Why AI is the Future of the Food Industry

By Oded Omer, Founder and CEO of Wasteless

Knowledge and attitudes around global food production are undergoing a transformation. The sheer scale of the food industry and rapid shifts in culture make it difficult to assess this transformation succinctly. However, we can point to several developments that have recently become mainstream: phrases like ‘farm-to-fork’ and ‘buy local,’ organic sections in almost every supermarket, and alternative meats in fast food restaurants are all indicative of rising awareness that food is about more than taste.

These changes in food consciousness are important in that they are pushing the conversation towards sustainability. However, the challenges the food industry is facing cannot be solved by consumer trends and ‘woke’ chefs alone. The fact is, global food production is a costly enterprise, contributing more than a quarter of all greenhouse gases while sucking down almost two-thirds of all fresh water.

These complex problems are requiring detailed solutions, and certain technology is finally getting to the point where it can make some meaningful contributions. Namely, the careful deployment of artificial intelligence and machine learning has the potential to make a significant impact on the sustainability of global food production, transport and sale, and consumption.

Thinking globally, acting globally

Feeding the world is no easy job, and, unfortunately, some of the challenges that farmers are facing are not going to improve in the coming decades. A rising population along with a degrading natural environment are going to put significant added pressure on a system that is already exploiting too many resources.

Everyone still needs to eat, so what this means for agriculture is the necessity to do more with less. In addition to the political will needed for a global perspective, we need to also start looking at the optimization of agriculture as a data management problem. It is precisely here that AI can make a big contribution.

Hardware advances, such as the use of drones to monitor crops, need to be paired with a new understanding of the complexity of a rapidly changing agricultural landscape. AI is a natural ally in this environment, as all forms of machine learning require robust data inputs to be truly effective. Farmers have always been practical people, and there is no reason to think that they wouldn’t welcome a new set of tools that can give them predictive insights that could factor in years worth of weather patterns, news developments, glacial melt and flooding, world-wide atmospheric conditions, market demand, soil conditions over time, as well as real-time reporting about crop conditions. As agriculture responds to the necessity of greater precision, we can fully expect data researchers and machine learning programmers to be working the fields right alongside farmers.

Going to market

Improvements in agriculture are only the beginning stage of optimizing our food systems. Foodstuffs -- be they animal, mineral, or vegetable -- must also be brought from the farms to the people who consume them. Conventional thinking here tends to focus on transportation. While it is certain that artificial intelligence should and will be a major development in supply chain management -- from procurement bots to autonomous vehicles -- it is actually food waste that is a much bigger problem in these economies.

Today, it is considered normal, and acceptable, that more than one third of the food we produce is thrown out, wasted. If food waste was a country, it would be the third highest producer of carbon behind the U.S. and China. We’re never going to get to zero waste, but we need to take a serious look at adjusting these norms. After all, any AI solution in agriculture would still be for nothing if we continue to toss over 30% of what we produce. Consumer environments play the largest role in lowering food waste, and AI can also help here in some surprising ways.

At the top of the list, inventory control systems could make huge improvements if they were enhanced by data tools that were as wide as possible in scope. Demand forecasting remains somewhat mystical even today, but it’s easily within reach to implement some new, more holistic solutions that could not only handle but thrive in such complexity. Pricing is a main area that’s sorely in need of a more exacting focus, and AI-driven pricing and markdown engines would keep more products out of the dumpster. AI will also be utilized on the manufacturing side to develop products more targeted to consumer demand.

It’s an area of climate-change solutions that probably won’t see any tattooed influencers as spokespeople, but such efforts would recoup billions in revenues and significantly lower a major contributor of greenhouse gases. AI can provide better monitoring and analysis of how food gets from farms to people, offering predictive metrics for retailers and money-saving incentives for consumers. This speaks well to the likely longevity of these developments, because they allow fiscal smarts to replace altruism in supermarkets.

From robot to table

Once food finally lands on a plate, in a pantry, or on a fridge shelf, there are still a number of behaviors that lead to an under-utilization of the resources that contributed to the food’s production. Data is starting to play a more important role in personal health, but as the price of food is likely to rise, consumers will be under the same pressure as farmers when it comes to food: make more out of less. The norms of food shopping -- a mix of emotion, brand navigation, trends, wisdom, and routine -- will soon be augmented with highly personalized, very fine-grained inputs of data.

AI will have a big role to play as people incorporate more of their personal health data into shopping lists that will factor in purchasing history with the global movements described above. Imagine your shopping cart making recipe suggestions based on your recent blood sugar, sleep pattern, vegetable freshness, and supplier sustainability data sets. The meals will be no less delicious, and we will have the added benefits of penetrating insights into how to get the most out of the food we buy. 

Is the future bright?

George Carlin said, “The planet is going to be fine; it’s people who are [going to have big problems].” This is a good statement to keep in mind as a motivating mantra. The challenges that we are facing as we continue to find new and better ways to feed the world’s population are no cause for pessimistic outlooks. We just need to get smarter when it comes to food.

Recent developments in machine learning and data management are offering some very promising solutions toward optimizing our food system. The main thing to understand in the effective use of AI, is that the data must be of a very high quality. Global food production can certainly provide an endless volume of data for such systems, but the task now is to learn how to frame the questions. AI can help us eliminate much of the waste and inefficiency in our food systems, but it’s up to us to build these tools for specific targets.

About Oded

Oded Omer is Founder and CEO of Wasteless, a technology company helping to lower food waste in supermarkets. He was previously CTO at WeissBeerger, which was acquired by ABInBev in 2017. He has since turned his full energy to helping the climate change crisis, and is an advisor and investor in several organizations working toward that goal. Oded has a bachelor’s degree in electrical engineering at Tel Aviv University and an Industrial Management Engineering MBA. He is a relentless polymath, moving fluidly between corporate team building, technology advisement, software and hardware engineering, and music. Oded lives in Tel Aviv with his family.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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