Affiliation:
1. Operations Management, University Ramon Llull
2. Entrepreneurship and Innovation Science, University of Stuttgart
3. Business Administration, University of Stuttgart
Abstract
Abstract
Open innovation requires the correct diagnosis of the situation, a differentiated value proposal, and a coherent, consistent action plan. In at least the first phases of this related funnel, open innovation can profit tremendously from artificial intelligence (AI) applications. How? Today, numerous sources of unstructured and scattered information, which may provide strategic insights, are accessible and can be automatically and systematically scanned and analyzed by AI algorithms. For example, the main sources of a company’s strategic information are the evolving scientific research on its core competencies; the emergence of synergistic startups; the company’s expansion decisions, new product launches, patents, and research and development investments; and its economic and financial results. While open innovation is subject to human cognitive biases, AI applications help overcome these biases and use metadata far beyond human respective ecosystems. This chapter explores the possibilities and limits of AI-enabled open innovation.
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