Successfully managing AI projects – Arbeitswelt.Plus successfully implements pilot training course
An interest in innovation topics and AI projects as part of their day-to-day work – that was what prompted the 13 participants to take part in the ‘Successfully managing AI projects’ training course run by the Arbeitswelt.Plus competence center from January to June. The practice-oriented pilot training course provided a comprehensive insight into the topic of artificial intelligence and offered the opportunity to implement their own use cases in the company.
“Without the expertise from research, we would not have come up with our solutions so quickly. This support was very helpful for us,” says Martin Dulisch from Lödige Systems. As one of the participants, he also implemented a use case as part of the training.
From basic knowledge to practical implementation
The training started with important basic knowledge about the possible uses of AI and the associated technological, organizational and personnel changes. Experts from the Competence Center contributed their know-how and different perspectives to the five training modules. For example, they dealt with data strategies and challenges, data protection, AI regulation and the factors influencing AI. Each of the training modules was accompanied by reports from the field. Stefan Hartmann, research associate at Fraunhofer IEM, gave an insight into the Datenfabrik.NRW project, while Oliver Dietrich, project manager at IG Metall, focused on the interaction between AI and employee co-determination. After a methodical preparation for project planning, the participants got down to business and worked out the use cases for AI in their respective companies. WAGO employee Yvonne Bauer developed the content and requirements for an AI guideline that will serve as a precursor for future AI projects. Because these are already being planned or implemented (see AI for detecting product plagiarism at WAGO). For Daniel Wecker from Wöhler Technik, the aim was to develop an AI module that recognizes and classifies products using a camera system and AI-based classification, thereby optimizing the processes in incoming goods. For Wecker, it was important: “We not only received technical information, but also what the use of AI means for employees.”
Training completed – AI projects continue
And now? Most of the use cases presented will continue to be developed beyond the duration of the training. Because all participants share one learning: AI projects require resources – be it time, money or knowledge. Networks such as it’s OWL, which facilitate access to and the exchange of expertise, can be particularly helpful here. This is important to Yvonne Bauer: the exchange with other companies on use cases, challenges and solutions with AI was particularly helpful. Did you miss the training course but are also interested in the topic of artificial intelligence? Take advantage of our 26 free information and consulting services at the Arbeitswelt.Plus competence center.
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