Robotic Process Automation in Public Accounting

Abstract

SYNOPSIS We investigate the implementation of Robotic Process Automation (RPA) software in public accounting by interviewing RPA leaders at Big 4 firms. RPA software automates the input, processing, and output of data to streamline repetitive, mundane tasks. Many of our findings are unique to accounting. For instance, participants report tax services are furthest along in RPA adoption, followed by advisory and assurance services. Furthermore, RPA has not impacted fees, but there is concern that clients may desire fee reductions due to decreased employee hours. Finally, unlike other technology implementations, RPA adoption is driven primarily by lower-level employees. Similar to other domains, our results indicate massive efficiency and effectiveness gains from RPA implementation. Also, interviewees do not expect reduced head count to result from RPA use. This study is the first to discuss the benefits, opportunities, and challenges to implementing RPA in accounting and serves as a catalyst for future research.

A profession in transition: actors, tasks and roles in AI-based accounting

“…(Marrone and Hazelton, 2019) (3) How can we organise effective, efficient and agile accounting structures, processes and teams that transcend geographical and cultural boundaries? (Brynjolfsson and Hitt, 2000;Cooper et al, 2019;Vial, 2019) (4) How will we effectively collaborate and communicate within heterogenous and disclocated, mixed AI and human accounting teams and external (artificial) partners (e.g. chatbots)?…”

“…It often refers to the digital networking of different areas and players (Bou ee and Schaible, 2015;Hansen and Sia, 2015;Tan et al, 2015), the digitalisation of overarching processes (Bowersox et al, 2005), the use of digital technologies for a wider reach or the reorientation of companies or even the disruption of markets and existing goods and services (Pavlou and El Sawy, 2010;Vial, 2019). In accounting, for example, integrated systems (Galani et al, 2010), software robots (Cooper et al, 2019), cloud solutions (Huttunen et al, 2019), blockchain technology (Bons on and Bedn arov a, 2019;McCallig et al, 2019) and AI and further smart digital technology (Greenman, 2017) changed or will change the workflow and processes of accounting (Diller et al, 2020;Susskind, 2017) in the future (Diller et al, 2020;Marrone and Hazelton, 2019;Oesterreich et al, 2019).The future of automation in accounting could be seen in the increased use of self-learning AI-based integrated systems, which access actual data in real time and, based on this, independently develop solutions, suggestions, forecasts and trends (Najderek, 2020).…”

“…Software robots (robotic process automation [RPA]) have already taken over routine tasks (Cooper et al, 2019) and are gradually providing more and more support in non-routine tasks that require decisions on complex and novel situations and flexibility (Autor and Dorn, 2013;Autor et al, 2003;Frey and Osborne, 2017) leading to a higher accounting efficiency (Guthrie and Parker, 2016). In the future, these "smart" AI-based software robots will also be in charge of highly complex tasks such as fraud detection and liquidity planning (Brynjolfsson and McAfee, 2014;Skrbi s and Jacqueline, 2019), improving the effectiveness of accounting organisations.…”

Limits of artificial intelligence in controlling and the ways forward: a call for future accounting research

“…(4) To what extent should AI-based robots (Cooper et al, 2019;Rozario and Vasarhelyi, 2018) be seen as actors in a network and how can we find out about their agency?…”

“…From this perspective, we identified the following salient questions:How will future accounting organisations look like in terms of structure and hierarchies (Kruskopf et al , 2020)?What is the role of societal values and their transformation in a digital age (Diller et al , 2020; Troshani et al , 2019; Vial, 2019) in the changes in the “whatness” of accounting?How can further system-theoretic and cybernetic approaches help to mitigate the overpromises of AI in terms of organisational capabilities?To what extent should AI-based robots (Cooper et al , 2019; Rozario and Vasarhelyi, 2018) be seen as actors in a network and how can we find out about their agency?How will AI transform not only the practices but also the structure as a result of their enactment?What is the role of technological leadership and change management (Makrygiannakis and Jack, 2016) in this?…”