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

This paper argues that artificial intelligence is reshaping service marketing research by strengthening the rigor and reach of literature reviews, which in turn frees scholars to devote more attention to richer theoretical, managerial, and societal implications. It weaves established publishing guidelines together with emerging AI applications and links these developments to the Association to Advance Collegiate Schools of Business (AACSB)’s 2020 emphasis on societal impact. In doing so, it shows how AI can relieve long-standing research bottlenecks while broadening access to high-quality scholarship across diverse institutional settings. The paper finds that AI tools markedly increase the comprehensiveness and efficiency of literature synthesis, allowing researchers to redirect intellectual energy toward impact-oriented outcomes, and it offers concrete strategies for preserving critical judgment when using AI from initial review through implications development. The framework serves faculty at both research-intensive and teaching-intensive institutions, with particular advantages for those carrying heavy teaching loads by compressing early research stages and, consequently, diversifying voices in marketing scholarship. It provides actionable guidance for integrating AI without sacrificing scholarly integrity and offers journal editors and doctoral program directors practical perspectives on evaluating and teaching AI-assisted methods. By centering societal impact and operationalizing it throughout the research process, the paper supports AACSB’s vision of business schools as engines of positive change and addresses the challenge of documenting non-citation forms of impact. It stands among the first comprehensive frameworks to reconcile AI integration with core scholarly values, reimagining the research process for the AI era while confronting resource inequalities across institutions.