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Decentralization, Blockchain, Artificial Intelligence (AI): Challenges and Opportunities

Author(s)
Hui, Xiang; Tucker, Catherine
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Abstract
New technologies like blockchain allow firms to decentralize core functions, forcing managers to reconsider the trade-off be-tween closed, proprietary control and open strategies that involve external contributors. While proponents often advocate forfull decentralization, we argue this view overlooks important economic trade-offs. We propose that the better strategy is selectivedecentralization: a disciplined approach to choosing where to centralize for efficiency and where to decentralize for innovation.We propose a three-level framework—Infrastructure, Decision-Making, and Operational Control—to guide this choice, helpingmanagers analyze the specific costs and benefits at each layer. We apply this framework to the strategic adoption of ArtificialIntelligence (AI), where the technology's powerful pull toward centralization provides a stark test case. Our analysis shows thatan “open source AI” strategy—decentralizing operations to foster innovation while keeping infrastructure centralized for effi-ciency—is more pragmatic than full decentralization. Selective decentralization therefore emerges as a key managerial capabilityfor capturing blockchain's benefits without sacrificing scale efficiencies.
Date issued
2025-07-22
URI
https://hdl.handle.net/1721.1/163403
Department
Sloan School of Management
Journal
Journal of Product Innovation Management
Publisher
Wiley
Citation
Hui, X., and C. Tucker. 2025. “ Decentralization, Blockchain, Artificial Intelligence (AI): Challenges and Opportunities.” Journal of Product Innovation Management 42, no. 5: 947–957.
Version: Final published version
ISSN
0737-6782
1540-5885

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