The emergence of AI in restaurant industry

IA: definitions and data

Sam Altman, CEO of OpenAI, announced last week that ChatGPT now boasts over 100 million weekly active users. The observation is simple: AI is being used everywhere and by everyone. But if AI intrigues as much as it frightens, it's hard to understand what the term really encompasses.

In this article, Adoria explains the emergence of Artificial Intelligence in restaurant chains and community catering.

Definition and context of artificial intelligence (AI)

To understand artificial intelligence, let's start with its definition:

"AI is a discipline (..) that brings together sciences, theories and techniques (including mathematical logic, statistics, probability, and computer science (...)) whose goal is to achieve the imitation of a human being's cognitive abilities by a machine.

Specialists (...) are sometimes reticent to use the term "intelligence" because the results, while extraordinary in certain fields, are still modest in relation to the ambitions nurtured."(1)

Concretely, today's AI is a set of algorithms, not a machine capable of thinking or replacing humans.

It's important to understand that today's IA is devoid of certain characteristics of human intelligence such as sensitivity, consciousness and willpower. Strong" artificial intelligence, in theory (or in science fiction), would be endowed with these characteristics to perfectly reproduce human intelligence. We're a long way from achieving this in reality.

Artificial Intelligence is a discipline born in the 50s that went through a long "crossing of the desert", before coming back to impose itself on a large scale in the early 2000s.

This type of program has therefore been used for some time by professionals in various sectors, including restaurant industry: for example via fill rate forecasting functionalities, particularly in community catering.

Distinguishing between AI, machine learning and datamining

Artificial Intelligence, Machine Learning, datamining... it's hard to find your way around these terms, sometimes used interchangeably even though they don't cover exactly the same thing.
Adoria offers you the chance to understand what they mean so you can use them more effectively:

• IA: this is the discipline that aims to create programs capable of simulating human intelligence, based on algorithms.
  
  
• Machine Learning (ML) : this is a subset of AI. Computers learn from data and improve through experience, unlike programming, which executes predetermined rules to the letter.
  For example, ML can make sales forecasts and will refine its results over time.
  
  
• Data mining: this is not AI but a process of analyzing massive volumes of data and Big Data from different angles, in order to identify relationships between data and transform them into usable information. This device falls within the scope of Business Intelligence. It is often coupled with Machine Learning.

At Adoria, we use AI through Machine Learning. Imagine the power of our twenty years of data in the restaurant industry, coupled with the functional richness of our tool? We bring a more precise vision to our customers with Machine Learning fleshed out by all our data and experience.

Data, a foundation for AI

It's important to emphasize one point: AI is nothing without your data.

Big data (storing and processing large amounts of data) has been a gas pedal for artificial intelligence, for which it forms the foundation.

AI feeds on your data, so it's necessary to restore it to feed your tool and give it the keys to understand consumer habits or anticipate requests.

The stakes of data for the use of AI

In restaurant industry, you have countless data collected related to your business or your customers.

It's this ecosystem of data that will enable AI to work.

The emergence of AI in the foodservice technological landscape

Organized catering has always been able to take advantage of new technologies. The advent of artificial intelligence, for example, enables prediction. Indeed, AI will come to interpret and adapt its results according to the data it gathers in real time.

But before AI, how did we do it? Here are a few historical reminders of the main digital revolutions.

Some historical reminders

You don't have to look far to find examples of technological revolutions. In particular, it was thanks to its formidable power of resilience that the restaurant industry was able to adapt to the Covid crisis. In an emergency, delivery platforms and click&collect have been developed to adapt offers to demand and restrictions.

Other innovations include POS cash registers, smartphone ordering and payment, CRM to keep abreast of customer habits, and ERP systems to manage the activities of catering groups.

Digitization, automation... all these technological revolutions have shaped the landscape of organized catering. They have led to AI and its system of algorithms, which seem to be the solution for refining predictions.

Using AI wisely

At Adoria, we think it's important to put artificial intelligence into context: it's a fantastic tool, but we mustn't bet everything on it.

Catering is a hands-on business, and it's the restaurateurs and all the players involved who are the experts. Adoria proposes to use AI as an aid to the restaurant professions, and in no way to replace these professionals.

The emergence of AI

Contrary to popular belief, AI did not suddenly appear in the restaurant industry. It has been in the research and experimentation phase for around ten years.
Functionalities are evolving and gaining in precision. For example, Adoria proposed its first version of sales forecasting 10 years ago.

But in concrete terms, what are the possibilities with AI?

Examples of applications in restaurant industry

Here are a few notable examples of AI applications and functionalities.
Over the next few articles, we'll explore others.

• Chatbot: virtual assistants on websites can answer questions and even take reservations ;
• Dynamic pricing: to adapt rates according to footfall. For example, offer a 20% discount on delivery orders (Ubereats or Deliveroo) to improve sales in real time.
• Sales forecasting: based on historical data, promotions or events outside your restaurant (such as the weather);
• Production forecasts;
• Consumption and stock forecasts to limit shortages or losses:
• Suggest dishes to customers based on their habits and preferences;
• ChatGPT: for writing menus, improving recipes, analyzing customer opinions and responding ;
• Voice commerce: still in the experimental phase, some restaurants are testing it to take reservations or menus. Some chains are also experimenting with conversational robots in their drives to optimize time, reduce errors and increase sales.

In our view, AI is a tool to assist restaurateurs and simplify their tasks, not a super-powered software program designed to replace them. But as you can see, the possibilities are immense, and we're only at the beginning of its use.

In the next articles in this white paper, you'll discover how to use artificial intelligence in your restaurants.

(1) Source : Council of Europe : https://www.coe.int/fr/web/artificial-intelligence/what-is-ai
(2) Source : https://gmggroup.org/how-are-ai-machine-learning-big-data-deep-learning-and-data-science-interconnected/