BCG-WEF Project: AI-Powered Industrial Operations

AI-Powered Industrial Operations: AI Survey Results

The world of industrial operations is changing, and manufacturing companies are facing considerable challenges—including rising economic pressure, the sustainability imperative, volatile resource prices, and supply chain disruptions as well as increasing capability challenges and talent shortages. In this complex environment, the expanding role of data and advanced manufacturing technologies such as artificial intelligence (AI) offers companies new opportunities to address these challenges and to significantly augment industrial operations.

To evaluate the current state of AI within industrial operations, BCG conducted a global survey of almost 1,800 manufacturing executives. The survey covered seven different industries across 15 nations worldwide.

What We Learned

Here are five key takeaways from the survey:

• AI is highly relevant to industrial operations: 89% of companies plan to implement AI in their production networks. 
• AI is boosting production efficiency: early adopters saw 14% savings on addressed manufacturing costs. 
• Adoption is increasing: 68% of companies have already started implementing AI solutions. 
• It’s not a sure-fire success: only 16% of companies have achieved their AI-related targets. 
• Scaling is particularly difficult: 98% of companies face challenges scaling their AI solutions. 

Among our other findings: Manufacturers in China and India lead those of other nations in terms of AI maturity, while among industries, technology equipment manufacturers are most mature in their use of AI. Quality control, robotics and production automation, production alert systems, and inventory optimization are some of the leading AI use cases for industrial operations, according to the study. But even the most common use cases were relatively immature—25% or less of the companies surveyed had fully rolled out those applications.

When it comes to the barriers to scaling AI throughout their production networks, 88% of executives named a lack of AI-related technology infrastructure as a major challenge, with data processing (34%) and visualization infrastructure (34%) being the most common areas of concern. Meanwhile, 92% of executives said the lack of an AI-related people and organization foundation was a challenge, with a shortage of digital skills and capabilities (39%) and the lack of an AI strategy and roadmap (33%) being cited most often.

The survey results underline both the relevance and potential of AI for industrial operations. Manufacturers who act now to incorporate AI solutions can gain a significant advantage in addressing today’s challenges, while those who delay risk falling further behind.