A new study by Schneider Electric warns that consumer packaged goods (CPG) manufacturers could face severe production losses and escalating cost pressures by 2030 if they fail to adopt artificial intelligence (AI) more aggressively. The research indicates that manufacturing delays, increased downtime, and equipment failures are expected to undermine operational efficiency and output significantly.
Key Findings of the Study
The study, which surveyed 1,453 global executives, reveals a widening gap between AI return on investment (ROI) ambitions and operational reality in the CPG sector. Currently, inefficiencies such as manufacturing delays, downtime, and equipment failure account for an estimated 20.3% of the final manufactured product cost. Respondents report that 15.2% of mean manufacturing revenue is already lost due to delays, downtime, rework, quality deviations, or suboptimal asset use.
These preventable losses are projected to worsen sharply, reaching 21.37% next year and rising toward 29.14% by 2030. The report emphasizes that CPG companies must turn to industrial intelligence—combining AI, data, and automation—to reinforce competitiveness in an era of accelerating volatility.
AI Adoption and ROI Expectations
While many CPG manufacturers are betting on industrial AI to cut projected losses, the study finds that only about 13% of manufacturers have fully integrated AI across core operations and decision-making processes. Respondents expect AI-driven ROI to rise sharply, with 32.7% anticipating returns of 50–74% on AI projects by 2030, and 7.9% forecasting returns above 100%.
Neil Smith, President of CPG at Schneider Electric, noted that manufacturers project a tripling of end-to-end AI adoption by 2030, alongside significant increases in expected returns. However, he described the widening expectation gap as the strongest signal of urgency seen in years. AI can only be transformative when it delivers true industrial intelligence, enabling real-time operational data, modern automation, and synchronized decision-making at scale.
Challenges and Recommendations
Smith stressed that many organizations still operate brownfield sites with fragmented data and legacy systems that limit AI’s value and adoption. Closing this readiness gap is now a top competitiveness priority for the CPG sector. Ajibola Akindele, Country President of Schneider Electric West Africa, added that delivering transformational ROI from industrial AI within four years will require a step change in collaboration, transparency, and shared standards. Sharing best practices and sector-specific expertise will be key to driving the next wave of industrial digital transformation.
