AI in CPG Survey reveals gap between ambition and reality

The survey reveals 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.

In the UK & Ireland, revenue losses linked to CPG manufacturing inefficiencies average 17.8% (mean % average) today. These preventable losses are expected to worsen sharply, reaching 24.5% next year and 34.0% by 2030, based on responses from UK&I-based food and beverage and life science manufacturing decision-makers. Many CPG manufacturers are betting on industrial AI to cut the projected rise in preventable production losses.

Lewis Winch, UK&I CPG segment leader, industrial and process automation at Schneider Electric said: “For most CPG manufacturers, the question is no longer whether AI matters to them, but how to make it work on the factory floor. Many are still constrained by ageing automation, fragmented data and the reality of keeping production running. What we’re seeing is a shift toward practical, step by step modernisation – strengthening data foundations and upgrading control systems so AI can be applied where it directly improves throughput, quality and reliability. Those who build these foundations now will be the ones able to scale industrial AI with confidence and protect their competitiveness over the next decade.”

AI expectations surge while readiness lags

Today, just one in eight (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, a tripling of adoption in just four years.

Respondents also expect AI-driven Return on Investment (ROI) to rise sharply:

• A third (32.7%) anticipate returns of 50-74% on their AI projects by 2030
• Nearly a tenth (7.9%) forecast returns of above 100%, meaning AI investments would pay for themselves in under a year.

This level of performance today is seen only in WEF Lighthouses or autonomous factories.

In contrast, 70% of respondents say current AI ROI is under 20%, with nearly a third (28.4%) seeing ROI of 5% or less, reflecting an industry still extracting limited value from early-stage deployments.

Neil Smith, president, CPG, Schneider Electric, commented: “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 synchronised decisions that improve efficiency at scale. 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.”

The barrier is not AI technology, it’s foundational readiness for industrial intelligence

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 contextualised operational data (36.3%),
• Workforce resistance (25.7%).

All of these emerge ahead of cybersecurity or compliance concerns (21.7%).

Cecile Vercellino, SVP services, industrial automation at Schneider Electric, commented: “The results are clear: delivering the transformational ROI expected for industrial AI in just four years requires a step change in collaboration, transparency and shared standards. Through SE Advisory Services, we are already applying our own Lighthouse manufacturing know-how with customers around the world, helping them turn digital ambition into measurable impact. We believe that sharing and deploying best practices and sector-specific expertise will catalyse the next wave of industrial digital transformation.”

The new paper: “Beyond the Hype: Practical AI for Competitive Consumer Goods Manufacturing” published 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.

Dowload the report here