How EU manufacturers use AI
Among EU manufacturers that use AI, the most common applications are not on the factory floor: in 2024 about 27.1% used AI for marketing and sales, narrowly ahead of 26.2% using it for production processes. Manufacturers mostly buy AI ready-made — around 6% used off-the-shelf commercial software, while fewer than 2% developed AI in-house.
What it means
Even in manufacturing, AI is applied to marketing and sales as often as to production itself — and most firms buy it ready-made rather than build it. For an operator the practical lesson is that the fastest, lowest-risk entry point to industrial AI is usually a commercial off-the-shelf tool applied to a clear business problem, not a bespoke in-house data-science project.
Context
Eurostat's isoc_eb_ain2 dataset breaks AI use down by NACE activity, including manufacturing, for the 2024 reference year. Shares describe what AI-using manufacturers apply the technology to and how they source it; production processes and marketing/sales lead, with logistics, administration and other functions behind. Because the base is firms that already use AI, these percentages describe usage patterns, not overall adoption across all manufacturers.
How to interpret this data
About the source: This data comes from Eurostat. Public datasets like this are the foundation of fact-based decision-making in industry. When you see these numbers cited in vendor proposals or consultant reports, remember: the raw data is freely available, and the value is in how you interpret it for your specific plant and situation.
Where this matters: Generative AI in manufacturing, AI agents for industrial maintenance are built on insights like the data shown here. Rather than treat data in isolation, read the deeper guides to see how these trends translate into actionable levers for your plant.
Sector relevance: This dataset is especially relevant to Food Processing, Chemicals. These sectors face the trends and challenges you see in this chart daily — energy cost pressure, the push for decarbonization, adoption of AI and predictive maintenance. Use this data to benchmark your plant against the industry average and identify where you lag or lead.
How to use this data: Take the headline number but look deeper at the chart. Is it growing or shrinking? Which segments or regions drive the trend? Does your plant's data align, or are you an outlier? Outliers are often where the best opportunities hide — either an efficiency gap you can exploit, or a leading practice you can copy.
Related charts
How widely manufacturers have adopted AI
Industrial robot installations worldwide
Robot density in manufacturing
Related topics
Generative AI in Manufacturing: Practical Examples · AI Agents for Industrial Maintenance: What They Are and Where They Help · Machine Learning (Industrial) · Generative AI
Relevant to: Food Processing · Chemicals · Steel & Metals