The Changing Landscape of Behavioral IS Research: Navigating Agentic, Epistemic, and Cognitive Shifts

This editorial essay examines how contemporary artificial intelligence is reshaping the intellectual terrain of behavioral Information Systems (IS) research. We argue that AI gives rise to three interrelated shifts that warrant systematic attention: an agentic shift, in which action, delegation, autonomy, and accountability are redistributed across human-AI ensembles; an epistemic shift, in which knowledge and judgment increasingly operate under conditions of opacity and probabilistic performance; and a cognitive shift, in which human thought is progressively recomposed through repeated interaction with systems that generate, frame, and refine thought-like outputs. We outline a research agenda comprising several research problems within each shift that IS researchers need to address. We also discuss broader implications of these shifts for theory, methods, and society. Taken together, these shifts challenge several assumptions that have long underpinned behavioral IS research, including treating technology as a bounded artifact, expecting intelligible causal pathways, and assuming the relative stability of the relationship between human cognition and its support by IS.