Robotic Process Automation (RPA) is an emerging technology that enables the automation of rules-based business processes and tasks through the use of software bots. Drawing upon the theory of Task-Technology Fit (TTF) and Technology-to-Performance Chain (TPC) (Goodhue and Thompson 1995) and research on expert systems (Messier and Hansen 1987; Sutton 1990), this study explores emerging themes surrounding bot implementation for accounting and finance tasks. We collect and analyze interview data from adopters of RPA and document task suitability, task-technology fit, implementation issues, and resulting performance outcomes. We find that securing technical capability is only a part of RPA implementation process. Organizations engage in standardization and optimization of processes, develop scorecard-like tools to rank tasks, adjust governance structures to include digital employees, and redefine internal controls. Organizations benefit from automating only certain processes, those that are structured, repeated, rules-based, and with digital inputs. Along with cost savings, organizations experience improved process documentation, lower error rates, more accurate measurement of process performance, and better report quality.

机器人流程自动化（RPA）是一项新兴技术，可通过使用软件bot来实现基于规则的业务流程和任务的自动化。基于任务技术适应性（TTF）和技术绩效链（TPC）的理论（Goodhue和Thompson 1995）以及专家系统的研究（Messier和Hansen 1987； Sutton 1990），该研究探索了围绕机器人的新兴主题。实施会计和财务任务。我们从RPA的采用者那里收集和分析采访数据，并记录任务适用性，任务技术适合性，实施问题以及由此产生的绩效结果。我们发现，确保技术能力只是RPA实施过程的一部分。组织致力于流程的标准化和优化，开发类似记分卡的工具来对任务进行排名，调整治理结构以包括数字员工，并重新定义内部控制。组织只能从某些特定的流程中自动化，这些流程是结构化的，重复的，基于规则的以及带有数字输入的流程。除了节省成本外，组织还体验到改进的过程文档，更低的错误率，更准确的过程性能度量以及更好的报告质量。