{"title":"How information technology automates and augments processes: Insights from Artificial-Intelligence-based systems in professional service operations","authors":"Martin Spring, James Faulconbridge, Atif Sarwar","doi":"10.1002/joom.1215","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":51097,"journal":{"name":"Journal of Operations Management","volume":"68 6-7","pages":"592-618"},"PeriodicalIF":6.5000,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/joom.1215","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Operations Management","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/joom.1215","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 12
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.
期刊介绍:
The Journal of Operations Management (JOM) is a leading academic publication dedicated to advancing the field of operations management (OM) through rigorous and original research. The journal's primary audience is the academic community, although it also values contributions that attract the interest of practitioners. However, it does not publish articles that are primarily aimed at practitioners, as academic relevance is a fundamental requirement.
JOM focuses on the management aspects of various types of operations, including manufacturing, service, and supply chain operations. The journal's scope is broad, covering both profit-oriented and non-profit organizations. The core criterion for publication is that the research question must be centered around operations management, rather than merely using operations as a context. For instance, a study on charismatic leadership in a manufacturing setting would only be within JOM's scope if it directly relates to the management of operations; the mere setting of the study is not enough.
Published papers in JOM are expected to address real-world operational questions and challenges. While not all research must be driven by practical concerns, there must be a credible link to practice that is considered from the outset of the research, not as an afterthought. Authors are cautioned against assuming that academic knowledge can be easily translated into practical applications without proper justification.
JOM's articles are abstracted and indexed by several prestigious databases and services, including Engineering Information, Inc.; Executive Sciences Institute; INSPEC; International Abstracts in Operations Research; Cambridge Scientific Abstracts; SciSearch/Science Citation Index; CompuMath Citation Index; Current Contents/Engineering, Computing & Technology; Information Access Company; and Social Sciences Citation Index. This ensures that the journal's research is widely accessible and recognized within the academic and professional communities.