arXiv:2606.15575v1 Announce Type: new Abstract: 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 uncertai
The increasing deployment of AI systems into decision-making roles within corporations necessitates a re-evaluation of how organizational knowledge is structured and accessed.
This paper highlights the critical need for corporations to proactively design knowledge management and human-AI agency allocation strategies to leverage AI effectively and responsibly.
The traditional human-centric design of organizational knowledge systems must evolve to accommodate the requirements of AI, leading to new paradigms for information storage, maintenance, and access.
- · AI-first knowledge management solution providers
- · Consultants specializing in human-AI collaboration
- · Corporations adopting advanced AI decision-making
- · Organizations with well-structured data
- · Organizations with siloed, unstructured knowledge
- · Traditional human-only decision-making processes
- · Companies slow to integrate AI into core operations
- · Legacy enterprise software vendors
Companies will begin investing in AI-compatible knowledge architectures and new governance frameworks for human-AI interaction.
The demand for specialized roles focused on designing and managing AI-ready knowledge bases and human-AI decision protocols will increase.
Successful integration could lead to significant advantages for early adopters in efficiency, innovation, and strategic responsiveness, potentially creating new market leaders.
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Read at arXiv cs.AI