Do we have the knowledge we need? Rethinking human-AI decision-making in corporations
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Abstract (arXiv)
Organizational knowledge is fragmented across a variety of software systems, tacit expertise, and manual documents that have traditionally been designed for human consumption. As AI systems are increasingly deployed and granted decision-making roles, they require access to this knowledge. This raises two questions: how should organizations store and maintain knowledge so that it remains accessible to both humans and future AI systems, and how should agency be allocated between humans and AI across tasks with different risks and levels of uncertainty? In this position paper, we describe how organizational knowledge evolves and contribute a framework that maps task attributes and knowledge availability to recommended agency allocations and control mechanisms. We illustrate the applicability of the framework on two different manufacturing tasks: a routine operation (visual quality inspection) and a one-off strategic decision (factory location), and conclude with opportunities for future research.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 19 references that are in the map. First posted on arXiv 2 Apr 2026.
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References · 4
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2025Levels of Autonomy for AI Agentscited by 48
- 2023Neurosymbolic AI for Reasoning over Knowledge Graphs: A Surveycited by 21
- 2024Deconstructing Human-AI Collaboration: Agency, Interaction, and Adaptationcited by 8
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