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Managing innovation in the era of AI

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  • Tekic, Zeljko
  • Füller, Johann

Abstract

This paper conceptualizes how artificial intelligence (AI) may impact the way companies innovate and manage their innovation process. A research framework we use in investigation builds upon three pillars – data, new tech, and talent. Based on it, we map and discuss changes for organizations applying AI in innovation management. We conceptualize innovation management in the era of AI as a data-driven process in which AI significantly affects all dimensions of the innovation process and its management. Further, our framework suggests that the need for data, technology, and talents will lead to more open and collaborative innovation approaches, novel strategies for innovation protection, and the emergence of new roles in innovation teams. Using AI for innovation management also creates challenges like ethical data usage, navigation through diversity emerging from humans collaborating with artificial intelligence, and escaping from the incremental innovation trap. We summarize our main conclusions as research propositions and outline their practical implications.

Suggested Citation

  • Tekic, Zeljko & Füller, Johann, 2023. "Managing innovation in the era of AI," Technology in Society, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:teinso:v:73:y:2023:i:c:s0160791x23000593
    DOI: 10.1016/j.techsoc.2023.102254
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    Citations

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    Cited by:

    1. Undheim, Trond Arne, 2024. "In search of better methods for the longitudinal assessment of tech-derived X-risks: How five leading scenario planning efforts can help," Technology in Society, Elsevier, vol. 77(C).
    2. Ullah, Rafid & Ismail, Hishamuddin Bin & Islam Khan, Mohammad Tariqul & Zeb, Ali, 2024. "Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy," Technology in Society, Elsevier, vol. 76(C).
    3. Roppelt, Julia Stefanie & Kanbach, Dominik K. & Kraus, Sascha, 2024. "Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors," Technology in Society, Elsevier, vol. 76(C).
    4. Barenji, Reza Vatankhah & Hariry, Reza Ebrahimi & Demirkol, Denizhan & Daim, Tugrul U., 2024. "Research landscape analysis for quality in Pharma 4.0 era," Technology in Society, Elsevier, vol. 76(C).
    5. Huang, Lei & Ladikas, Miltos & Schippl, Jens & He, Guangxi & Hahn, Julia, 2023. "Knowledge mapping of an artificial intelligence application scenario: A bibliometric analysis of the basic research of data-driven autonomous vehicles," Technology in Society, Elsevier, vol. 75(C).
    6. Wang, Mingsheng & Huang, Yong, 2024. "A digital Technology–Cultural resource strategy to drive innovation in cultural industries: A dynamic analysis based on machine learning," Technology in Society, Elsevier, vol. 77(C).
    7. Jin, Minghui & Chen, Yang, 2024. "Has green innovation been improved by intelligent manufacturing?—Evidence from listed Chinese manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    8. Ali, Omar & Murray, Peter A. & Momin, Mujtaba & Al-Anzi, Fawaz S., 2023. "The knowledge and innovation challenges of ChatGPT: A scoping review," Technology in Society, Elsevier, vol. 75(C).
    9. Koc, Erdogan & Hatipoglu, Sercan & Kivrak, Oguzhan & Celik, Cemal & Koc, Kaan, 2023. "Houston, we have a problem!: The use of ChatGPT in responding to customer complaints," Technology in Society, Elsevier, vol. 74(C).

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