Keicher, LukasLukasKeicherArdilio, AntoninoAntoninoArdilioNawroth, GeorgGeorgNawroth2022-10-262022-10-262022https://publica.fraunhofer.de/handle/publica/42798810.23919/PICMET53225.2022.9882591Today enterprises must encounter more challenges than ever: besides dealing with global markets/competitors and an increasing flood of freely available information, the rising demand for individualized solutions, the ever-shorter life cycles of technologies and products, the digitalization pressure and the effects of Covid-19 are only a few more examples for challenges. All these challenges have indirect and direct impacts on the company's innovation activities. To face the innovation tasks deriving from the above-mentioned challenges, Artificial Intelligence (AI) could be a key technology. Due to the increasingly developed capabilities of this technology and the already explored application opportunities, the implementation of AI in the innovation process (as cost-intensive activity) can be highly relevant. Therefore, this study conducts a desktop research of existing application scenarios of AI in innovation management and examines what different subsets of AI (such as learning or speech recognition) are existing. Moreover, it will examined which subsets of AI can additionally support innovation managers in different tasks of the single phases within the innovation process and how to apply these subsets of AI to these tasks. As a result, recommendations for the usage of specific subsets of AI for the individual tasks in innovation management will be given.enconference paper