The 2024 AI in European Manufacturing Report

How European manufacturers leverage AI – and what they expect for the future .

Artificial intelligence is nothing new in manufacturing. However, it’s now reached critical mass in awareness.

The hype is everywhere. But what’s the reality for manufacturers on the ground in Europe? And how is AI being infused into manufacturing operations?

This report presents insights showing manufacturers’ priorities for AI, the main implementation challenges, and the future impact AI will have.

About the Survey

This MakerVerse survey had more than 50 respondents. The respondents were Europe-based and worked in manufacturing across different sectors.

 

AI: A Strategic Priority

Importance of Adopting AI

We asked manufacturers how important AI is from a strategic standpoint. The results show that adopting AI is essential or central to most operations. The “hype” of manufacturing today is real.

The interest in AI is understandable, as manufacturers must produce increasingly complex and higher-quality products faster than ever.

 

The Gap Between Hype and Adoption

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Here, European manufacturers show a gap between what they wish to achieve and what they currently do with AI.

Most European manufacturers aren’t using AI at all yet.

Things are different in other parts of the world. In North America, 21% of manufacturing companies say they already use an AI solution. An additional 18.5% say they’ve established AI use cases that generate business value.

 

Popular AI Applications

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While there are plenty of applications for AI in manufacturing, some key outcomes are sought.

Some of these include:

Quality Control and Inspection: Potential faults and imperfections can be automatically identified, saving time and effort. In one use case, machinery OEM reduced assembly process failures by 70%.

Optimizing Production Planning: Manufacturers strive for efficient production planning. AI-enabled production planning helps improve decision-making and adapt to rapidly changing situations in real-time.

Maintenance: Machines can undergo predictive maintenance with dynamic scheduling to ensure maximum performance with minimum downtime.

Supply Chain Management: AI can mitigate or prevent supply chain disruptions to help find alternative suppliers, onboard new suppliers, and more.

 

AI Challenges: Easier Said than Done

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Survey results show that manufacturers focus on AI in their strategies but aren’t yet integrating AI into day-to-day processes.

We wanted to know why.

The biggest challenge cited was a lack of expertise.

The high demand for AI is outpacing the available skills, showing a significant difference between the demand for the technology and the means to implement it.

 

Outlook: High Hopes for the Future

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European manufacturers may face challenges in implementing AI as freely as they’d like, but they’re optimistic about the future. They have high expectations of how AI will improve efficiency in the next few years and expect a massive impact.

 

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