Schneider Electric, the global leader in energy technology, has recently unveiled findings from its global 2026 Industrial AI in CPG Survey, which highlighted that consumer-packaged goods (CPG) manufacturers expect significant increases in production inefficiencies and cost pressures by 2030. Many are turning to industrial intelligence – the combined power of AI, data and automation – to reinforce competitiveness in a decade of accelerating volatility.
The survey reveals that CPG manufacturers expect an accelerating margin crisis, with inefficiencies including manufacturing delays, downtime, and equipment failure already amounting to an estimated 20.3% of the final manufactured product cost today. Respondents report 15.2% of mean manufacturing revenue lost today due to delays, downtime, rework, quality deviations or suboptimal asset use.
These preventable losses are expected to worsen sharply, reaching 21.37% next year and rising toward 29.14% by 2030. Many CPG manufacturers are betting on industrial AI to cut the projected rise in preventable production losses.
Currently, only one in 8 (13%) CPG manufacturers say AI is embedded end-to-end in core operations and decision-making. By 2030, more than a third (37%) expect AI to be core to their operations, tripling the adopting in just 4 years.
Neil Smith, President, CPG, Schneider Electric said, “Manufacturers are projecting a tripling of the end-to-end AI adoption by 2030, alongside a step change in the returns they expect to see, matching the levels only the most advanced Lighthouse and autonomous factories achieve today. This expectation gap is the strongest signal of urgency we’ve seen in years. AI can only be transformative when it delivers true industrial intelligence: the ability to turn real-time operational data, modern automation and AI into synchronized decisions that improve efficiency at scale. Many organizations 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.”
Despite strong confidence in AI’s potential, survey respondents consistently identify structural, not technological, hurdles as the primary obstacles to scaling:
- skills gaps in AI or data science (43.0%),
- legacy automation systems and infrastructure (37.5%),
- lack of contextualized operational data (36.3%),
- workforce resistance (25.7%),
All of these emerge ahead of cybersecurity or compliance concerns (21.7%).
The new paper ‘Beyond the Hype: Practical AI for Competitive Consumer Goods Manufacturing’ published recently by Schneider Electric in collaboration with AVEVA, provides guidance on successful AI implementation across the food and beverage and life sciences sectors. It outlines the pathway to autonomous operations through industrial data, modular automation, electrification and Industrial AI implementation steps.
The global 2026 Industrial AI in CPG Survey was conducted by Censuswide with a sample base of 1,453 respondents from the Food and Beverage, and Life Sciences sectors across 14 countries.
