Interdisciplinary Directions for Researching the Effects of Robotic Process Automation and Large Language Models on Business Processes

被引:0
|
作者
Haase, Jennifer [1 ,2 ]
Kremser, Waldemar [3 ]
Leopold, Henrik [4 ,5 ]
Mendling, Jan [1 ,2 ]
Onnasch, Linda [6 ]
Plattfaut, Ralf [7 ]
机构
[1] Humboldt Univ, Comp Sci Dept, Berlin, Germany
[2] Weizenbaum Inst, Berlin, Germany
[3] Johannes Kepler Univ Linz, Strateg Management, Linz, Austria
[4] Kuhne Logist Univ, Data Sci, Hamburg, Germany
[5] Univ Potsdam, Hasso Plattner Inst, Digital Engn Fac, Potsdam, Germany
[6] Tech Univ Berlin, Psychol Act & Automat, Berlin, Germany
[7] Univ Duisburg Essen, Informat Syst & Transformat Management, Essen, Germany
关键词
Process Automation; Large Language Models; Routine Dynamics; Human Automation Interaction; Interdisciplinary Research; HUMAN-PERFORMANCE CONSEQUENCES; SITUATION AWARENESS; DECISION AIDS; SYSTEMS; ROUTINES; BIAS; TECHNOLOGIES; COMPLACENCY; DISCIPLINE; MANAGEMENT;
D O I
10.17705/1CAIS.05421
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Rapid technological advancements, especially in artificial intelligence, robotic process automation, and large language models, have significantly transformed information systems and business processes. These shifts are characterized by the automation of tasks, reshaping traditional human-centric operations, and consequently redefining human roles and experiences. This Panel Report builds on a discussion held at the annual Routines. Research. Community workshop in March 2023 in Berlin, Germany. It integrates diverse disciplinary perspectives to offer a comprehensive understanding of process automation. The panel draws on insights into automation tools such as robotic process automation and large language models, human -automation interaction research, and the study of routine dynamics, all vital for grasping the immediate human responses and longitudinal organizational adaptations due to automation. The report highlights the need for future research to focus on user-centric design for task automation, understanding individual differences in automation effects, exploring long-term psychological impact, and developing adaptive tools and training strategies. It also calls for examining AI integration in routine tasks and RPA tools, its influence on organizational routines and culture, and the dynamics in teams with AI -based members to better understand and enhance human -automation collaboration. This interdisciplinary approach is essential for navigating the challenges and opportunities of the rapidly evolving digital landscape.
引用
收藏
页码:579 / 604
页数:28
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