Reconceptualising Research Methodology Teaching in the Age of AI to Rethink How Researchers Are Formed

Abstract

The rapid integration of artificial intelligence into academic research practices has begun to unsettle long-standing assumptions about how research methodologies are taught in education. While existing scholarships largely frame AI as a technical tool to be regulated or mastered, far less attention has been given to its implications for the teaching of research methodology itself. This conceptual paper argues that AI necessitates a fundamental shift in methodological education, from transmission of procedural research skills to the cultivation of methodological judgement. Drawing on methodological theory and contemporary debates on AI-mediated knowledge production, this paper reconceptualises AI, not merely as a support mechanism for research activities, but as a methodological actor that reshapes decisions relating to research design and theoretical development. It is contended that traditional pedagogical approaches, which emphasise method selection and procedural compliance, are increasingly inadequate in AI-augmented research environments. Rather than treating AI as a pedagogical concern, this paper situates it within the core of methodological education and argues for a recalibration of what it means to teach research methods not only in business and management studies but beyond. It advances the notion of methodological judgment as a central pedagogical aim in AI–mediated research environments. This is done through emphasis on the importance of epistemic awareness and critical engagement with AI-assisted research processes. It is the aspiration of this paper to offer a conceptual lens through which research methodology curricula may be reoriented towards cultivating researchers capable of exercising informed methodological discretion in increasingly AI-augmented contexts.