Beyond the loop: a research agenda towards a framework for critical AI literacy in the AI-assisted literature review

Introduction. AI tools hold significant promise for enhancing the efficiency and transparency of academic literature reviews by streamlining literature search and data synthesis. However, their uncritical use poses risks to methodological rigor and academic integrity due to algorithmic bias, fabricated information (‘hallucinations’), and opaque AI processes. Current ‘human-in-the-loop’ guidelines often lack clear oversight protocols, potentially fostering intellectual passivity. Method. Through a critical literature review, this paper identifies three paradoxes: the Verification Paradox, where efficiency compromises factual integrity; the Homogenization Paradox, where bias reinforces dominant perspectives, stifling innovation; and the Automation Paradox, where opaque algorithms undermine critical thinking and rigor. Analysis/Results. To address these challenges, we propose a ‘framework for critical AI literacy in IS’, grounded in epistemological agility, methodological transparency, and ethical responsibility. This framework must offer actionable guidance for information systems scholars to responsibly integrate AI into literature reviews, ensuring human expertise and intellectual integrity remain central. Conclusion. By fostering critical engagement with AI tools, this study sets a research agenda for a robust, transparent, and ethically sound research practices in an AI-Assisted research landscape.