Creating business value through intelligent automation: a task-technology fit analysis

Purpose This paper examines how intelligent automation (IA) creates business value and how different value-creation pathways depend on the alignment between task characteristics and IA capabilities from a Task-Technology Fit perspective. Design/methodology/approach The study adopts a qualitative research design based on 25 IA implementation projects delivered by 2 global AI integrator firms across multiple industries. Guided by a realist and configurational perspective, the analysis combines Context–Mechanism–Outcome intra-case analysis with systematic cross-case comparison to identify theoretically informed and empirically grounded IA value-creation pathways. Findings The findings show five recurrent IA value-creation pathways: (1) efficiency improvement; (2) cost reduction and financial gains; (3) quality and compliance enhancement; (4) customer and employee experience improvement; and (5) integration and innovation. The study further shows that performance outcomes vary according to the fit between task characteristics and IA capabilities. Lower-level automation mainly generates efficiency and cost benefits in structured and rule-based contexts, whereas higher-level IA orchestration enables broader integration, innovation and strategic outcomes. Originality/value This study provides an integrated theoretical lens for understanding how IA creates business value across operational and strategic levels. The study also provides a practical framework that helps managers and AI integrators align IA solutions with task and process requirements, supporting effective implementation strategies and holistic performance metrics.