The role of artificial intelligence (AI) in food has been on the rise in the past decade, with mostly a practical focus on improving convenience and increasing speed, particularly for larger food and beverage MNCs.
But as algorithms mature and data sources expand, everyone is looking to AI to deliver much more in order to live up to expectations, in addition to becoming much more accessible to not only large food firms but also small and medium businesses.
Here are four of the most crucial food industry applications that AI is moving towards in order to make a more significant impact – and make its presence more prominent – in the sector.
1) Shortening product development cycles
The entire idea of integrating AI into company operations is to increase productivity, but in addition to it helping with things like pre-meeting research or better meeting scheduling, experts believe there is a much larger role for AI to play when it comes to directly improving the time to market (TTM) for new product development.
“Different food and beverage companies have different portfolio sophistications which determines the level of AI tools needed, and often this leads to just surficial usage with scheduling meetings or translating conversations – but there is much, much more to discover here,” Dubai-based Royex Technologies CEO Rajib Roy told the floor at the recent Fi Asia 2025 show in Bangkok, Thailand.
“One of the clearest areas that AI has strong potential for performance in is product development, and this is beyond algorithms to run machines or boost production, but instead the ability to speed up information gathering, analysis and overall innovation.”
Although this may seem straightforward on the surface, TTM is one of the areas that many food and beverage companies face the most challenges and AI has many opportunities to shine.
“Product development can go through many stages, and the fact is that each stage takes a very long time to complete so the overall development can take months to years which is not ideal in a fast-moving market like food,” Betagro Food Innovation Centre VP Phontakorn Wongcharoen added.
“AI can shorten this by screening all the ideas we have and shortlisting for concepts with the best potential results; as well as playing the role of ensuring the eventual product prototype meets important requirements such as from a regulatory aspect.”
Betagro is one of Thailand’s leading protein companies, producing hundreds of protein and other agro-food related products that are exported globally.
“The traditional method of relying on paper-by-paper analysis for either the science or the regulatory details is a long and painstaking one, and can lead to a single product taking 10 to 15 years to reach the market,” he added.
“Of course, we need to be mindful that AI is not going to be 100% accurate and is itself still learning using the data we feed it, but there are many ways to use it to increase the speed of product development.”
The key areas that AI can help in are speed and accuracy, and with TTM becoming increasingly important to the food industry today in order to stay competitive, this is where it can stand out.
“There was once a time when we could say ‘slow and steady wins the race’, but in food innovation today this is no longer so – speed and accuracy are going to be the real winners,” Roy stated.
2) Differentiating between what is just ‘loud’ and what is truly a trend
But in this era of social media, just about every new event or idea is being touted as a ‘trend’ even if it is not, so just how can food manufacturers be sure they are truly following the correct trends in their innovation? AI may have the answer to this as well.
“The main challenge when it comes to innovating according to trends is that firms tend to know about a trend only after it has actually become a trend – then it all becomes a game of playing catch-up,” AI firm AI Palette CEO Somsubhra Ganchoudury said.
“Today, there is an additional challenge in the sense that something that is ‘loud’ in terms of just being pushed at the audience everywhere on social media, may not necessarily be a real trend, and food firms need to be able to know the difference to not waste time and money in innovation.”
Here is where AI can make a real impact as it is able to make use of multiple data sources and billions of data points in order to remove biases that humans cannot detect, helping to identify whether a ‘trend’ is truly a trend.
“This offers more accurate and forward-looking insights into trends – all trends follow a bell curve in terms of maturity and AI can also identify what maturity phase a trend is at so firms know better what sorts of actions to take about it,” he said.
“This is a futuristic view of what comes next and can greatly help in decision-making to invest time and resources, based on what is best for the food firm at that point.”
3) Making sure products make sense to consumers
Unfortunately, it happens more often than not that new products make it to the market, but end up failing with consumers for a variety of reasons, then have to make a sad exit.
According to Roy, one of the biggest issues with such products is the lack of resonance with consumers, failing to become relevant to them from the very beginning.
“When looking for a product to go-to-market, what is most important is really to have insights on that market which are both actionable and sharp – which is what AI can provide,” he stressed.
“This is what will drive the quality of engagement with consumers as it ensures the product becomes relevant to them, and combined with a powerful story or narrative on the marketing front will be very monetizable.”
Making that first contact or sale is also not in any way sufficient to ensure a product’s survival in the market, so this relevance becomes even more important.
“Relevance will assure that a product not only appeals to the consumer so that they try it once, but also that it makes sense to them,” he said.
“This will make a lot of difference because it allows the brand to have better conversations with their target audience, which in turn will help to boost return rates and purchases that keeps the product on shelves.”
4) Reducing food waste from the top
Sustainable initiatives have become a big topic for many food firms, but at the same time many of these firms also face major challenges in terms of related issues like food waste and food loss.
To this end, Ganchoudury believes that AI holds the answer to reducing these issues from the top down.
“AI can understand what consumer demand is for a product in real time, as well as the specific demands and nuances in each market,” he said.
“This means that companies have a better understanding of the amount of production needed which saves on [everything from electricity to ingredients] and prevents food waste generation from excessive production.”
Such insights can also be applied to the area of investment and marketing, where he described a plant-based yoghurt brand which held off on big investment plans for the Asian market based on AI insights – and saved thousands of investment dollars by doing so.
“It was AI technology that showed the product would not see sustainable success here, and it has been proven right as the plant-based industry still has not taken off in Asia until now,” he said.
“Conversely, it can also identify the best formats, flavours, ingredients and so on that will do well in each market, such as focusing on clean label in Thailand or better packaging in China to appeal to a wider audience.”
