Artificial intelligence–enabled Lean Six Sigma: a bibliometric and thematic review toward smart operational excellence

Purpose This study aims to examine the integration of artificial intelligence (AI) with Lean, Six Sigma and Lean Six Sigma (LSS) and develop a conceptual framework for AI-enabled operational excellence. Design/methodology/approach A combined bibliometric and thematic review was conducted using 52 Scopus-indexed journal articles. Publication trends, co-authorship, keyword co-occurrence, citation patterns and bibliographic coupling were integrated with qualitative thematic synthesis. Findings The field has progressed from Lean–Industry 4.0 alignment toward AI-enabled process improvement, LSS4.0, digitally enhanced define–measure–analyze–improve–control and decision intelligence. Five themes emerged: Lean digital transformation, AI-supported Six Sigma, LSS4.0 integration, AI-enabled decision intelligence and sustainability-oriented performance. Research limitations/implications The Scopus-only journal corpus may exclude relevant contributions. Future studies should empirically validate the framework and examine sector-specific applications and human–AI collaboration. Practical implications The framework guides organizations in aligning data infrastructure, AI capabilities, improvement routines, workforce competencies, leadership and governance when developing AI-enabled LSS systems. Social implications Responsible integration may support resource efficiency, sustainability, workforce development, transparency and accountability in AI-supported improvement decisions. Originality/value This study consolidates fragmented research into an evidence-informed framework connecting digital infrastructure, AI capability, process-improvement logic, organizational enablement and governance and value realization.