Innovation Management for Artificial Intelligence

Patrick Glauner ()
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Patrick Glauner: Deggendorf Institute of Technology

Chapter 1 in Creating Innovation Spaces, 2021, pp 1-13 from Springer

Abstract: Abstract While there have been a large number of artificial intelligence (AI) research outputs in recent years, managers and practitioners often struggle to turn those into concrete value-adding products. One of the reasons is a lack of innovation management for AI. This chapter connects these dots and demonstrates how successful AI innovation management can be done. Key to turning AI research into concrete AI-based products is building ecosystems that are fruitful, cutting-edge and sustainable. As an outcome, readers can follow our best practices when working towards their own cutting-edge AI products, while getting the big picture of AI, its promise and contemporary challenges.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-3-030-57642-4_1

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DOI: 10.1007/978-3-030-57642-4_1

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