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AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots

Abhishek Kathuria et al.

Information Systems Research2026https://doi.org/10.1287/isre.2023.0588article
FT50UTD24AJG 4*ABDC A*
Weight
0.50

Abstract

We revisit the centralization–decentralization tension in the context of decentralized technology production at the AI frontier, focusing on Intelligent Process Automation (IPA) bots as a salient manifestation of the democratization of AI. IPA bots combine robotic process automation with AI technologies and process mining based on deep, mindful domain expertise. We collaborate with a Fortune 200 multinational to study how IPA projects yield successful governance outcomes of utilization and repeatability. Our research reveals that traditional centralized mandates, when paired with the unique learning and adaptive capabilities of AI systems, can actively suppress utilization and stifle organizational reuse of the bots. Conversely, democratization is no panacea. While empowerment of business users through decentralization usually leads to successful outcomes for the deployed bots, when certain boundary conditions are crossed, these same decentralized efforts can produce fragmentation in the form of one-off solutions. Our research challenges core tenets of the IT governance canon, demonstrating that centralization–decentralization logic at the AI frontier must expand to account for the evolution of governance, process, and technological characteristics to realize effective AI governance.

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https://doi.org/https://doi.org/10.1287/isre.2023.0588

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@article{abhishek2026,
  title        = {{AI Governance and the Decentralization of Technology Production: An Investigation of AI-Based IPA Bots}},
  author       = {Abhishek Kathuria et al.},
  journal      = {Information Systems Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/isre.2023.0588},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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