Cooking up algorithms

Once the realm of science fiction, AI has quickly become a familiar part of everyday life. It may not have (yet) taken the form of autonomous robots, but AI is now part and parcel of the way we live our online lives; from the Netflix recommendations to suggested items on Amazon.

The value of AI lies in its ability to consume, digest and find patterns in vast quantities of data. When almost every interaction generates data, making sense of that information and using it to make meaningful decisions is a task beyond any human capability. But an increasingly intelligent system running on computer hardware that can run operations at a billion times faster than a single human is right at home doing just that. As with almost every other business sector, this capability presents a vast array of opportunities for the food industry, and manufacturers have been quick to deploy AI for everything from analysing the effectiveness of online marketing and supply chain operations to developing new recipes and calculating the perfect planting time for key ingredients.

At home in food manufacturing

AI and machine learning (ML) are among many advanced technologies that have the potential to transform the food industry as part of a broader process of digital transformation that is sweeping across all business sectors. Their potential to improve food processing is just one of many potential applications, though it is one of the most promising as it provides scope for many inefficient tasks to be automated, including sorting, packing, shipping and quality control.

Food sorting, for example, is a highly labourintensive process that requires a significant investment in skilled labour. Using AI and ML to minimise the potential for human error in the sorting could dramatically reduce costs and speed up the process. This is related to another key area where AI can deliver a step change in performance – food safety.

In many industries, the use of AI-enabled camera systems to monitor employees is growing fast, and in the food industry the ability to track people’s compliance with food safety protocols – including wearing the correct workwear and performing the necessary cleaning procedures – could have a dramatic impact on food safety.

Supply chain management can also benefit from the power of AI. As transparency is paramount for food safety and regulatory compliance, AI is uniquely positioned to assess the deluge of data from monitors throughout the logistics process to ensure that all safety standards are met. For example, any deviation from the required parameters of the cold chain can be swiftly identified and reported.

As well as the automation of processes, AI can also play a key role in the development of new products, helping food manufacturers to identify new trends, incorporate new and popular ingredients, and create more healthy and nutritious recipes in response to customer preferences. In the age of social media, it is easier than ever to conduct surveys or to parse the comments from major platforms to see what customers want, and AI can ensure that the valuable information hidden within a huge quantity of data comes to the surface.

Big companies are the prime movers

Nestlé is an early mover into AI, using it primarily to analyse clinical data to inform the creation of new healthy and sustainable products. Speaking at a recent investor conference, Nestlé’s chief technology officer, Stefan Palzer, noted that data science, AI and ML will be crucial for the company’s rapid response to industry trends, remarking that the company had developed “AI-based concept generation” that could respond to trends on social media to gain insight into what customers want. To leverage the vast amount of information available on social media – along with market data and customer input – the company’s AI concept engine can provide the platform for the generation of innovative ideas for new products, which can be assessed by employees and potentially put forward for full development. The company has also built an AI module for recipe development, leveraging the ability of the system to rapidly identify food trends and customer preferences to rapidly create goods that appeal to market needs.

Nestlé is not confining its use of AI to product development either as it is also used to improve the efficiency of its digital marketing strategy. Of its total media spend, 55% goes on digital media assets, and almost 16% of its sales are through e-commerce platforms, so it is vital to understand how its digital presence is generating value. AI can provide quick access to actionable data insights that enable the company to keep pace with fast-changing consumer needs. The company’s analytics capability helps it to steer a steady course through a volatile retail environment, where the rising cost of raw materials is a big challenge to the bottom line.

Nestlé has developed a strategic revenue management programme that covers almost 95% of its markets, with AI playing a key role in tracking and enhancing the relevance of more than 500,000 digital assets per year across a variety of digital platforms. The result is a 66% improvement in performance in return on ad spend across Meta platforms, Facebook and Instagram.

Fellow industry giant PepsiCo has fully embraced AI, with the company’s chief strategy and transformation officer, Athina Kanioura, recently noting that “businesses have systems that have intelligence behind them that have transformed the way we solve problems, engage with consumers and make products”.

PepsiCo’s digital transformation process includes using AI for a variety of purposes, from analysing the best time to plant crops to forecasting how many products should be shipped to stores. AI helps to organise huge amounts of data that no human or team of humans could make sense of in a timeframe necessary to take meaningful action. PepsiCo can now get insight from millions of data sets to tailor its products to the needs of its customers. Furthermore, the product innovation cycle has become significantly shorter, as the company can see what customers are talking about and searching for online.

Then there are companies like Danone, perhaps best known for its yoghurt products, that are utilising AI to link the latest scientific research to an in-depth analysis of customer demand. The company’s deputy CEO, Juergen Esser, recently noted that: “The longterm business strategy of Danone is very much about turning around dairy, and everything about bringing the right ferments, the right health benefits and making it shine to the consumer is critical.”

To that end, Danone has developed a range of experiments and analyses based on parsing vast quantities of data and the latest research into gut health. Having invested $100m in a new research laboratory near Paris that opened earlier this year, the company has created an artificial stomach replicating the human gut to test new formulations based on parameters defined by patient samples and health profiles analysed by AI systems and track the performance of probiotics. The stomach simulates the human digestive process and AI systems defines the data component. The company hopes this initiative will be pivotal to the success of its next generation of health-promoting dairy products.

At Mars, Incorporated – which brings the world Skittles and Snickers, among a host of popular products – AI is being used to improve nutrition. The Mars Advanced Research Institute recently announced a multi-year agreement with AI company PIPA to increase the speed of discovery of new plant-based ingredients. The company’s LEAP platform brings together AI, knowledge graphs and bioinformatics to define links between food, compounds, microbes and health states.

At Mondelez International, the company behind brands such as Cadbury and Oreo, AI is being deployed in the development of new products and flavours, fuelling the creative process with data analysis and enabling the product prototyping process to pick up speed. The vital ingredient here is the ability to rapidly understand how customers are responding to new products.

A steep investment curve

Seemingly able to improve every aspect of the food industry from logistics to product development, AI is unsurprisingly a hot topic and a key focus for investment. There are, however, some lingering concerns about its use. The high cost of AI could be a stumbling block, though the potential efficiency gains across a food manufacturer’s business seem to hold more than enough potential for this concern to be overlooked. Ethical concerns about the safe use of AI pervade every industrial application, and there are always fears that smart algorithms could increasingly replace humans in food production. If an industry that feeds billions of people every day becomes overly dependent on AI, there could be risks to the global supply chain.

Nevertheless, it seems the industry is sold on AI and its benefits, so investment is likely to ramp up sharply. The key will be for food manufacturers to ensure that those benefits do not come at too high a cost.