AI-enhanced literature reviews: liberating scholars for impact in service marketing

Purpose This viewpoint article examines how artifical intelligence (AI) is transforming service marketing research specifically by enhancing literature reviews, thereby freeing scholars to focus on developing more meaningful theoretical, managerial and societal implications. Design/methodology/approach The paper synthesizes established publishing guidelines with emerging AI applications in research, connecting these developments to Association to Advance Collegiate Schools of Business (AACSB)’s 2020 emphasis on societal impact. It explores how AI can address traditional research challenges while democratizing high-quality scholarship across diverse institutional contexts. Findings AI tools significantly enhance literature review comprehensiveness and efficiency, allowing researchers to redirect intellectual energy toward impact-focused outcomes. The paper identifies specific strategies for maintaining critical judgment while using AI throughout the research process, from literature synthesis through implications development. Research limitations/implications The framework offers pathways for researchers at both research-intensive and teaching-intensive institutions to enhance their scholarly contributions. It particularly benefits faculty with heavy teaching loads by compressing initial research stages, potentially diversifying the perspectives represented in marketing scholarship. Practical implications The paper provides actionable guidance for researchers seeking to integrate AI into their workflow while maintaining scholarly integrity. It also offers journal editors and doctoral program directors perspective on evaluating and teaching AI-assisted research methods. Social implications By emphasizing societal impact and providing structured approaches to operationalize such considerations throughout the research process, the paper supports AACSB’s vision of business schools as positive forces for change while addressing the challenge of documenting noncitation forms of impact. Originality/value This is among the first comprehensive frameworks for integrating AI into academic marketing research while enhancing rather than compromising scholarly values. It reconceptualizes the research process for the AI era while addressing inequalities in research resources across institutional contexts.