Early evidence of digital labor in accounting: Innovation with Robotic Process Automation

Abstract

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.