexa’s approach as “pattern matching”: adapting proven AI solutions from other industries to grocery-specific challenges. This reduces risk while accelerating time to value.

What does agentic AI mean for grocery facilities operations?

Agentic AI moves beyond automation into systems that can reason, decide, and act.

Instead of routing all refrigeration issues to a default vendor, an agentic system evaluates the asset, warranty status, vendor performance, urgency, and workload, then selects the best provider for that specific situation.

Multi-agent systems represent the next frontier, with specialized agents handling refrigeration, energy management, vendor performance, and capital planning in coordination.

How are grocery buildings becoming more autonomous?

Smart building systems are already reducing manual intervention. AI-enabled controls can adjust refrigeration loads, HVAC settings, and lighting in real time based on occupancy and performance data.

While AI won’t physically repair equipment, it can make thousands of micro-adjustments that reduce energy usage, prevent failures, and extend asset life.

The role of humans in an AI-driven grocery environment

Despite rapid advances, human oversight remains essential. AI can recommend actions, but people must validate decisions involving food safety, compliance, and significant financial impact.

Kurt Smith emphasizes that AI is about empowerment, not displacement. As with ATMs in banking, AI shifts human focus toward higher-value, strategic work rather than eliminating roles.

Adopting AI responsibly and securely

Responsible AI deployment requires transparency, audit trails, and strong data privacy protections—especially as grocery operators deploy sensors and collect operational data at scale.

Engaging employees early and positioning AI as an augmentation tool builds trust and adoption. Starting with pilot teams allows organizations to learn and iterate before scaling.

Where is AI in grocery facilities management headed next?

Kurt Smith predicts a tenfold productivity increase within five years. The next evolution will involve holistic facility agents operating across entire grocery portfolios—ingesting data from refrigeration systems, maintenance records, energy usage, and asset performance.

Future AI will be multimodal, integrating text, voice, images, and video. A store manager could photograph a malfunctioning freezer, and the AI would identify the asset, diagnose the issue, and create a fully contextualized work order instantly.

As grocery stores continue evolving to meet changing customer expectations, AI will provide the agility required to adapt efficiently and consistently.

The AI era is here

“We’ve fully shifted into the AI era,” Kurt Smith states. “The tools built decades ago weren’t built for this new world—full stop.”

Grocery brands that embrace AI will unlock significant gains in efficiency, compliance, and cost control. Those that delay risk falling behind competitors who are already transforming operations.

Ready to transform grocery facilities operations with AI?

Fexa’s AI-powered platform helps grocery brands eliminate busywork, reduce downtime, protect food safety, and optimize spend across every store. From conversational work order creation to intelligent vendor routing and duplicate detection, FexaAI delivers the productivity gains defining the next era of grocery facilities management.

Request a demo today.