streamlined services<\/a> in offices and factories, and now the likes of Nestl\u00e9, PepsiCo, Danone and Unilever are putting it to work to help in a predictive capacity \u2013 to anticipate consumer demand and foresee and mitigate problems before they occur. <\/p>\nFrom using it to identify the most resilient crops for its products to better planning of warehouse space, AI technology is taking a huge amount of guesswork out of the equation for food and drink manufacturers. In this age of global uncertainty, AI\u2019s ability to analyse data quickly from all areas of an organisation \u2013 even when the data is limited \u2013 is a useful tool. <\/p>\n
\u201cFood manufacturing requires constant trade\u2011offs between quality, cost, service and sustainability,\u201d explains Christophe Villain, senior global operations and digital transformation leader at Nestl\u00e9. <\/p>\n
\u201cAI helps make those trade\u2011offs more transparent and manageable, allowing companies to respond faster to consumer needs without compromising safety or standards.\u201d<\/p>\n
Villain, who leads end-to-end operations and digital transformation at the Swiss-based manufacturer, said beyond efficiency, Nestl\u00e9 was using AI to help it anticipate consumer needs to ensure products were delivered in the right place at the right time. <\/p>\n
\u201cThis includes using AI and causal models to simulate complex scenarios impacting our end-to-end value chain \u2013 for example, how changes in demand, availability of ingredients or logistics constraints could affect product availability or freshness,\u201d he says. \u201cThese simulations help operations teams adjust plans before consumers feel the impact.\u201d<\/p>\n
Logistical help<\/p>\n
AI is also aiding logistics. In the US, PepsiCo is using digital twins (virtual models) and AI-agents to co-design new production and warehousing facilities. The move means the business can test the space for capacity and efficiency before spending huge sums on a build. <\/p>\n
Danone and Unilever are among the businesses using AI to suggest the kinds of products its customers will want in the future. <\/p>\n
![\"Robot](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/06\/FNTA3POVPZFYRH27SMU5IG4Q7I.png\")
AI is increasingly able to streamline food production (Image: Nano Banana)<\/p>\n
Danone said it had enlisted the help of predictive modelling and AI-enabled research in areas such as gut health to \u2018develop products with evolving needs\u2019, while FMCG giant Unilever is doing similar in its beauty and wellness division. <\/p>\n
Aside from predictive modelling, AI is being used by food manufacturers to aid areas such as compliance, traceability and quality control, says Stephen Pavlich of Loftware. <\/p>\n
The labelling software company uses AI to automate label checks by reviewing ingredient lists, allergen declarations, nutritional information and country-of-origin details against regulatory requirements such as Natasha\u2019s Law and FSMA 204. <\/p>\n
\u201cOur work focuses on helping businesses move away from manual, fragmented processes toward connected product identification systems that reduce errors and improve responsiveness,\u201d says Pavlich, noting growing interest in connected packaging strategies that link physical products with digital information and consumer engagement experiences.<\/p>\n
Sustainability gains <\/p>\n
AI is also doing some heavy lifting in helping to cut carbon emissions. It\u2019s being used across the supply chain to measure, reduce and redesign emissions-intensive activities, says Sam Stark, CEO and founder of Green Project Technologies, with the biggest impact made by combining AI with operational data. <\/p>\n
\u201cUnlike traditional rule\u2011based systems, AI can learn from imperfect and incomplete data, which happens often in food supply chains where supplier data is inconsistent. This makes Scope 3 emissions measurable and actionable much earlier than previously possible.\u201d<\/p>\n
![\"Mid](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/06\/O3SJ2BLDR5A5DNWFQRNVREDMNI.jpg\")
AI is improving data accuracy in agriculture (Image: Getty\/ArtistGNDphotography.)<\/p>\n
As with other areas where AI is used, it is its ability to speed things up in carbon reporting that is its forte. <\/p>\n
\u201cAI shifts decarbonisation from reactive reporting to predictive action. By forecasting demand, yields, energy use and emissions trajectories, it enables early decision-making to avoid excess emissions being generated,\u201d concludes Stark. <\/p>\n
How the big brands are using AI <\/p>\n
PepsiCo<\/p>\n
PepsiCo is using AI and digital twin technology to help \u2018retool and optimise\u2019 its existing physical footprint in response to rising demand for production and distribution capacity. <\/p>\n
The collaboration with Siemens and NVIDIA, which is currently being piloted in the US before being rolled out globally, will use digital twins (virtual models) and AI-agents to co-design new production and warehousing facilities. <\/p>\n
PepsiCo chairman and CEO Ramon Laguarta said the business was \u2018embedding AI throughout operations\u2019 to help it meet increasing demands from customers. <\/p>\n
\u201cThe scale and complexity of PepsiCo\u2019s business, from farm to shelf, is massive,\u201d he says. <\/p>\n
A Siemens digital twin composer, built on NVDIA Omniverse libraries digital twins and AI agents, will be used to simulate upgrades to its current facilities, allowing the business to test the space before committing to a physical build. <\/p>\n
The technology allows every machine, conveyor, pallet route and operator path to be recreated \u2018with physics level accuracy\u2019, according to the Pepsi-Cola and Lay\u2019s producer. <\/p>\n
![\"Digital](\"https:\/\/www.europesays.com\/ai\/wp-content\/uploads\/2026\/06\/LL5Y5EXYRNAEBO3J5OO7WYT2BM.jpg\")
PepsiCo is using digital twin technology across its business (Image: Getty\/Ole_CNX)<\/p>\n
AI agents then simulate, test and refine system changes with the ability to identify up to 90 per cent of potential issues before they physically occur. The approach is said to drive faster design cycles \u2013 teams reported they were able to validate new configurations that boosted capacity and throughput \u2018within weeks\u2019 \u2013 and can reduce capital expenditure by up to 15 per cent. <\/p>\n
Athina Kanioura, CEO, Latin America, and global chief strategy & transformation officer at PepsiCo, said the digital blueprint was a first for the industry. <\/p>\n
\u201cWith a unified, AI-powered digital foundation, PepsiCo is building toward a world where every plant and warehouse operates as part of a single, intelligent ecosystem. In this future, our facilities don\u2019t just respond to demand, they anticipate and then adapt to it.\u201d <\/p>\n
Danone <\/p>\n
AI\u2019s use at the French dairy and water major is focused in three areas: developing new products, making operations more efficient and sustainable, and staff training. <\/p>\n
The first \u2013 innovation \u2013 is arguably its most creative use. Here, Danone has enlisted predictive modelling and AI-enabled research in health and wellness to \u2018accelerate science and innovation\u2019 in areas like gut health that will help it develop new products that it says will meet consumers\u2019 \u2018evolving needs\u2019. <\/p>\n
Efficiencies are less exciting, but essential for a successful business. AI supports Danone\u2019s industrial operations to make plants safer, reliable and resource efficient, it says. <\/p>\n
\u201cIn practice, we use digital tools that help teams anticipate equipment issues through predictive maintenance and optimise key production parameters, while keeping human expertise in control,\u201d says a spokesperson. <\/p>\n
Danone is also one of a growing number of manufacturers automating its product carbon footprinting with sustainability research company and SaaS platform HowGood. <\/p>\n
Where AI is making the biggest difference at Danone, however, is in supporting its teams. The business is collaborating with Microsoft to build on the work of its DanSkills programme, which trains teams in how best to use AI. For example, in digital twin technology to simulate and test changes and predictive maintenance to anticipate issues. <\/p>\n
\u201cFor us, the biggest benefits of AI are people enablement \u2013 helping teams on the shop floor, in supply chain and in R&D get better visibility and decision support \u2013 and reducing manual admin,\u201d it says. <\/p>\n
Using data and AI to cut energy use and wastage and to analyse customer behaviours to better deliver services for them are also major benefits. <\/p>\n
Nestl\u00e9<\/p>\n
AI isn\u2019t considered a support service at Nestl\u00e9. The Swiss manufacturing giant regards it as a core capability and \u201can integral part of how Nestl\u00e9 operates its global manufacturing and supply chain network\u201d, says Nestl\u00e9\u2019s Villain.<\/p>\n
\u201cAI reduces the risk of over\u2011 or under\u2011production, improves on\u2011shelf availability and limits waste \u2013 directly affecting what consumers find in stores.\u201d<\/p>\n
Christophe Villain, senior global operations and digital transformation leader at Nestl\u00e9<\/p>\n
Today, AI is used across multiple areas of the business, from ensuring that the demand and supply of its products align to optimising performance in factories. <\/p>\n
For example, the AI-based forecasting tools it uses analyse historical sales and other factors to better anticipate consumer demand. <\/p>\n
\u201cThis reduces the risk of over\u2011 or under\u2011production, improves on\u2011shelf availability and limits waste \u2013 directly affecting what consumers find in stores,\u201d says Villain. <\/p>\n
At the other end of the supply chain, it has enlisted the help of AI\u2011supported climate\u2011resilient agriculture, using advanced data models to select and breed more resilient crop varieties. It is also used to accelerate the development of more sustainable packaging materials. <\/p>\n
On the topic of sustainability, AI is helping to make Nestl\u00e9 more energy efficient by analysing material flows, quality losses and energy consumption. The regular analysis gives teams a more in-depth view of food and energy wastage, says Villain, meaning the business can react quickly to reducing it. <\/p>\n
Like PepsiCo, Nestl\u00e9 has employed digital twins in its factories through a partnership with Accenture Song (built on NVIDIA Omniverse) to test changes virtually. This includes using AI and causal models to simulate complex scenarios, such as how a change in demand, availability of ingredients or logistics constraints could impact the end product. AI is also used to support real-time process optimisation, helping to detect deviations earlier and stabilise production lines. <\/p>\n
Highlighting issues before they get too big maintains product quality and availability, while simulations help the operations teams adjust plans if needed and ultimately save the business time and money. \u201cThis reduces time to market for new products, supports smoother industrialisation and helps ensure that innovation reaches consumers faster and more consistently,\u201d adds Villain. <\/p>\n
The system is already making a difference. Nestl\u00e9 created additional packaging supply in premium pet food when demand forecasts rose sharply while production was brought forward and additional manufacturing capacity unlocked for cold coffee concentrates. In confectionery, it has removed bottlenecks and is preparing additional line capacity for new products, so supply can stay ahead of the growth curve.<\/p>\n
But it is AI\u2019s ability to speed up decision-making that ultimately makes it an invaluable tool for Nestl\u00e9, a business that has its arms open and ready to welcome more AI systems in the future. <\/p>\n
\u201cThe focus is on scaling what works \u2013 responsibly \u2013 and ensuring that technology ultimately translates into better, more reliable products for consumers. The direction is clear: moving from isolated use cases to enterprise\u2011wide, value\u2011driven AI embedded in daily operations,\u201d says Villain. <\/p>\n","protected":false},"excerpt":{"rendered":"AI in food: summary AI in F&B boosts growth with predictive analytics to help forecast demand and reduce…\n","protected":false},"author":2,"featured_media":80099,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[24,25,512,43574,6277,1221,4103,5222,5969,6694,497,2501,7033,711,2074,2920,9624,25981,598,17316,9507,527,4115,8829,43575,7699,781,43576,43577,3276,43578],"class_list":["post-80098","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai","tag-ai","tag-artificial-intelligence","tag-automation","tag-bridging","tag-collaboration","tag-computing","tag-concept","tag-connect","tag-cyber","tag-cyberspace","tag-datum","tag-digital","tag-digital-twins","tag-future","tag-human","tag-information","tag-integration","tag-interface","tag-machine","tag-man","tag-management","tag-model","tag-network","tag-online","tag-physical","tag-simulation","tag-tech","tag-touch","tag-twins","tag-virtual","tag-worlds"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/80098","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=80098"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/80098\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/80099"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=80098"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=80098"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=80098"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}