TY - CHAP
T1 - Connecting the (invisible) dots
T2 - When artificial intelligence meets open innovation
AU - Ferrás-Hernández, X.
AU - Nylund, Petra
AU - Brem, Alexander
N1 - Publisher Copyright:
© Oxford University Press 2024. All rights reserved.
PY - 2024/2/22
Y1 - 2024/2/22
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Innovation ecosystem
KW - Machine learning
KW - Metadata
KW - Open innovation
UR - http://www.scopus.com/inward/record.url?scp=85198590052&partnerID=8YFLogxK
U2 - 10.1093/oxfordhb/9780192899798.013.31
DO - 10.1093/oxfordhb/9780192899798.013.31
M3 - Chapter
AN - SCOPUS:85198590052
SN - 9780192899798
SP - 519
EP - 532
BT - The Oxford Handbook of Open Innovation
PB - Oxford University Press (OUP)
ER -