Chat-to-basket: supplier actions for AI in AFH

During a recent visit to Food & Hospitality Asia 2026, the region’s largest food and drink trade show, our analysts explored the latest trends and technologies shaping away from home markets in Asia.

While there were many innovations, what stood out most was how operators are innovating with artificial intelligence (AI) to create efficiencies and improve consumer experiences at pace.

For example, Yum! Brands owner of KFC, Pizza Hut, Taco Bell and Habit Burger & Grill,]
is partnering with NVIDIA to fast-track its development of AI technologies across 61,000 global restaurants, including over 1,500 in the UK.

Although some operators, such as PizzaExpress, Pizza Pilgrim’s and Just Eat, are experimenting with AI in the UK and Europe, high investment costs, scalability, and consumer acceptance are slowing wide-scale adoption.

As AI development in Asia continues to evolve at a pace, UK away from home operators and suppliers can learn what AI technology is likely to succeed and how to prepare.

This article identifies three key ways AI is shaping the UK away from home market.

• Conversational ordering.

• Enterprise-level AI assistants.

• Forecasting and inventory management.

Conversational ordering: streamlining consumer ordering experiences

How suppliers should respond: Make your products easy for AI to surface and select, ensuring all product data is structured, comparable, and aligned to common consumer goals, such as price, health, and convenience.

Yum! Brands’ NVIDIA partnership is improving its automated voice-activated ordering at a pace. In just three months, it developed a conversational AI that can understand speech, navigate complex menus, and personalise orders in real time.

While the technology promises faster service, fewer errors, and lower labour costs, rollout has been slow, with reliability issues and consumer friction slowing adoption.

As a result, AI is gaining stronger traction in written environments – our Agentic AI report shows seven in 10 shoppers have acted on AI recommendations, and 58% now use AI tools for product discovery.

Just Eat is responding by launching AI-powered ordering via WhatsApp in Norway and Spain, enabling “chat-to-basket” journeys. By embedding AI in familiar, digital-first channels, it requires little behavioural change, lowering a barrier to widespread use.

As our delivery aggregator report highlights, four in 10 consumers already order food and drink on delivery apps at least once a month. Although voice AI may be struggling to take off, the widespread use of delivery apps and familiarity with text AI indicate that consumers are likely to widely adopt text-based conversational ordering.

Enterprise-level AI assistants: creating staffing and training efficiencies

How suppliers should respond: Support lower staffing levels with low, easy-to-make options, such as ready-to-pour drinks or pre-portioned sauces and condiments. At the same time, ensure product data is up to date and aligned with operator AI systems with support for automatic updates.

AI is increasingly being used to support in-store decision making, helping operators streamline labour scheduling, inventory management and food quality control in real time.

Tools, such as KFC China’s Q-Smart and Pizza Pilgrim’s “Joshua”, highlight how operators in Asia and the UK are shifting towards enterprise-level AI assistants that allow teams to access operational insights quickly and hands-free, improving speed and consistency in execution.

Rather than replacing decision-makers, these tools are giving managers immediate access to guidance on staffing, performance, and preparation, while evolving towards more real-time analytics that support faster, more informed decisions at a site level.

Forecasting and inventory management: increasing accuracy and reducing waste

How suppliers should respond: suppliers will need to make strategic choices about how to support AI forecasting systems, whether by building their own capabilities, partnering with operator platforms, or integrating with third-party ecosystems.

Yum! Brands is using AI to improve forecasting accuracy and reduce waste. Its Byte platform is enabling faster, data-driven decisions by combining real-time inventory and demand signals.

Pizza Express is adopting a similar approach, using AI to optimise stock levels, control costs, and improve consistency while freeing up staff time through more efficient purchasing, preparation, and menu management.

Experimentation to execution

AI is quickly moving from experimentation to execution, with Asia demonstrating how quickly it can be embedded to unlock both efficiency and scale. Rather than replicating every use case immediately, UK operators should focus on where adoption is most commercially viable, particularly in digital-first ordering, frontline decision support, and data-led forecasting.

What stands out is that AI is already shaping how decisions are made, products are discovered, and operations are run. Success will depend less on the technology itself and more on how well it fits with existing behaviours and systems.

This raises the stakes for suppliers, with visibility in AI environments, data readiness, and alignment with operator platforms increasingly determining the share of demand. Supporting simple execution and aligning with AI-driven forecasting will also be critical.

As AI adoption accelerates, those who act early to align their data and partnerships will be best placed to capture value. Those who lag risk being excluded from increasingly AI-driven decision-making processes and consumer journeys.