Revolutionising the manufacturing industry

Artificial Intelligence (AI), encompassing machine learning and newer developments like generative and agentic AI, is at the forefront of addressing these challenges. By revolutionising procurement, production, R&D, and supply chain processes, AI is reshaping the competitive landscape and enhancing value chains.

Over 400 operations executives from 30+ countries across Europe, the Middle East, and Africa were recently surveyed to provide insights for this study. The participants are from diverse sectors like manufacturing, transport and logistics, and retail. Our findings reveal a strong belief in AI’s potential to enhance profitability, with nearly 70% expecting at least a three percentage point increase in operating profits by 2030. Over 40% anticipate a more substantial increase of five percentage points or more.

Although manufacturers are seeing promising impacts from AI, only 4% report that they are already achieving significant financial benefits and ROI, underscoring a relatively low AI maturity level. Less than a third have moved beyond initial pilot phases, and only about 8% qualify as 'AI Operations Champions,' systematically implementing AI across their enterprises. Scaling these efforts will require strategic investment, an area where companies show varied readiness levels.

Our research underscores that the rewards of AI integration are nonetheless significant. AI is enhancing decision-making, boosting productivity and flexibility, enabling the reduction of costs and increases insales and delivery volumes. Moreover, it is helping address skill gaps within the industry. 'AI Operations Champions' are reaping the most benefits, effectively scaling and integrating AI across their operations. Looking forward, survey respondents anticipate impressive improvements.

Supply chain use cases are the most widespread, but the companies we studied are taking advantage of a broad range of applications for AI. The research reveals a number of differences across industry sectors. We explore these in detail in the full paper, including practical examples. For example, the automotive industry shows particular strength in production use cases, while the pharmaceuticals, life sciences and medical technology sectors are highly active in the R&D space.

Data management emerges as the primary hurdle to AI adoption, with challenges around data availability, quality, and security. Additional concerns include the pace of technological change and the development of AI expertise.

We have identified four core principles that are critical to getting the most value from AI. In our full discussion of these principles, we include examples of what Operations Champions are already doing to drive successful implementation of AI across their organisations.

AI is undeniably transforming manufacturing. The question is no longer if or how it will impact operations, but rather how fast. Operations leaders must make bold AI investment decisions now. Revolutionise your manufacturing business today and gain a competitive edge.