Fresh Perspectives Q&A: How Automation, AI, and Connected Systems Are Shaping Fresh Food Operations

It is an exciting time in fresh food operations. As purpose-built technology for this space becomes more widely available and more advanced, food retailers and foodservice operators are rethinking how fresh is planned, produced, and executed at scale. The recent launch of Logile’s Fresh Operations Management suite is helping drive this shift forward with a unified platform designed around how fresh environments actually work.

Built on the coordinated principles of customer demand, labor-aware execution, and true cost visibility, this platform brings together Demand-Driven Fresh Production, Fresh Margin & Waste Control, Inventory Replenishment, and Food Safety & Fresh Compliance solutions that have traditionally been managed in isolation, and it continuously aligns these elements throughout the day under a single, coordinated operating model.

This ongoing investment in Fresh Operations Management reflects what we are seeing firsthand across the market: a growing recognition that fresh cannot be managed effectively with disconnected processes, manual decisions, or lagging data. To explore this further, we asked Logile’s Alicia Napomoceno, Senior Product Management Director of Fresh Operations, to share her perspectives on how automation, AI, and emerging technologies are reshaping the category, along with key observations on where the industry is heading next.

Q: Automation continues to gain momentum across industries. How do you see adoption evolving in food retail and foodservice?

Napomoceno: We expect retail and foodservice automation to accelerate further in 2026. Although much of the media headline focus remains on customer-facing robotics, some of the highest-ROI advances are emerging in back-of-house fresh food operations—specifically in how production is planned, scheduled, and executed—around a unified demand signal.

A fast-growing area is solutions like Logile’s Fresh Operations Management, which equips store teams to fulfill customer demand with precise quantities and timely production, with consistently high freshness and flavor. By combining demand forecasting with real-time sales and inventory, these systems generate precise, time-phased production guidance that helps associates prepare only what is needed as demand unfolds for less waste and fresher products available throughout the day.

We also expect broader automation of daily operational tasks as retailers contend with rising complexity and persistent labor constraints. Modern platforms can now dynamically coordinate work across departments, ensuring:

·      Critical tasks are sequenced and completed on time

·      Item availability and freshness remain consistently high

·      Departments stay clean, stocked, and audit-ready throughout the day

·      Teams spend more time serving customers and less time on manual tracking or guesswork

This operational automation improves execution and consistency especially in fresh departments with recent emphasis on “Made to Order,” where timing and quality directly shape customer trust and repeat purchases.

As labor markets tighten and customer expectations continue to rise, systems with these capabilities will shift from “nice to have” to essential. Fresh production is too perishable, variable, and timing-dependent to manage manually at scale. These tools enable data-driven, real-time production decisions that keep shelves full without overproduction, protect freshness standards, and reduce labor strain. In 2026, retailers and foodservice operators that adopt this level of automation will be best positioned to deliver reliable quality, minimize waste, and sustain a competitive edge in an increasingly demanding market.

Q: How have you seen AI impact operations for food retailers in 2026?

Napomoceno: What is most exciting is how AI is moving beyond theory in fresh operations to deliver real, day-to-day operational value. In our development and work with food retailers, we have already seen its transformational potential in action. In our experience, the evolution of Logile’s own AI-powered fresh operations suite continues to push the boundaries of what is possible. Food retailers can now generate high-accuracy, item-level demand forecasts and automatically convert them into executable store production plans, including labor allocations, start times, batch sizes, and bake/produce sequencing.

This enables associates to produce the right items at the right time, in the right quantity, and in the right order, maintaining peak freshness and consistent quality while minimizing waste. Forecasts are continuously refined using historical sales, seasonality, promotional uplift, customer purchasing trends, and localized weather inputs, keeping production aligned with near-real-time demand.

Ultimately, profitability improves through reduced waste, fewer out-of-stocks from underproduction, lower shrink from overproduction, and faster, smoother flow from prep to shelf. AI turns fresh production from a schedule-and-compliance task into a standardized, repeatable workflow that embeds proper handling, storage, and food-safety process controls, protecting product integrity at every step.

By tightly matching output to demand and optimizing labor and ingredient utilization, AI reduces unit cost and safeguards margins so retailers can consistently offer the fresh items customers want, at a cost that sustains profitability.

Q: What other technology do you think could significantly impact the food industry?

Napomoceno: In 2026 and beyond, a high-impact technology for food retail and foodservice will be camera-based computer-vision systems deployed on shelves, prep areas, and service lines. These systems continuously interpret live video to quantify facings and product levels, flag stock-outs or low inventory within minutes, and capture true product movement rather than relying on periodic manual counts. Retailers are already scaling “shelf-AI” cameras for real-time availability and waste reduction, showing the technology moving from pilots to broad deployment.

That real-time visibility makes fresh-food optimization platforms like Logile’s materially stronger. Instead of waiting for lagging sales or inventory updates, vision feeds current on-hand, shelf gaps, and pickup velocity directly into forecasting and execution. The system can then reforecast intraday, recompute batch sizes and start times, and shift labor to the departments or dayparts showing unexpected demand to tighten the plan-to-produce loop from hours to minutes.

At the same time, foodservice is continuing its shift toward made-to-order and short-run fresh offerings, which raises the cost of forecast error and makes labor timing critical. We addressed this in our fresh operations technology using historical patterns plus real-time demand signals to produce time-phased production guidance (what to make, when, and in what quantity). When paired with vision, the guidance becomes adaptive: if cameras detect faster-than-expected sell-down or a sudden queue surge, the platform can trigger an immediate make-more decision, reprioritize items in sequence, and recommend labor adjustments to prevent outages without overproduction.

Together, camera-based vision and AI production planning create a closed-loop fresh-operations stack: vision captures what is happening now; forecasting predicts what will happen next; and production/labor optimization executes the lowest-waste, highest-availability response. The outcome is higher on-shelf availability and service-line readiness, lower shrink, and consistently fresh product delivered with less manual checking and fewer labor fire drills.

A New Chapter for Fresh Operations

Rapid advances in automation, AI, and supporting technologies mark a fundamental shift in how fresh operations are approached and executed, making this moment especially compelling as food retailers and foodservice operators work to meet growing customer needs and business goals. No longer constrained by disconnected processes or reactive decision making, fresh operations can move toward a more coordinated, demand-driven approach that improves availability, reduces waste, and strengthens financial performance across departments.

And with the introduction of Logile’s Fresh Operations Management suite, retailers now have access to a truly connected model that aligns demand, labor, inventory, waste, and food safety within a single, continuously adaptive system that helps transform fresh operations into competitive advantage.

As industry innovation accelerates and adoption expands, the opportunity ahead is significant. For retailers looking to scale fresh, differentiate their offering, and operate with greater precision and confidence, this is an exciting time to explore what is now possible in fresh operations.

Learn more about Logile Fresh Operations Management or request a demo today.