<p>The integration of artificial intelligence into research in the humanities and social sciences goes beyond a technological innovation and requires rethinking the relationship between scientific methodology, researcher identity, and ethical responsibility. Despite rapid advances of AI in the natural sciences, scholars in the humanities and social sciences continue to face an adaptation gap shaped by cognitive uncertainty and ethical tension. To address this challenge, the present study adopts a two-stage hybrid methodology grounded in a pragmatic paradigm. In the first stage, PRISMA-based systematic literature review synthesizing evidence from 82 core studies was conducted to develop an integrated conceptual model explaining researchers’ intention to adapt to AI. In the second stage, the model was empirically tested using covariance-based structural equation modeling (CB-SEM) on a transnational sample of 687 humanities and social sciences researchers from 15 countries. The findings suggest that adaptation to AI is driven less by technical efficiency alone and more by the alignment of AI tools with epistemological logics, social legitimacy within academic communities, and individual ethical commitments. AI is not approached merely as a functional instrument but as a methodological partner whose acceptance depends on compatibility with scholarly identity and normative expectations of scientific practice. Notably, the absence of a meaningful effect of research experience indicates that AI operates as a form of “skill reset,” challenging traditional experience-based hierarchies in academic research. Overall, this study proposes an ethically informed explanatory–prescriptive framework for understanding sustainable AI adoption in the humanities and social sciences.</p>