Bis zur Unendlichkeit und noch viel weiter? Künstliche Intelligenz als Prozesstechnologie für organisationelle Suche
Zusammenfassung der Projektergebnisse
In line with our proposal, for this project, we conducted three interconnected studies on how AI will impact the future of innovation, scrutinizing (1) its impact on how firms may search for breakthroughs, (2) how firms may introduce AI as a process technology for innovation, and (3) what boundary conditions make such an introduction more likely and more effective. In the first study, we developed a conceptual argument showcasing that while “genius” humans will most likely continuously outperform AI at breakthrough innovation, most humans are not geniuses. In turn, if AI learns techniques similar to those most of us use to be creative, the human advantage over AI may not be as large as previously often claimed for breakthrough innovation. In the second project, we studied in the field how organizations deploy artificial intelligence as a process technology. We discovered that while AI may enter the organization both in a central department as well as in decentral functions, afterwards, there is a largely identical process of central standardization followed by decentral exploration. Various factors and dynamics within this process seem to determine the efficacy AI may eventually be able to achieve. Beyond top management support and a consistent and clear vision, that included for example training as well as understanding when not to use AI, as it might erode existing learning opportunities for novice users (who will then never be able to develop the competence to aid the AI when it cannot make a clear prediction). In the third study, through a survey with several hundred organizations, we inquired what made organizations adopt AI as a process technology, and, in particular, whether these factors would similarly explain if an organization used AI more, and more successfully. Here, we noted that the factors that explain the adoption and diffusion of AI are different: for example, while more resources made it more likely that an organization would experiment with AI, that did not lead the organization to make more use of it. Through these projects, we eventually hope to present substantial extensions to academic debates around how AI changes our existing theories of innovation, in particular those looking at innovation as organizational search, in the leading academic journals in strategy, organization theory, and innovation management.
Projektbezogene Publikationen (Auswahl)
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Innovation and the Asymptotic Rationality of Artificial Intelligence. Soph.I.A. Antipolis, Nice, France.
Huber, D. M., Reetz, D. K. & Alexy, O.
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Innovation and the Asymptotic Rationality of Artificial Intelligence. Strategic Management Society 42nd Annual Conference, London, UK.
Huber, D. M., Reetz, D. K. & Alexy, O.
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Innovation and the Asymptotic Rationality of Artificial Intelligence. Strategic Management Society Special Conference on Governing Knowledge and Imagination in the Digital Era, Milan, Italy.
Huber, D. M., Reetz, D. K. & Alexy, O.
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Innovation and the Asymptotic Rationality of Artificial Intelligence. Vienna Conference on Strategy, Organizational Design and Innovation, Vienna.
Huber, D. M., Reetz, D. K. & Alexy, O.
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Introducing AI: The Search for Structure in Managing a General Purpose Technology. Academy of Management Proceedings, 2023(1).
Huber, David Michael
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Measuring AI Integration – A Quantification of Structural Determinants for AI Depth and Breadth in Organizations. Druid24, Nice, France.
Huber, D. M.
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Organizing for AI - Multiple Goals, Structural Dynamics, and the Introduction of a General Purpose Technology. Organization Science Winter Conference, Zurich.
Huber, D. M. & Reetz, D. K.
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Organizing for AI - Multiple Goals, Structural Dynamics, and the Introduction of a General Purpose Technology. Strategic Management Society 44th Annual Conference, Istanbul, Turkey.
Huber, D. M. & Reetz, D. K.
