Organizational knowledge is often fragmented across various software systems, tacit expertise, and manual documents designed for human consumption. As AI systems are increasingly deployed and take on decision-making roles, they require access to this knowledge. This raises two critical questions:
- How should organizations store and maintain knowledge to ensure accessibility for both humans and future AI systems?
- How should agency be allocated between humans and AI across tasks with varying 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), concluding with opportunities for future research.
Blogger's Review: This paper provides a systematic perspective on knowledge management in human-AI collaboration, highlighting the importance of appropriate agency allocation in an era where AI decision-making is becoming prevalent. Future research could further explore specific applications across different domains.