Research: 70% of Restaurants Either Actively Using or Piloting AI to Boost Loyalty Programs |

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The global artificial intelligence (AI) market is expected to more than double in the next four years, growing from $235 billion in 2024 to more than $631 billion by 2028. How much of that growth will be fueled by the restaurant industry? Quite possibly a significant portion, according to Deloitte’s State of AI in Restaurants Survey. The global study—based on interviews with 375 restaurant executives across 11 countries—finds that restaurants are increasingly leveraging AI to improve customer experience, optimize operations, and build long-term competitiveness.

According to the report, a vast majority (82%) of restaurant leaders expect to increase their investment in AI over the next fiscal year. Only 2% anticipate any kind of reduction. This indicates that AI is being viewed as a strategic imperative, not just an operational add-on.

When asked to identify expected benefits of AI adoption, 60% of respondents cited improved customer experience as their top priority. Other leading benefits include smoother restaurant operations (36%), enhanced loyalty programs (36%), and more efficient procurement and supply chain management (36%). A sizable minority also anticipate benefits in food waste reduction, digital marketing performance, crew engagement, and new product development.

Segment-level differences emerged in the analysis. Casual dining operators were significantly more focused on customer experience than their quick service (QSR) or fast casual counterparts. Regionally, respondents in the U.S. and Europe showed higher optimism around guest experience, while those in Asia more often pointed to automation and labor augmentation as top priorities.

Deloitte categorizes AI implementation in the restaurant industry as occurring in three waves:

First Wave – Core Operations:
- 63% of respondents report using AI for customer experience enhancements on a daily basis.
- 55% say the same for inventory management, supported by predictive analytics and IoT sensor integration.
Second Wave – Loyalty and Labor:
- About 70% of respondents are either actively using or piloting AI to boost loyalty programs and improve employee experience.
- In QSRs especially, AI is being tested for real-time crew scheduling and performance analytics.
Third Wave – Food Prep and Innovation:
- Fewer than 50% of restaurants currently use AI for food preparation or product innovation, but over 40% are in the planning phase.
- Use cases include AI-driven flavor profiling, quality inspection via computer vision, and automated test kitchen modeling.

Casual dining brands and restaurants in Asia lead in adoption across all three waves. U.S.-based respondents tend to lag behind in operational use cases but lead in customer-facing applications like conversational AI and voice ordering.

Deloitte’s data also points to growing usage of several specific technologies:

Chatbots: Used daily by 60% of restaurants, most commonly for online ordering, reservation management, and FAQ handling.
Machine Learning (ML): Used by 54%, typically for dynamic pricing, demand forecasting, and real-time guest analytics.
Natural Language Processing (NLP) and Intelligent Automation: Common in front-of-house functions like kiosks and drive-thru voice assistants.
Computer Vision: Deployed for food safety monitoring and order accuracy. Still largely in the pilot phase.
Generative AI: Actively used by only 9%, with another 25% in testing. Applications range from personalized menus to autonomous marketing content generation.
Avatars and Virtual Environments: Adoption remains low but interest is growing, especially among brands investing in next-gen loyalty ecosystems.

Despite enthusiasm and early wins, most restaurant brands admit they are underprepared for widespread AI deployment:

Only 1 in 5 respondents believes their organization is ready in terms of governance and risk management.
Less than 30% say they have sufficient infrastructure or technical talent.
Strategy is the most advanced area, with 60% feeling at least somewhat confident in their roadmaps.

Notably, restaurants already generating strong ROI from AI are more likely to report readiness in these key areas. Operators—especially large multi-unit franchisees—tend to report higher readiness than brand owners.

Among the top barriers to AI deployment:

Identifying the right use cases: More than 40% say this is the most significant hurdle.
Managing risk: A top concern for operators, particularly around guest data privacy and compliance.
Lack of technical talent: A widespread issue across all segments.
Regulatory compliance: Especially critical in markets with strict labor and data privacy laws.

Interestingly, lack of executive commitment or technology infrastructure no longer appears to be a top obstacle—suggesting that foundational buy-in has already occurred and that the focus has shifted to execution.

Respondents identified the following top AI-related risks:

Misuse of customer data
Algorithmic bias and lack of transparency
Inadequate cybersecurity

Still, 54% of leading companies report having an integrated AI risk management strategy. That number drops to 43% for everyone else. Moreover, fewer than half include vendor assessments in their risk protocols—an oversight that could lead to trouble as outsourcing and third-party tools proliferate.

Among the most widely adopted best practices by IT leaders:

Cybersecurity protections tailored to AI workloads
ROI tracking from pilot to scale
Bias auditing for AI model accuracy
Human-centered design for customer-facing applications

Interestingly, practices like model explainability and human-in-the-loop oversight are also gaining traction as part of an emerging AI ethics framework.

The Deloitte survey (available for download) reveals a restaurant industry that is both optimistic and pragmatic. AI is already reshaping how restaurants operate and compete—and those who invest wisely stand to gain significantly in efficiency, profitability, and customer loyalty. But readiness remains a concern. Technical debt, talent shortages, and governance gaps could stall momentum. To unlock the full potential of AI, restaurant companies must not only identify the right use cases but also ensure they have the infrastructure and capabilities to execute responsibly.

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