How information technology automates and augments processes: Insights from Artificial‐Intelligence‐based systems in professional service operations

Martin Spring, James Faulconbridge, Atif SarwarOperations运营分析UTD24

Journal of Operations Management2022-09-01Lancaster University; Liverpool Hope UniversityDOI

Citations189

Influential2

References57

Abstract This study contributes to the technology management literature on the effects of IT on operations processes by examining the use of systems based on Artificial Intelligence (AI) in professional services. The paper builds on key concepts on AI, information systems, professional work, and professional services operations management. A model is developed to explain how AI‐based systems combine with humans to do work, both automating and augmenting the work of the professional, leading to process improvement and extension of the service offering. The study uses case‐based research in two law firms and two accountancy firms using AI‐based systems. It shows that AI‐based systems are used selectively, mainly on high‐volume, back‐office tasks, across the sequence of stages in the professional service process—diagnosis, inference, and treatment. Automation using AI relieves professionals from repetitive tasks, while AI achieves augmentation by buffering professionals from low‐value activity, making their expertise scalable and providing new analytical insights. System use can improve performance in delivering core professional services and enable service extension into additional, high‐value advisory work. The model and research approach have potential implications for other emerging areas of technology management in OM.

Computer scienceService (business)Knowledge managementAutomationScalabilityProcess (computing)Professional servicesInformation technology consultingInformation systemArtificial intelligenceEngineering managementProcess management