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Daily news and analysis about the food tech revolution

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A Week in Rome: Conclaves, Coffee, and Reflections on the Ethics of AI in Our Food System

Last week, I was in Rome at the Vatican for a workshop on the ethical and social implications of artificial intelligence and automation in our food system.

The workshop was part of an ongoing three-year NIH-funded project focused on the ethics of AI in food. It took place at the Vatican’s Pontifical Academy for Life, the same institution that played a pivotal role in 2020 in getting Microsoft, IBM, and others to sign the Rome Call for AI Ethics, a cross-sector commitment to develop AI that “serves every person and humanity as a whole; that respects the dignity of the human person.”

I was invited to provide an overview of AI in the food system to help set the stage for the day’s conversations, which featured Michelin-starred chefs, Catholic priests, journalists, authors, and professors specializing in ethics, artificial intelligence, and more. I walked through some of the developments I’ve seen across the food system—in agriculture, next-gen food product development, restaurants, and the home. As I wrote recently for The Spoon, today “every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.”

I posed questions like: What happens when AI dictates what we eat? Or if it engineers the “perfect sandwich”—something so addictive it floods demand and strains supply chains, as Mike Lee has imagined? What does it mean when a company builds a proprietary food AI trained on global culinary data? Does that dataset become the intellectual property of one corporation? And if AI can tailor nutrition down to the molecule, who controls those insights?

These are not just technical questions. They’re questions with deep implications for humanity.

One thing was clear throughout the day: everyone in the room recognized both the promise of AI as a tool for addressing complex challenges in the food system, and the risks posed by such a powerful, society-shaping technology. Among the questions raised: How do we balance the cultural and inherently human-centered significance of food—growing it, preparing it, sharing it at the family dinner table—with the use of AI and automation across kitchens, farms, and wellness platforms?

Above: The signed Rome Call for AI Ethics

As some attendees expressed, there’s a growing concern that the “soul” of food—its role in connection, tradition, and creativity—could be lost in a world where AI plays a central role.

For obvious reasons, being at The Vatican and in Rome at this time was a bit surreal, as the two days of the workshop and the Vatican came during the same week that the College of Cardinals gathered to select the next Pope after last month’s passing of Pope Francis.

As we wrapped up our discussions, the Conclave began. And just as I was leaving Rome, white smoke rose from the chimney of the Sistine Chapel, signaling that a new pope had been chosen.

In his first address, Pope Leo XIV made it clear that he is thinking deeply about AI’s role in society, so much so that he chose his name in homage to a previous pope who guided the Church through an earlier technological upheaval.

“… I chose to take the name Leo XIV. There are different reasons for this, but mainly because Pope Leo XIII, in his historic encyclical Rerum Novarum, addressed the social question in the context of the first great industrial revolution. In our own day, the Church offers to everyone the treasury of her social teaching in response to another industrial revolution and to developments in the field of artificial intelligence that pose new challenges for the defence of human dignity, justice and labour.”

Also present at the workshop was our friend Sara Roversi, founder of the Future Food Institute. The Spoon and Future Food Institute co-founded the Food AI Co-Lab, a monthly virtual forum where experts across disciplines explore the intersection of food and AI.

Sara, Tiffany McClurg from The Spoon, and I grabbed coffee at a small café in Rome to reflect on the workshop and what it means for our ongoing work. We launched the Food AI Co-Lab in early 2024 as a space to gather our communities and talk through how AI is impacting the food system. So far, much of the conversation has focused on education—helping people understand what AI is and how to thoughtfully implement it in their organizations.

But we all agreed: the world has changed rapidly since we began. Nearly everyone is now seriously considering how to integrate AI into their companies, institutions, or personal lives. And so, the Co-Lab needs to evolve too. Our hour-long sessions, often featuring guest speakers, have been great for tracking innovation, but now it’s time to elevate the conversation. Ethics. Labor. Equity. Sustainability. These aren’t side topics—they’re central to how AI will shape the future of food.

If the world feels more chaotic than ever, one thing is certain: we need to prepare for faster, more unpredictable change. At the first workshop two years ago, most attendees were just learning about AI. There was plenty of fear about a runaway system invading the food chain.

Today, there’s greater recognition that AI is inevitable and that it can be a powerful tool for solving some of the food system’s most complex problems. There was even a bit more optimism this time.

But above all, there’s a clear understanding that we still have a long road ahead to strike the right balance: embracing AI as a tool while preserving what makes food so deeply human, so critical to our culture, communities, and shared existence.

You can learn more about the Food AI Ethics project led by Cal Poly at San Luis Obispo [here]. If you’d like to join us for future Food AI Co-Lab events, you can sign up via our LinkedIn Group or The Spoon Slack. We’ll keep you updated on upcoming events and speakers.

From Starday to Shiru to Givaudan, AI Is Now Tablestakes Across the Food Value Chain

Back in the early days of the cloud computing revolution, my former employer, GigaOM, hosted perhaps the biggest and most influential conference on the topic called STRUCTURE.

One of the phrases that has stuck with me from those days is “data is the new oil,” which I heard declared from the STRUCTURE stage more than a handful of times. At the time, big data technologies were leveraging machine-learning-driven analytics tools to create new correlations and insights from disparate datasets faster than ever before. Those who controlled the data — and could mine it effectively — wielded enormous power.

Now, nearly two decades into the cloud era and three years after the AI “big bang” sparked by the launch of ChatGPT, those early days seem almost quaint by comparison. New AI-powered tools and companies are emerging every day. While much of the “data is the new oil” rhetoric back then felt like spin, today we’re seeing real, transformative progress, especially in new product development.

Food is no exception.

Take the news from Shiru this past week. The company, which uses AI to sort through plant-based food building blocks, announced that it had scaled its first AI-discovered products: OleoPro and uPro. These new approaches to identifying proteins — particularly oleogel structurants (structured fat systems) — are designed to support large-scale production.

As Shiru CEO Jasmin Hume put it:

“This moment is a turning point not just for Shiru, but for the food industry. Even though oleogels have been explored for years (there are over 500 publications on them in the last decade), commercially scaled examples have been elusive — until now. Our AI platform helped us identify the right proteins, but that was only part of the story. Our team then engineered a scalable and entirely new process for producing those proteins with the precise performance attributes required to succeed in real-world formulations.”

But it’s not just next-generation ingredient discovery. New CPG brands are also using AI to decipher early consumer signals and connect the dots before anyone else can launch the next big product. One example is Starday, a startup that recently raised $11 million. Starday uses AI to sift through millions of data points from social media feeds, surveys, point-of-sale data, and more to identify emerging opportunities in food that could lead to future hits.

“Imagine if you had 10,000 consumer insights folks that are watching every video on internet, typing up what’s being said, tagging it, and then kind of building these regression models around how these trends are happening,” said Starday CEO Chaz Flexman in a recent interview with The Spoon. “We’re trying to do that on steroids. We take in about 10 million pieces of content every week, which is very significant.”

In the early big data heyday, companies could look at things like trending tweet mentions. Today, companies like Starday are able to dive into video content, extract context much faster, and build predictive intelligence to guide new product development.

Shiru and Starday are just two examples making headlines recently about how AI is reshaping the food industry. Others are innovating across different parts of the food value chain — from manufacturing optimization (Keychain) to intelligent automation (Chef Robotics), all the way back to the farm with companies like Agtonomy.

Even century-old flavor companies are getting into the act. This past week, Givaudan announced Myromi, a handheld digital aroma delivery device that leverages an AI platform called ATOM.

In short, AI is enabling both startups and established players to move much faster.

And they’re going to have to. In the current MAHA moment in the US, companies are urgently reevaluating ingredient lists and being forced to replace ingredients like food dyes and sugars. This new urgency is adding to what many had already been doing as they see climate change slowly but surely impacting how and what they can source for their products.

Back in 2010, there was a lot of talk about using big data to create better products, but no one was seriously using AI to build food products at that point (heck, Watson, after all, hadn’t even become a chef.) Today, every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.

In other words, if data is the new oil, it’s now clear that AI is the engine of innovation that is accelerating and driving change across every part of the food system.

Join Us Today as We Discuss How Artificial Intelligence Will Impact Culinary Creation

Admit it: you’ve probably played around with making recipes using AI. At this point, most of us have.

If you’re like me, the early results were… rough. But over time, general-purpose LLMs have become surprisingly good at whipping up recipes. Still, there’s a long way to go before AI becomes a true sous chef in our kitchens, and plenty of questions remain about where this is all going.

To help us explore what’s next in this month’s edition of our Food AI Co-Lab, we’re joined by two people who’ve been working at the intersection of AI and cooking for nearly a decade: James Briscione and Lav Varshney, co-creators of Chef Watson—the world’s first culinary AI. Their latest project, CulinAI, is an AI-powered app designed to create personalized meal plans.

Want to join the conversation, ask questions, and see where AI cooking is headed? Register for today’s Food AI Co-Lab here.

ClearCOGS Raises $3.8M its AI-Powered Forecasting Software That Helps Restaurants Reduce Waste

AI-powered restaurant forecasting startup ClearCOGS has raised $3.8 million in an oversubscribed seed round led by Closed Loop Partners, with participation from Myriad Venture Partners and Hearst’s Level Up Ventures. The funding includes $2.3 million in new capital and the conversion of $1.4 million in pre-seed investments. The company’s software provides predictive analytics to assist operators in making decisions around food prep, ordering, and staffing, with an emphasis on reducing food waste and improving operational efficiency.

Company CEO Matt Wampler told The Spoon that he came up with the idea of ClearCOGS during the pandemic. He’d been being laid off and was exploring coding and analytics, when he discovered his cousin who ran a Jimmy John’s franchise was still using a decade-old Excel forecast. Wampler wondered if AI could help create a better predicitve forecasting tool, and before long he had teamed up with Osa Osarenkhoe to build a solution that uses machine learning and time-series forecasting that currover 100 million data points a day.

When ClearCOGS participated in our first virtual Food AI Summit a couple of years ago, Osa and Matt had started experimenting with leveraging large language models (LLMs) like those from OpenAI to create an interface for their forecasting tool. I asked Matt how those experiments with LLMs had gone.

“We did a whole big thing with it… It didn’t go well,” said Wampler. “And it wasn’t from a technical standpoint. It was from the standpoint of the restaurant brands we were talking to… they were like, ‘Look, my general manager can either just get on and play with your AI bot and it’ll tell them, or you can just send it to them? Just send it to them.’”

Wampler said the LLM interface wasn’t the problem. It was just that operators didn’t want to interact with it at all. Instead, they just wanted the answers delivered to them, simply and directly, through email and integrations with solutions from Toast or SevenRooms. This experience reaffirmed Wampler’s belief that proprietary forecasting (and not LLM-powered conversational AI) is where ClearCOGS can deliver the most value.

“LLMs are kind of a commodity at this point. Proprietary data sets are what really matters… You still have to be able to provide a fundamental business value before that AI is really helpful.”

While many platforms offer dashboards or raw analytics, ClearCOGS focuses on delivering direct, decision-ready insights to restaurant managers. This is central to how he differentiates the company:

“If you’re a brand, you probably have 20 or 30 questions that you have to answer every day… We go really deep on those and provide a systematic way of delivering those to your operators every day.”

With the new capital, ClearCOGS plans to accelerate its product development and customer acquisition efforts, with an emphasis of better positioning itself in the food service sector. The company currently serves a customer base of 100 brands in four countries, and Matt says they plan to continue building a lean team, prioritizing automation and AI over headcount.

The Food & Retail AI Rollup Continues as Crisp Buys Shelf Engine

Crisp, a New York-based retail data company, has acquired Seattle-based startup Shelf Engine. Founded in 2016 by Stefan Kalb and Bede Jordan, Shelf Engine specializes in using machine learning to optimize ordering processes for perishable goods, with the goal of reducing costs and minimizing food waste. The platform is now in use across more than 7,000 stores. Terms of the acquisition were not disclosed.

Shelf Engine was one of the earliest adopters of AI technology in food retail aimed at reducing waste and optimizing fresh food ordering. Kalb, who launched a food distribution business at 23 and holds degrees in actuarial science and economics, developed the idea during a 2014 ski trip with his friend and engineer Bede Jordan, a former Microsoft HoloLens developer. The pair questioned why food industry processes and systems remained outdated:

“Could we create a platform that enables retailers to buy food and eliminate significant waste? Could we create a platform that eliminates redundant busywork between vendors and retailers? Could we create a more perfect marketplace?”

These questions led Kalb and Jordan to develop a product designed to drive the food industry towards greater efficiency through technology.

Kalb reflected on the deal on LinkedIn:

“What started as a side project with my good friend Bede turned into a platform that’s now in over 7,000 stores across the U.S., helping reduce millions of pounds of food waste. It’s been eight years of wild highs, humbling challenges, and so much growth.”

Crisp plans to integrate Shelf Engine’s advanced algorithms into its commerce platform. The company believes the integration will help its retailer customers optimize in-stock inventory, improve shelf management, and drive revenue in an increasingly margin-sensitive retail environment.​

“Joining forces with Crisp allows us to scale our proven technology and deliver greater value to retailers and their supplier partners,” said Kalb. “Together, we will set a new standard in forecasting and inventory management, helping our customers thrive even in challenging market conditions.”​

This news is yet another in a series of acquisition announcements for early pioneers who are building technology leveraging AI to optimize different parts of the food value chain. Earlier this month AI Palette was gobbled up by trend forecaster Global Data, and before that Spoonshot was acquired by Target. Like other buyers in these deals, Crisp provides predictive intelligence software and services and is buying Shelf Engine to improve their AI insights capabilities.

Unlike these previous deals, Crisp and Shelf Engine focus more on retail and supply chain commerce optimization, which is one of the areas that is seeing the greatest leaps forward in productivity and cost-reduction. My guess is Afresh, which is similar to Shelf Engine and remains independent following its $115 million in series B funding in 2022, may also be one of the next companies gobbled up as bigger software and supply chain players look to add AI capabilities to their products.

AI-Powered CPG Trend Forecaster AI Palette Gets Gobbled Up

AI Palette, a company that uses AI to help CPG brands anticipate consumer tastes ahead of market trends and better predict new product success throughout their lifecycle, announced today it was acquired by market research company GlobalData.

AI Palette launched within the last decade alongside a cohort of startups—including Analytical Flavor Systems, Tastewise, and Spoonshot—that began utilizing machine learning and big data analysis tools. These tools enabled CPG brands to move away from traditional product ideation and surveys, uncovering hidden insights more rapidly through AI. Like many similar startups, AI Palette started talking up their generative AI bona fides over the past couple of years.

“The integration of AI Palette supercharges our ability to help CPG brands innovate smarter and faster,” said Mike Danson, CEO of GlobalData Plc. “Together, we are setting a new standard for AI-driven intelligence in the consumer space.”

In some ways, this deal resembles Spoonshot’s acquisition a little over a year ago, when legacy market intelligence provider Target Research Group acquired the AI startup. GlobalData Plc, which places greater emphasis on pure data analytics than Target, is a company that has grown primarily through acquisition. From what I can see, AI Palette represents GlobalData’s first pure-play AI company deal.

With most major food-brand CTOs currently exploring—or being directed—to leverage AI, it seems likely that acquisitions of vertically specialized platforms will continue over the next 12-24 months. Consultancies and market intelligence providers will probably lead this trend as incorporating AI into intelligence toolsets becomes essential to maintaining relevance..

McDonald’s is Creating Virtual ‘AI Managers’ for Its Restaurants

Want some AI with your Big Mac? McDonald’s is about to serve it up in a big way.

According to a story in the Wall Street Journal today, McDonald’s is undergoing a technology overhaul across its 43,000 restaurants, implementing internet-connected kitchen equipment, AI-driven drive-throughs, and tools for managers. McDonald’s is partnering with Google Cloud to deploy edge computing technology, allowing restaurants to analyze data locally rather than sending it to the cloud. This setup helps predict equipment failures—such as fryers or ice cream machines—before they occur and ensures order accuracy through AI-powered cameras.

We’ve written quite a bit at The Spoon about McDonald’s experimentation with AI at the drive-thru, but this story shows they are looking to use generative AI for customer interaction and beyond, including exploring generative AI virtual assistants to handle managerial tasks.

From the WSJ: Edge computing will also help McDonald’s restaurant managers oversee their in-store operations. The burger giant is looking to create a “generative AI virtual manager,” Rice said, which handles administrative tasks such as shift scheduling on managers’ behalf. Fast-food giant Yum Brands’ Pizza Hut and Taco Bell have explored similar capabilities.

This story comes just a day after Taco Bell talked up their own AI initiatives, including their ‘Byte by Yum’ AI tool designed to assist restaurant managers with tasks such as labor and inventory management. The AI can manage schedules, assist with drive-through orders, and suggest operational changes based on competitor activity, aiming to optimize employee efficiency without reducing labor costs.

Join Us Today as We Explore Future Scenarios of an AI-Powered Food System

Ever think about all the different scenarios that AI could ultimately unleash on our food system?

Us too, so we decided to invite noted food futurist Mike Lee to talk about it on our latest edition of the Food AI Co-Lab.

Join us today at 8:30 Pacific to explore the different scenarios that AI could unleash upon us.

In this session, we’ll discuss

  • AI & Regenerative Food Systems – How can technology help restore biodiversity, improve soil health, and create more resilient agricultural ecosystems?
  • Personalized Nutrition & Food Sovereignty – Can AI make food systems more inclusive, culturally relevant, and tailored to individual health needs while ensuring accessibility for all?
  • Circular Economy – How can AI-driven solutions reduce food waste, optimize supply chains, and create more efficient, closed-loop food systems?
  • Ethics & AI in Food – As technology advances, how do we ensure that food innovation remains fair, transparent, and truly benefits people and the planet?

You can watch it below or join us on our interactive Livestream to ask Mike questions!

Exploring Future Scenarios of an AI-Powered Food System

The Idea of Food ‘Teleportation’ Isn’t New—But AI Is Finally Making Distributed Digital Food Replication a Reality

Over the past decade, there’s been no shortage of attempts to better understand, map, and recreate food and its properties with the click of a mouse.

From new data ontologies to a proliferation of digital noses, we’ve seen incremental steps toward an envisioned world where the fundamental building blocks of food can be better understood. However, in the past year, there has been a rapid acceleration in our collective ability to digitize various properties of food, largely driven by advances in AI.

The latest example of this comes from Osmo, which recently announced its development of the ability to digitally “teleport” a scent by using AI to digitize and re-materialize it.

Scent Teleportation

As the company’s CEO, Alex Wiltschko, explained:

“We select a scent to teleport and introduce it to a machine called the GCMS (Gas Chromatography-Mass Spectrometry). If it’s a liquid, we inject it directly; if it’s a physical sample, like a plum, we use headspace analysis, trapping the scent in the air around the object and absorbing it through a tube. The GCMS identifies the raw data, which can be interpreted as molecules, and uploads it to a cloud. There, it becomes a coordinate on our Principal Odor Map — a novel, advanced AI-driven tool that can predict what a particular combination of molecules smells like. This formula is sent to one of our Formulation Robots, which treats it as a recipe and mixes different scents to replicate our sample.”

In other words, Osmo breaks down the building blocks (molecules), creates a map, and then sends this digital map to an essence “printer” that re-creates it.

This announcement comes just weeks after leaders of NotCo’s scent and flavor AI team shared research on their new generative AI that creates scent and flavor formulations. Here’s how Aadit Patel, NotCo’s head of product, described the model:

“The system takes your prompt—such as ‘an ocean scent on a breezy summer day on a tropical island’—and creates a novel chemical formulation of that scent in one shot.” The model then generates a corresponding fragrance formula. According to Patel, the model is built on a “natural language to chemical composition” framework, tokenizing molecules to create a system capable of understanding and generating novel combinations.

With years of work focused on digitally understanding, quantifying, mapping, and reproducing scents, flavors, and food building blocks, what is allowing these latest efforts to make such significant leaps?

In a word (or two): AI. In the past, creating a facsimile of a flavor or scent took thousands of hours, relying on trained experts to work in a lab or kitchen, drawing on years of expertise. Now, AI is expediting that process with orders of magnitude more efficiency, often leaving the expert to provide a final sign-off to ensure the AI-created formula meets standards for proximity to the desired result, as well as checks for safety, cost feasibility, and more.

For the record, Osmo isn’t the first company to discuss “teleporting” a formula for digital recreation. In 2018, Japanese startup Open Meals made headlines with its “sushi teleportation” demo, essentially sending 3D printing instructions to create a sushi-like meal. We also saw Cana’s ambitious attempt to make a Star Trek replicator (though, as it turns out, investors weren’t quite ready to enter the food teleportation age).

All of this follows years of efforts to quantify and understand food digitally, including the creation of ontologies for the Internet of Food and early attempts to use AI to analyze food. But over the past couple of years, there’s no doubt that parallel advances in AI (especially in large language models) and breakthroughs in food, olfactory, and chemical science are ushering in a world where true food “teleportation”—or, more accurately, the ability to understand and synthetically recreate food, flavors, and scents—has arrived.

I’m excited to see where this all goes. To manifest the vision laid out in science fiction over the years and imaginative product concepts like that of Open Meal required a true digital understanding of the molecular building blocks of food. With AI, we are closer than ever to that understanding, and the products we’ll see built in the coming decade will not only create some mind-blowing consumer experiences but also possibly fundamentally change how food and beverage products are made and distributed.

Live Event: Using Generative AI to Build Next-Generation Flavors & Fragrances

Join us today for a live event at 8:30 AM PT, featuring the project leads for NotCo’s new AI to develop flavors and fragrances. Register and watch below or head to Streamyard.

Can AI be used to create new flavors and fragrances?

As I wrote last week, food-tech company NotCo has been asking itself this question for the past couple of years. Their answer is a newly unveiled generative AI model, the Generative Aroma Transformer (GAT), that they say is capable of creating new flavor and fragrance formulations.

The company’s Senior vice president of Product, Aadit Patel, described how it works this way: “The system intakes your prompt, such as ‘an ocean scent on a breezy summer day on a tropical island’, to create a novel chemical formulation of that scent in one shot.” From there, the model generates a corresponding fragrance formula. According to Patel, the model is built on a “natural language to chemical composition” framework, tokenizing molecules to create a system capable of understanding and generating novel combinations.

NotCo says early tests have been extremely positive, and the company says their research indicates that GAT’s abilities rival those of human perfumers. At the Food AI Summit last month, the two product leads, Francisco Francisco Clavero and Cindy Sigler, gave an in-depth presentation on the science behind their new model and talked about early results.

Their presentation was fascinating, so I asked them to present to our Food AI Co-Lab community.

Watch the recorded session below:

Using Generative AI to Build Next-Generation Flavors & Fragances

Cashierless Checkout Pioneer Grabango Shuts Down After Failing to Secure Additional Funding

Grabango, a grocery-tech startup that raised over $93 million for its cashierless checkout technology, is shutting down, The Spoon has learned. The closure follows the company’s inability to secure the necessary funding to continue operations.

In a statement to The Spoon, Grabango said:

“Grabango announced today it has permanently discontinued operations. Although the company established itself as a leader in checkout-free technology, it was not able to secure the funding it needed to continue providing service to its clients. The company would like to thank its employees, investors, and clients for their hard work and dedication. The decision was an extremely difficult one to make.”

Founded in 2016, Grabango emerged during a surge of investment in grocery checkout technology startups, spurred by Amazon’s launch of Amazon Go. However, the field quickly became crowded with competitors like Shopic, Trigo, Mashgin, and Caper (acquired by Instacart), all of which offered variations of computer vision and AI-powered shopping platforms.

Despite the competition, Grabango secured notable clients, including European grocery giant ALDI, which just six months ago introduced its ALDIgo checkout-free solution, powered by Grabango’s technology. Yet, as seen with Amazon’s recent rollback of its Go platform in Fresh stores, cashierless checkout needs to be carefully deployed because customers can sometimes find their friendly cashiers being replaced by a technology platform offputting.

Grabango’s shutdown is a reminder of the tough climate for startups today. The days of easy venture capital are over, and in highly competitive sectors like grocery tech, startups that can’t extend their financial runway or achieve profitability are vulnerable. It’s likely that Grabango’s assets and intellectual property will soon be scooped up by a competitor.

When it Comes to Using AI To Shape New Culinary Creations, Ali Bouzari Thinks Food is Mostly ‘All Hands’

In the most recent episode of the Spoon Podcast, I caught up with food scientist Ali Bouzari to discuss his work and get his thoughts on new technologies that are helping to shape the future of food.

I first met Bouzari when he spoke at the Culinary Institute of America a few years ago about how robotics could impact food service and other sectors. At the time, he talked about Creator—a burger restaurant powered by robots—and suggested that food robots could sometimes do things that most food service employees could not replicate. He specifically referred to how Creator’s burger bot could create more intricate structures in the burger patty than possible to enhance mouthfeel.

When I asked him about this on the podcast, he suggested that while yes, there are things technology can do, he was worried about the recent obsession with AI and using it to craft recipes and new culinary creations. He drew a parallel between AI’s notorious difficulty in rendering realistic-looking human hands in artwork and the challenge of using AI in food production.

“You know that recurring motif where somebody will put a seemingly impressive piece of AI-generated imagery up and be like, ‘My God, look at Darth Vader doing this thing in Saturday Night Fever or something.’ And everybody always says, ‘Look at the hands, look at the fingers.’ And there’s always something wrong with the hands. There’s something that is difficult for AI to crack. What I would say it is most of food is hands. Food is basically all hands.”

Bouzari also shared how multiple clients had approached him after playing with generative AI tools to experiment with developing food products. “We have clients being like, ‘Hey, ChatGPT said we should put arrowroot flour in this cookie.’ I think that somebody is feeding all of the AI brains a lot of great information about arrowroot. Because three different people on three different projects have said that AI said, ‘Have you tried arrowroot?’ which is, in a lot of instances, kind of a useless ingredient.

But thinking about things like AI have caught his attention, Bouzari told me the biggest challenge that has his attention nowadays is the impact of climate change and how food brands are facing a reality that their products may not have a future if they continue to do things – and create food products – in the same way as they have in the past.

One example he gave is the global cacao shortage. “Chocolate is in trouble,” Bouzari said. He pointed to how disruptions in cacao production are driving up costs and threatening the availability of what is a beloved staple. This isn’t some distant, theoretical issue Bouzari told me. “It’s already happening.”

And it’s not just chocolate.

“Coffee’s next,” said Bouzari. “Coffee might do a thing where, like grapes, it just creeps higher and higher latitudes as things change.”

And because of this urgency food brands are now faced with that Bouzari gets a little annoyed with how food makers are sometimes distracted with shiny new toys while missing the big picture.

“My thinking with food is it’s a little bit extra irksome, the conversation around AI sometimes, where people say, ‘I’ve spent six months trying to get this generative AI to make me a new pasta recipe,’ when I don’t think we need that. And the water and energy cost of all of that computation is directly contributing to, I think, the actual biggest existential problem we have, which is climate change.”

We also talk about Bouzari’s experience on the Netflix Show Snack vs. Chef, his thoughts on alternative proteins and what gets him excited about the future.

You can listen to the full episode on Apple Podcasts, Spotify or by clicking play below.