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Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors

Author

Listed:
  • Jan Jöhnk

    (FIM Research Center)

  • Malte Weißert

    (University of Bayreuth)

  • Katrin Wyrtki

    (FIM Research Center)

Abstract

Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important to successfully leverage AI’s business value. Thus, companies need to assess whether their assets, capabilities, and commitment are ready for the individual AI adoption purpose. Research on AI readiness and AI adoption is still in its infancy. Consequently, researchers and practitioners lack guidance on the adoption of AI. The paper presents five categories of AI readiness factors and their illustrative actionable indicators. The AI readiness factors are deduced from an in-depth interview study with 25 AI experts and triangulated with both scientific and practitioner literature. Thus, the paper provides a sound set of organizational AI readiness factors, derives corresponding indicators for AI readiness assessments, and discusses the general implications for AI adoption. This is a first step toward conceptualizing relevant organizational AI readiness factors and guiding purposeful decisions in the entire AI adoption process for both research and practice.

Suggested Citation

  • Jan Jöhnk & Malte Weißert & Katrin Wyrtki, 2021. "Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 5-20, February.
    • Handle: RePEc:spr:binfse:v:63:y:2021:i:1:d:10.1007_s12599-020-00676-7
    DOI: 10.1007/s12599-020-00676-7
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    References listed on IDEAS

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    1. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    4. Jovanovic, Boyan & Rousseau, Peter L., 2005. "General Purpose Technologies," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 18, pages 1181-1224, Elsevier.
    5. Andrew Burton-Jones & Camille Grange, 2013. "From Use to Effective Use: A Representation Theory Perspective," Information Systems Research, INFORMS, vol. 24(3), pages 632-658, September.
    6. Abdinnour-Helm, Sue & Lengnick-Hall, Mark L. & Lengnick-Hall, Cynthia A., 2003. "Pre-implementation attitudes and organizational readiness for implementing an Enterprise Resource Planning system," European Journal of Operational Research, Elsevier, vol. 146(2), pages 258-273, April.
    7. Gopalakrishnan, S. & Damanpour, F., 1997. "A review of innovation research in economics, sociology and technology management," Omega, Elsevier, vol. 25(1), pages 15-28, February.
    8. Magistretti, Stefano & Dell’Era, Claudio & Messeni Petruzzelli, Antonio, 2019. "How intelligent is Watson? Enabling digital transformation through artificial intelligence," Business Horizons, Elsevier, vol. 62(6), pages 819-829.
    9. Paul Chwelos & Izak Benbasat & Albert S. Dexter, 2001. "Research Report: Empirical Test of an EDI Adoption Model," Information Systems Research, INFORMS, vol. 12(3), pages 304-321, September.
    10. Pumplun, Luisa & Tauchert, Christoph & Heidt, Margareta, 2019. "A New Organizational Chassis for Artificial Intelligence - Exploring Organizational Readiness Factors," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112582, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Subramanian, A. & Nilakanta, S., 1996. "Organizational innovativeness: Exploring the relationship between organizational determinants of innovation, types of innovations, and measures of organizational performance," Omega, Elsevier, vol. 24(6), pages 631-647, December.
    12. Frambach, Ruud T. & Schillewaert, Niels, 2002. "Organizational innovation adoption: a multi-level framework of determinants and opportunities for future research," Journal of Business Research, Elsevier, vol. 55(2), pages 163-176, February.
    13. Constance E. Helfat & Margaret A. Peteraf, 2003. "The dynamic resource‐based view: capability lifecycles," Strategic Management Journal, Wiley Blackwell, vol. 24(10), pages 997-1010, October.
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    Cited by:

    1. Michael Weber & Martin Engert & Norman Schaffer & Jörg Weking & Helmut Krcmar, 2023. "Organizational Capabilities for AI Implementation—Coping with Inscrutability and Data Dependency in AI," Information Systems Frontiers, Springer, vol. 25(4), pages 1549-1569, August.
    2. Issa, Helmi & Jabbouri, Rachid & Palmer, Mark, 2022. "An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    3. Nick Lüthi & Christian Matt & Thomas Myrach & Iris Junglas, 2023. "Augmented Intelligence, Augmented Responsibility?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(4), pages 391-401, August.
    4. Peter Buxmann & Thomas Hess & Jason Bennett Thatcher, 2021. "AI-Based Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 1-4, February.
    5. Fatima, Samar & Desouza, Kevin C. & Dawson, Gregory S. & Denford, James S., 2022. "Interpreting national artificial intelligence plans: A screening approach for aspirations and reality," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 378-388.
    6. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    7. Michael Weber & Moritz Beutter & Jörg Weking & Markus Böhm & Helmut Krcmar, 2022. "AI Startup Business Models," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(1), pages 91-109, February.

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