BURSTArtificial intelligence (AI) isn’t just disrupting how we work. It’s also going to revolutionize how we eat.
More and more industries and roles are adopting AI tools like ChatGPT to do their work more efficiently and unlock capabilities that they didn’t have before. Chefs, culinary professionals, and home cooks are no exception.
AI increasingly is being used in kitchens and restaurants to push the boundaries of what’s possible in the culinary arts. That includes using AI not only to brainstorm new recipes and reduce waste, but also to change the very nature of what and how we eat.
In the process, it’s opening up brand new horizons for chefs and foodies, though this brave new world isn’t without its share of risks.
Taking Kitchens by Storm
Today, AI is already having a big impact in kitchens and restaurants, experts say.
“AI is revolutionizing the culinary world in several innovative ways, making it more accessible and efficient for chefs and culinary experts in their day-to-day kitchen functions,” said Hyunsu Kim, a professor of resort and tourism management at the University of Macau.
One area where AI is having a big impact is inventory management.
AI systems can predict inventory needs based on historical data, current trends, and upcoming events, said Kim. That helps reduce food waste and optimize stock levels, ensuring kitchens are well-stocked without over-purchasing ingredients. Not to mention, tools that suggest recipes based on ingredients already on hand are gaining in popularity, both in home kitchens and in food service.
Another area where AI is starting to shine is food preparation. Here, advanced AI-powered robots and machines are starting to assist in repetitive tasks such as chopping, slicing, and mixing. This automation increases efficiency and consistency in food preparation, allowing chefs to focus on the more creative aspects of cooking.
But the biggest impact of AI right now may actually be in the art of cooking.
“Increasingly, chefs and culinary experts are using AI-based approaches to augment their creativity,” said Ganesh Bagler, a professor at the Indraprastha Institute of Information Technology, Delhi (IIIT-Delhi), in India.
More and more chefs are using AI tools like ChatGPT for inspiration. That includes using AI to beat creative fatigue by having it brainstorm new dishes or explore new ingredient combos. It also shows potential in recipe adaptation, particularly for dietary restrictions or cultural reinterpretations. AI can often quickly and easily modify a recipe for, say, a vegan diet. Or infuse it with the style and flavors of another cuisine.
That kind of creative jolt doesn’t just thrill chefs; it can also make them more successful. Giovannbattista Califano, a food researcher at Italy’s University of Naples Federico II, points to the example of a culinary director at fast casual restaurant Velvet Taco who used ChatGPT to help develop a successful weekly special.
“The AI suggestions helped stimulate new thinking, acting as a springboard rather than a solution,” said Califano. “At this stage, the most promising applications of AI in food are not about replacing chefs or food professionals, but about augmenting their creative processes.”
Food of the Future
The future of AI in food looks bright, too.
One area that has experts excited is the ability of AI to hyper-personalize and curate food experiences. Bagler is a pioneer in the field of “computational gastronomy,” which blends the culinary arts with data science and AI. Computational gastronomy essentially seeks to make food and culinary processes computable in ways that merge human cooking with AI. The discipline has led to the creation of structured, curated databases of recipes, along with their flavor attributes and health information.
“Along with computational algorithms, such datasets provide a vital tool for application of AI in culinary endeavors,” said Bagler. “AI models trained on large datasets of ingredients, recipes, and chemical flavor profiles can suggest novel ingredient combinations that may not be traditionally paired but have potential compatibility. This opens creative frontiers for chefs and mixologists.”
Computational gastronomy data is also used to improve food system sustainability by analyzing the environmental impact of ingredients, as well as to analyze the cultural and historical origins of recipes.
“I think we are moving towards building computable representations of food—structured, machine-readable models that integrate taste, nutrition, health, sustainability, and culture,” said Bagler. “This will form the foundation for intelligent food systems of the future.
That may look like AI that designs diets for specific medical conditions such as diabetes and gut health based on individual genetic and microbiome data, he said. Or we may see language models co-create recipes with sensory feedback loops. AI models are also getting better at predicting flavor outcomes which could accelerate research and development in food innovation, functional foods, and sustainable alternatives.
The Risks of AI in the Culinary Arts
Like anything related to AI, there are possible risks and downsides involved in using the technology to augment such a human process.
One potential downside is the danger of automation supplanting human agency, said Amit Zoran, a researcher at Israel’s Hebrew University of Jerusalem. When human creativity is ceded to AI, the authenticity and cultural depth of culinary work can be compromised, though Zoran is quick to note that this outcome is not inevitable.
Another risk is the technology itself. Many AI-generated recipes are still unreliable right out of the gate, said Califano.
“Common issues include missing quantities, incorrect sequencing, and unfamiliar or incompatible ingredients,” he said. “These failures undermine user trust and highlight the fact that AI does not yet grasp the tacit sensory and cultural knowledge embedded in cooking.”
That doesn’t just lead to food that tastes bad; it can cause serious safety issues. Califano cited the example of a supermarket app in New Zealand that suggested a recipe which, if followed, would have actually generated poisonous chlorine gas due to the recommended mix of ingredients. “While this incident stemmed from users deliberately entering inedible items into the system, it reflects the current limits of AI systems to reliably evaluate context, intent, and basic safety,” he said.
Also, AI models have biases in their training data. Many models rely heavily on English-language sources and Western cuisines, said Califano, which leads to a lack of cultural diversity and sensitivity in their outputs.
Growing pains may abound, but it’s still early days and may not be long before AI corrects these issues and takes the culinary arts to new heights.
Logan Kugler is a freelance technology writer based in Tampa, FL. He is a regular contributor to CACM and has written for nearly 100 major publications.