<p>Large language models (LLMs) are increasingly embedded in tasks ranging from trivial queries to high-stakes decision-making. This raises pressing questions about how to attribute epistemic credit and moral responsibility to users that interact with AI for solving epistemic tasks. I argue that the cognitive status we ascribe to AI—whether as tool, extension, collaborator, or agent—cannot be fixed in the abstract but is instead shaped by contextual moral stakes. Drawing on frameworks of extended and distributed cognition, as well as debates about testimony and pragmatic encroachment, I explore a contextualist solution: in low-stakes settings, users may justifiably treat AI as if it possessed epistemic agency, but in high-stakes domains such as medicine, AI should be regarded strictly as a tool, with moral responsibility remaining exclusively human. I suggest, education offers an intermediate case, where AI may function as a cognitive extension or collaborator so long as students and teachers retain responsibility for the relevant outcomes of the learning process. I conclude that while AI can produce epistemic goods on par with human agents, its lack of moral accountability should motivate users to avoid taking outputs at face value in relevantly moral contexts. Users should therefore modulate their epistemic stance toward AI according to context, preserving human responsibility in morally charged interactions while allowing more agent-like treatment in cases where moral constraints don’t play a role.</p>