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

Abstract

New technologies like blockchain allow firms to decentralize core functions, forcing managers to reconsider the trade-off between closed, proprietary control and open strategies that involve external contributors. While proponents often advocate for full decentralization, we argue this view overlooks important economic trade-offs. We propose that the better strategy is selective decentralization: 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, helping managers analyze the specific costs and benefits at each layer. We apply this framework to the strategic adoption of Artificial Intelligence (AI), where the technology's powerful pull toward centralization provides a stark test case. Our analysis shows that an “open source AI” strategy—decentralizing operations to foster innovation while keeping infrastructure centralized for efficiency—is more pragmatic than full decentralization. Selective decentralization therefore emerges as a key managerial capability for capturing blockchain's benefits without sacrificing scale efficiencies.