CPG MANUFACTURERS PUT THEIR FAITH IN AI TO REVIVE THE SECTOR Manufacturers in the CPG (consumer packaged goods) sector say they are losing 15.2% of their revenues, on average, due to delays, downtime, rework, quality deviations or “sub-optimal” use of their assets. These preventable losses account for an estimated 20.3% of the final cost of their products, and they expect the losses to worsen, reaching 21.4% in 2027 and 29.1% by 2030. The figures come from a Schneider Electric survey of 1,435 senior manufacturing decision-makers working in the food and beverage, and life sciences, sectors in 14 countries, including the UK, US, Germany and France. In the UK & Ireland, revenue losses linked to CPG manufacturing inefficiencies are estimated to be around 17.8% today, and are expected to reach 24.5% next year and 34% by 2030, according to the survey. Many CPG manufacturers are betting on industrial AI to help them cut the losses, although just 13% say they have already embedded AI end-to-end in their operations and decision-making processes. But by 2030, 37% expect AI to be core to their operations, with 32.7% predicting returns of 50–74% from their AI projects by 2030, with 7.9% forecasting returns of more than 100% – meaning that their AI investments will pay for themselves in less than a year. 70% of the respondents reckon that the ROI on their current AI investments is under 20%, with 28.4% reporting ROIs of 5% or less. Schneider suggests that this reflects the limited value they are getting from early deployments of AI. Despite the executives’ faith in AI helping to turn their businesses around, they identify several structural – rather than technological – obstacles to a wider use of AI. These include: skills gaps in AI or data science (cited by 43% of respondents); their use of legacy automation systems and infrastructure (37.5%); a lack of contextualised operational data (36.3%); and resistance from employees (25.7%). Cybersecurity and compliance concerns were cited by just 21.7%. According to Neil Smith, president of Schneider’s CPG business, the manufacturers expect to triple their adoption of end-to-end AI by 2030, as well achieving as “a step change” in returns from the technology. “This expectation gap is the strongest signal of urgency we’ve seen in years,” he says. “AI can only be transformative when it delivers true industrial intelligence: the ability to turn real-time operational data, modern automation and AI into synchronised decisions that improve efficiency at scale. But, he adds, “many organisations are still operating brownfield sites with fragmented data and legacy systems that limit AI’s value and adoption. Closing this readiness gap is now one of the most important competitiveness priorities for the CPG sector.” Judging by the number of AI-related announcements at the recent Hannover Messe, manufacturers will not be short of AI tools that they can apply in their businesses. We will have to wait to see whether these tools have the transformative effect that many expect. Tony Sacks, Editor n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ÐÕÍÖÓÖÎÐÊ ËÌÚ ÐÕÊÌ ¯´²³ Ð Î Õ ZZZ LQIRORJLF GHVLJQ
RkJQdWJsaXNoZXIy MjQ0NzM=