Schneider Electric study shows FMCG industry accelerating adoption of industrial AI

In the conditions surrounding the rapidly increasing economic instability and growing pressure on financial margins, producers of consumer-packaged goods (CPG) are faced with two options: to transform their operations or reduce their competitiveness. New global research about the topic by Schneider Electric highlights clear tendencies for 2026 – the future belongs to those, who successfully integrate industrial artificial intelligence.

The information gathered by Schneider Electric regarding industrial artificial intelligence for CPG shows a worrying picture: until 2030, structural production costs will continue to rise, and to this day, inefficiency reaches an average of 20.3% of the final cost. Parallel to that, companies are losing 15.2% of their production revenues because of avoidable problems - including rework, inconsistent quality and inefficient utilization of assets.

The downhill trend is predicted to intensify:

• Up to 21.37% losses next year;
• Up to 29.14% by 2030.

"These indicators put the issue of efficiency at the center of strategic planning in the sector," Schneider Electric commented.

With this in mind, industrial artificial intelligence establishes itself as the next step in the development of industrial operations. It combined industrial intelligence, operational data and automation into an integrated system for taking decisions in real time.

At present, its implementation remains limited. According to Schneider Electric:

• 13% of companies indicate that artificial intelligence (AI) is fully integrated into their core processes;
• 37% expect this to happen by 2030.

By the words of Neil Smith, president of CPG at Schneider Electric, this dynamic reflects the continuing change in the industry. “Manufacturers are predicting a tripling of AI deployments by 2030, coupled with a significant shift in the returns they expect to achieve – levels seen today primarily in autonomous factories. AI has a transformative role when used as part of a broader industrial intelligence with synchronization between data, automation and real-time analytical models,” he explained.

Photo source: Schneider Electric Bulgaria