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Jowat SE launches company-wide AI strategy with Fraunhofer IEM
The targeted use of AI is no longer just a matter of technological progress. It is becoming a strategic factor. Jowat SE, a leading manufacturer of industrial adhesives, has therefore launched a company-wide AI strategy in collaboration with Fraunhofer IEM. The project shows how companies can leverage their potential and position themselves for the future with a structured approach—in line with the transfer goals of the Engineering Automation High-Performance Center.
Jowat SE had already successfully piloted initial AI solutions in the past. However, a holistic approach, clear responsibilities, and comprehensive integration into the organization were lacking until now. The aim of the project was therefore to lay the foundations for a company-wide AI implementation.
The first step was a comprehensive maturity analysis. Interviews with various departments identified the status quo and digital potential. It emerged that extensive data sets with high usability for AI already exist, but data integration, structuring, and networking are often still lacking.
In several workshops, 47 specific AI use cases were identified, prioritized, and assigned measures. These included the use case “Intelligent Design of Experiments” which can significantly accelerate the development of new adhesives. The use cases were not only classified according to effort and benefit, but also evaluated for their scalability.
The researchers developed practical recommendations for the next steps: a common vision, accessible documented roadmaps, targeted piloting in the specialist areas, and early scalability of the solutions. With these results, Jowat SE now has a solid foundation for the strategic further development of its AI activities.
The project with Jowat SE exemplifies how companies can build and expand their AI expertise with the help of structured methods and accompanying research. The Engineering Automation High-Performance Center supports companies with individual formats such as potential analysis, use case workshops, and piloting generative AI solutions in the engineering environment.
