AI is now embedded in airport foodservice. It powers forecasts, schedules, inventory and guest engagement. In a recent webinar hosted by Nation’s Restaurant News, executives shared data showing adoption is gaining ground across all segments. Operators use it to tighten planning, boost margins and stay ahead of shifting demand.
According to data presented by the media organization, one in three foodservice operators already use AI in at least one function, and nearly half expect to adopt it this year. Chain operators lead the trend, but independents show equal drive. Among those with AI in place, more than 80% plan to invest further over the next twelve months, and 63% expect to expand staffing to support these tools.
Operators who adopt AI identify early benefits across five areas. The data – gathered from surveying nearly 500 restaurant industry leaders – showed that 44% see improved data reporting and analysis and 34% highlight time savings for hourly teams. Forecasting, inventory accuracy and menu optimization follow close behind. The common thread is sharper decision-making. For airports specifically, in an environment where schedules shift and demand spikes with every new gate call, these tools let operators adjust quickly.
Forecasting has become the foundation, Nation’s Restaurant News revealed, with 44% of operators believing AI-based forecasting leads to some profit growth and 31% expecting a major profit lift. Teams use the forecasts to shape labor schedules, inform marketing and refine procurement. When a prep schedule adapts to an early bank of flights or a sudden weather delay, that flexibility turns into margin.
Return on investment appears in two forms. One is efficiency: smarter schedules, lower waste, fewer hours lost to manual tracking. The other is growth: better loyalty offers, stronger menus, pricing that adjusts to what travelers actually order. In airport dining, where throughput and experience carry equal weight, AI allows both to move forward.
The data showed five key areas of AI application by restaurant organizations, including:
- Inventory and prep forecasting: Six in ten operators use AI to guide inventory. A similar share apply it to back-of-house labor planning. The results include less shrink, better product availability and smoother transitions between service periods.
- Menu strategy and pricing: More than half of operators rely on AI to analyze item performance and pricing. These systems flag margin erosion and track substitution trends. Adjustments happen before problems appear on the balance sheet.
- Labor and scheduling: Over 50% of operators now use predictive scheduling that aligns labor with traffic patterns. In airport units that means schedules flex to match departure banks and dwell-time surges.
- Marketing and personalization: 71%t of operators use generative AI to speed up marketing content. More teams also apply it to create targeted messages based on time of day, location and traveler behavior.
- Data consolidation and visibility: 65% have integrated AI into their reporting stack. This turns multiple feeds into one view. Field managers spend less time gathering data and more time acting on it.
Building AI Knowledge
Most companies begin by training their existing employees, according to the feedback given to the media organization. This approach supports continuity especially in airport operations where hiring involves credentialing and secure-area access. Leaders also cite partnerships with vendors and selective hiring as part of the strategy. Operators report clear improvements in forecasting, scheduling and visibility. They point to faster workflows and stronger alignment across departments.
The areas flagged for improvement include integration with existing systems and establishing one shared source of data. Operators who navigate these challenges successfully tend to start with small pilots, use results to build support and expand only after early success.
Staffing plans reflect long-term confidence, webinar participants said. A majority of operators expect to maintain or grow hourly headcount. Rather than replace roles, AI shifts them. Tasks like logging inventory, managing compliance records and assembling reports move into automated systems, allowing teams to spend more time on service.
Applying AI In Practice
Data from the field show five practical ways airport foodservice teams apply AI today. They reflect decisions already working for operators in both large chains and independent concepts, including:
- Forecast by daypart: Combine flight schedules, historical sales and event calendars to build sharper demand projections, and use these to adjust prep, labor and inventory.
- Automate inventory management: Six in ten operators use predictive tools to generate restock orders based on usage. The result is less waste and stronger product availability.
- Refine a menu strategy: AI helps identify which items carry strong contribution margins and which show early signs of drag, allowing operators to adjust before performance declines.
- Simplify operational visibility: 65% of operators use AI to combine labor, cost and supply data into one dashboard. Managers get a full view without chasing spreadsheets.
- Streamline administrative work: Compliance tracking, reporting and routine logs now shift into AI-supported systems, freeing up time for coaching teams and engaging customers.
Operators with high return on AI tend to follow four shared practices, the webinar participants suggested. They advised starting small with focus on a clear financial upside, then using those wins to support expansion. They also suggest investing in existing team members to leverage operational knowledge and piloting a small AI rollout before expanding across a restaurant portfolio.
Across use cases, operators cite improved clarity, saved time and better decision support. Many say the greatest value lies in helping teams do their work with less friction.
Marketing teams also report success. More than two-thirds now use AI tools to generate content and tailor guest messaging. Kitchens benefit as well. AI-powered prep forecasting reduces overproduction and allows for leaner, more accurate inventory management.
Satisfaction is highest with AI tools that support forecasting and scheduling. These are the areas where operators see direct gains in labor planning and service consistency. The strongest implementations also handle the known challenges. Operators address integration and data alignment by setting narrow goals, measuring outcomes and refining systems in pilot before scaling.
