Paper Number
Panel 2
Abstract
This panel examines the transformative implications of Artificial Intelligence and Large Language Models (LLMs) for organizational knowledge, expertise, and cognition. Four interconnected perspectives are explored: the emergence of un-humanlike errors when LLMs detach intelligence from sociocultural language foundations and treat it as an instance of statistical operations on data; the challenge of ensuring knowledge reliability in AI-driven contexts through the lens of inquiring systems; the organizational implications of synthetic data as a substitute for experience-derived knowledge; and the fundamental inversion of knowledge conditions brought about by digital abundance and agentic machines. Collectively, these perspectives argue that AI does not merely automate knowledge tasks but alters the very conditions under which knowledge is created, validated, and acted upon in organizations. The panel invites the ECIS community to engage with these foundational questions at the intersection of information systems, organizations, and artificial intelligence.
Recommended Citation
Kallinikos, Jannis; Alaimo, Cristina; Berente, Nicholas; Rosa, Marta Stelmaszak; and Yoo, Youngin, "AI AND ORGANIZATIONAL KNOWLEDGE: ON DATA, COGNITION, AND EXPERT LEARNING" (2026). ECIS 2026 Proceedings. 2.
https://aisel.aisnet.org/ecis2026/panels/panels/2
AI AND ORGANIZATIONAL KNOWLEDGE: ON DATA, COGNITION, AND EXPERT LEARNING
This panel examines the transformative implications of Artificial Intelligence and Large Language Models (LLMs) for organizational knowledge, expertise, and cognition. Four interconnected perspectives are explored: the emergence of un-humanlike errors when LLMs detach intelligence from sociocultural language foundations and treat it as an instance of statistical operations on data; the challenge of ensuring knowledge reliability in AI-driven contexts through the lens of inquiring systems; the organizational implications of synthetic data as a substitute for experience-derived knowledge; and the fundamental inversion of knowledge conditions brought about by digital abundance and agentic machines. Collectively, these perspectives argue that AI does not merely automate knowledge tasks but alters the very conditions under which knowledge is created, validated, and acted upon in organizations. The panel invites the ECIS community to engage with these foundational questions at the intersection of information systems, organizations, and artificial intelligence.
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