On the 16th, Schneider Electric announced the results of the '2026 Industrial AI in CPG Survey,' conducted with 1,453 executives and manufacturing decision-makers in the global consumer goods manufacturing sector. The survey was conducted to analyze the current status of AI utilization in the consumer goods manufacturing industry, future investment prospects, and challenges regarding the adoption of industrial AI.

The results of the investigation showed that production inefficiency costs resulting from manufacturing delays, plant shutdowns, and equipment breakdowns amounted to an average of 20.3% of the final product manufacturing cost. Losses resulting from production delays, rework, quality deviations, and reduced asset utilization amounted to an average of 15.2% of manufacturing sales.

Responding companies projected that the proportion of these losses would increase to 21.37% next year and reach 29.14% by 2030. Amidst expanding cost burdens, the survey found that manufacturers perceive industrial AI, which combines AI, data, and automation, as a key means for improving productivity and reducing costs.

Currently, only 13% of companies reported that AI is integrated across their entire core operations and decision-making processes. However, with 37% expected to apply AI to their core operating systems by 2030, there is significant potential for expanded adoption in the future.

Expectations for the effectiveness of AI investments were also high. 32.7% of respondents said they expected a return on investment (ROI) of 50–74% through AI projects, while 7.9% anticipated achieving an ROI of over 100%. On the other hand, current performance fell short of expectations. 70% of respondents stated that their current AI ROI was less than 20%, and among them, 28.4% said it was 5% or less.

The shortage of AI and data science personnel was identified as the biggest obstacle to the spread of AI, at 43.0%. This was followed by legacy automation systems and infrastructure at 37.5%, a lack of operational data at 36.3%, and resistance to change among organizational members at 25.7%. Cybersecurity and regulatory compliance issues were recorded at 21.7%.

Cecil Bersellino, Senior Vice President of Industrial Automation Services at Schneider Electric, explained that realizing industrial AI performance requires not only the adoption of technology but also data-driven operating systems and organizational-wide transformation.

The results of this survey are included in the report 'Beyond the Hype: Practical AI for Competitive Consumer Goods Manufacturing,' jointly published by Schneider Electric and Aveva. The report covers the current status of industrial AI adoption in the consumer goods manufacturing industry and actionable tasks for securing manufacturing competitiveness.