Beyond the tool view of AI: Intelligent technologies and the emergence of new epistemic regimes

Abstract

What distinguishes contemporary intelligent technologies is that they produce knowledge claims that are grounded in logics quite different from those that have historically underpinned professional expertise and organizational decision making. AI systems rely on computational modeling, statistical inference, and large-scale data infrastructures. The outputs they generate are not simply new pieces of information; they are claims about what is likely, optimal, or true that are derived from patterns in data rather than from embodied experience, disciplinary training, or situated judgment. As such, they begin to unsettle established epistemic foundations within organizations, professions, and fields. This dynamic cannot be adequately described using the prevailing vocabularies of adoption, automation, augmentation, or digital transformation. Those frameworks presume that new technologies are incorporated into existing structures of authority and expertise. What we are observing is more consequential. Intelligent technologies introduce alternative bases of knowing that can rival, displace, or reconfigure existing ones. Accordingly, we propose viewing organizations not as information-processing entities but as arenas where competing epistemic regimes contend for legitimacy. In this view, organizational life involves ongoing struggles over what counts as credible evidence, who is authorized to interpret it, and how decisions ought to be justified. This shift in perspective opens a research agenda that focuses on how organizations manage clashes between computational and professional modes of reasoning, how authority is redistributed when algorithmic outputs gain standing, and how strategic action unfolds in contexts where the grounds of knowing themselves are in dispute.