Artificial intelligence seems to hold almost endless possibilities for restaurants. Look at any part of a restaurant’s operation, from inventory to scheduling to hiring and even cooking, and you can probably find a job for AI.
But for now, operators say the technology has been most effective at improving the customer experience.
That’s according to "How AI Is Revolutionizing Restaurants," a new study from consulting firm Deloitte, which surveyed 375 restaurant executives in 11 countries about their thoughts on AI.
Restaurants said they’re using things like AI chatbots to handle reservations and address customer service issues, and machine learning to power upsells in mobile apps and kiosks. Some (13%) are beginning to use voice AI to automate order taking.
Overall, 60% of respondents said customer experience is where they see AI benefiting their business the most. It was by far the most popular response, followed by improving operations (36%) and enhancing loyalty programs (31%).
The study said it’s not surprising that customer experience topped the list, given the wide availability of things like chatbots and recommendation engines. Six in ten restaurants said they’re using chatbots, for instance.
Benefits could include higher check averages due to more consistent upsells, or the ability to respond faster to customer service issues by automating the process.
What the study did not explore is how customers feel about more AI in their restaurant experience. But other research has suggested that it’s a mixed bag. According to a DoorDash report published last month, 52% of consumers are open to receiving AI recommendations based on their past orders. And a survey last year by Mood Media found that more than half were comfortable placing their order with an AI bot.
But consumers also give AI little room for error: About a quarter said they’d be less likely to visit a chain after having a negative encounter with AI, according to Mood Media.
In the Deloitte study, restaurants’ outlook on AI differed somewhat by segment. Casual-dining brands are more focused on using AI as a customer experience aid, with 60% viewing that as the biggest benefit of the technology, compared to 48% for limited-service restaurants.
The study predicted that adoption will come in waves, with the first consisting of customer experience and inventory management tools. More than half (55%) of restaurants said they’re using AI to forecast product needs or track inventory today.
The next wave will relate to loyalty and employee experience, and the third will impact food preparation and product development.
That cadence was based on how restaurants are currently investing in AI and where they plan to invest in the future.
Surprisingly, the study found that casual-dining operators have been quicker to implement AI and also see more promise in the technology. About 55% of casual-dining brands are using it in customer experience today, compared to just over 40% of limited-service outfits. And about 45% are applying it to inventory, versus only about 25% of LSRs.
The study suggested this is because casual-dining operations tend to be more complex and service-oriented than their counterparts in fast food, and therefore have a bigger need for AI.
In general, there was enthusiasm for AI and a willingness to keep investing in it. Nearly three-fourths (73%) of all respondents said they plan to increase their AI spending somewhat this year, while 9% plan to make a significant investment.
At the same time, a significant percentage of restaurants believe they still have work to do before they’re ready to adopt AI more broadly.
About 80% cited concerns about risk and governance, three-fourths said they need more talent, and more than 70% feel they don’t have the right tech infrastructure in place. More than half said they need to get their operations right first, and a little less than 40% don’t have a fully fleshed-out strategy.
A slightly different question asked what was holding operators back from adding more AI. About half said they’ve had a hard time identifying use cases, and the same amount said they’re struggling to manage risks, such as the misuse of customer data. A slightly smaller group said they lack the technical talent and skills to handle more AI.
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