RPA in Accounting Risk and Internal Control: Insights from RPA Program Managers

Purpose The authors share a real-world case study of a multiple-year adoption process of robotic process automation (RPA) in procurement to add to the limited empirical research base on RPA in supply chain management. The Maersk case offers hard evidence of the value of RPA that can be used as a benchmark for decision-making in companies and as a basis for further research in key areas such as change management and behavioral aspects as well as return on investment on RPA and the need for RPA capability development. Design/methodology/approach Together with the co-author from Maersk, the authors cover a multiple year RPA program in procurements, to capture lessons learned and develop research questions for the future. The authors consider 39 generic action principles for RPA adoption in a specific procurement context. Findings The authors find RPA for procurement to be an enabler of strategic progress and of advancing the concept of triple values (enterprise, customer and employee) in a supply chain setting. The authors offer RPA adoption scoping guidance and show how, with growth and maturity of the program, conditions such as predictability of volume become less relevant as a scoping criterium. The authors also find that RPA augments work rather than replace staff. Maersk utilizes staff time freed up by automation to focus employees on more strategic priorities. The authors consider 39 generic action principles for RPA adoption in a procurement-specific context and develop additional action principles based upon the Maersk case. Originality/value The authors study both a unique and rich case to complement limited empirical research on RPA in procurement and supply chain management and the limited research into RPA past early stage adoptions. The authors address Hofmann et al.'s (2019) questions about the change management involved in RPA and consider generic RPA action principles from literature in this specific procurement setting. The authors extend those action principles and develop a rich set of research opportunities.

The rising complexity of enterprise operations, coupled with the demand for real-time responsiveness, has catalyzed the integration of Robotic Process Automation (RPA) in ERP systems. SAP, being a foundational technology for many global enterprises, is now at the forefront of RPA-driven innovation. This research paper explores how intelligent automation, driven by RPA, is reshaping SAP landscapes, making them more agile, scalable, and future-ready. Drawing from the strategic implementations led by Vaibhav Gupta, Senior Director of Digital Signature and Operations at Resolve Tech Solutions, the paper provides an in-depth view of how RPA tools are being deployed to modernize traditional SAP workflows. Gupta’s approach to RPA in SAP involves identifying repetitive, rule-based processes and designing automation bots that reduce manual intervention, accelerate execution time, and ensure data integrity. By embedding RPA into core SAP modules such as FI, MM, SD, and HR, his team has enabled clients to unlock efficiency gains while minimizing human error and increasing regulatory compliance. The paper also highlights the integration of RPA tools like UiPath and SAP Intelligent RPA with both ECC and S/4HANA systems. Through detailed data analysis and real-world examples, the study showcases the transformation of legacy workflows into digitally orchestrated processes with minimal disruption. It emphasizes the importance of a well-defined automation strategy, governance model, and continuous monitoring framework to scale RPA initiatives. Additionally, it evaluates user feedback and performance metrics post-implementation. This paper serves as a blueprint for CIOs, IT leaders, and SAP architects aiming to transition toward an intelligent enterprise model. It underscores that RPA is not merely a technology trend, but a strategic enabler of next-generation business transformation within SAP ecosystems.

Objectives: Due to the explosive growth of the internet, mobile applications, machine learning, and new information technologies, new management methods that do not require face-to-face contact are spreading rapidly. Innovative approaches to process automation are needed in the era of the coronavirus disease 2019 (COVID-19) pandemic, and firms are actively adopting and implementing solutions such as robotic process automation (RPA) to increase their operational excellence. The objective of this study is to address state-of-the-art use cases of RPA by IBM Korea to determine key factors related to successful RPA implementation. Methods: Multiple case study methods and triangulation of findings were used. This study examined several cases in which RPA was implemented and proposed an analytical framework for RPA. Results: This article described IBM’s RPA usage strategies to accelerate business process management and examined four cases of RPA implementation by client firms of IBM in South Korea. This case study found that IBM’s RPA solutions positively affected the client firms’ performance, suggesting that solutions like RPA could be essential for firms’ survival due to the benefits of process automation. Conclusions: Solutions using RPA can both reduce labor costs and improve the operational excellence of firms’ internal processes. Due to the COVID-19 pandemic, process automation is increasingly essential. Practical issues such as change management and shadow work caused by process automation are discussed.

Transformative technology such as Robotic Process Automation (RPA) and Cloud Integration is the platform to achieve streamlining of operations, enhance employee productivity, and drive innovation for your business. While RPA automates repetitive, rule based work, cloud computing is the scalable, flexible and decentralized infrastructure for storing and processing of data, and collaboration. With RPA integrated with cloud platforms, organizations gain several advantages including accessibility, low cost and real time collaboration. Choosing the right cloud provider that supports RPA workloads, ensuring data flow seamlessly between RPA bots and cloud systems, and using cloud based RPA tools that can scale and that add flexibility, are the best practices for RPA and Cloud integration. It is also important to enforce robust security protocols, data governance as well as comply with risks. Integration is successful when RPA links with cloud native apps and services with as little disruption to work as possible and as much automation effect as possible. It is therefore recommended that performance monitoring, testing and continuous improvement of automation process should be given priority. Through the implementation of these best practices, organizations can attain near full potential RPA and cloud integration for operation efficiency, better customer experience and faster digital transformation. In this paper we explore the key strategies, challenges and solutions to ensure success with the integration of RPA into cloud technologies to help businesses looking to optimize the use of automation and cloud capabilities in unison.

Processes that contain repetitive and well-defined steps are more suitable for robotic process automation (RPA) than others. Many financial processes such as quarterly reports and balance sheet preparation fall into this category. Also, these processes are voluminous, making the benefits of RPA even more recognizable. Financial institutions (FIs) become aware of the benefits of RPA earlier than others and adopted RPA in many of their applications. Account reconciliations, reporting, and tax planning are among the processes that have been adapted to RPA. RPA has been a popular term in the industry for the last few years, only recently has it started to become a technology that’s within the reach of most organizations. RPA market has been almost doubling every year and it is expected to grow by more than 50 through 2020. Growth in the Turkish market is also substantial: between 2018 and 2020 more than 130 top companies have employed RPA robots in their infrastructure. Banks and technology companies in Turkey adapt RPA faster than other sectors, about 50% of the companies that adapted RPA are from these sectors. This paper discusses applications and advantages of RPA by giving examples from the finance and accounting in Turkey.

Half of the world’s population resides in cities and this percentage is going to rise in the coming years. This rapid transformation of the economy and society is making traditional city management redundant. Intensive urbanization has brought with it some challenges. Scanty resources, population growth, increased carbon footprint, reduced air quality, congestion on roads, depriving health status, and falling food quality, all are prominent parts of cities. Does this bring a question in mind is accelerated growth sustainable? The answer and solution to this is an adaption of the Smart City Concept. A smart city integrates all the available technology with the requirements of city development and builds infrastructure which can improve the quality of life of citizens. Smart cities are designed in a manner to use minimum resources with maximum efficiency in all areas of urban life. It provides smart solutions using smart technologies. Urban needs and technological advancements meet in smart cities. It manages cities more quickly and effectively by using AI, IT technologies, and robotic process automation. Intelligent transportation, intelligent energy, intelligent governance, intelligent security, intelligent healthcare are all central to the idea of smart cities. The emphasis of this essay is on smart transit as a component of smart cities. The movement of people and goods across several geographical boundaries has been significantly aided by the transportation sector. Globally, the majority of smart cities face logistical and transportation issues. Both the fast growing human population and the increase in the number of cars on the road are to blame for this. In order to design and run a sustainable transportation system, technology may be of great assistance. Robotic systems for real-time vehicle data collection, traffic management, and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with traffic congestion. The transportation industry, which faces difficulties including traffic congestion, unanticipated delays, and routing issues that cause businesses to lose money, has successfully used robotic process automation. Robotic process automation provides reliable results and affordable solutions while reducing uncertainty in the decision-making process. It is very helpful in designing and running a successful transit system. Robotic Process Automation (RPA) systems for obtaining real-time data from vehicles, buses, and trucks for traffic management and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with poor management and congestion. By examining different uses of robotic process automation, it is possible to evaluate precise prediction and detection models that are intended to forecast traffic volume, an appropriate route, traffic conditions, accurate information about timing, incidents, and which time and roadway for transport are suitable for running and mobility. The application of RPA in smart cities could be seen in Intelligent Transportation Systems’ Traffic Management, Public Transportation, Safety Management, Manufacturing, and Logistics. The research focuses on areas of concern for smart cities in the sphere of the transportation sector and related difficulties that may be solved via robotic process automation. The article emphasizes the challenges and solutions for making smart transportation more effective by using Intelligent Robotic Transportation Systems.

By using Robotic Process Automation (RPA) companies are looking to improve their performance. In RPA, robots, or ‘bots’, are software agents which carries out activities within software systems in the same way a human would [27], [30]. This positions RPA as a lightweight tool to automate information handling at the user interface layer of existing applications without the specialized technology skills required for automation at the logical and data layers [29]. Therefore, RPA is a potential tool for small and medium sized enterprises (SMEs) who cannot compete with larger firms in resources required for large scale automation. This paper presents a case study of how a small auditing firm use RPA to automate repetitive tasks freeing time that can be used for higher value-added tasks. The results show that RPA can eliminate workload bottlenecks and give access to more high-quality data for auditing at low costs. Interestingly, RPA caused process redesign that constituted 62,5% of the time savings, while the remaining 25% were attributed to RPA alone. The results are valuable for SMEs evaluating RPA as a tool for performance improvements, and for researchers by challenges identified for future research.

Construction is dangerous, making safety management essential. Robotics process automation (RPA) can improve construction project risk management. RPA is hindered by several factors. This study examined the primary technical, economic, legal, privacy, and resource obstacles to RPA adoption for tall building safety management. The pilot survey comprised 161 Malaysian tall building specialists, while the full questionnaire poll included 231 experts. EFA and SEM analyzed the data. Technology, economics, legislation, privacy, and resources prevented RPA from managing tall building safety. Theoretical and empirical breakthroughs in construction safety management and RPA deployment prompted this inquiry. This study illuminates the main obstacles to employing RPA for tall building safety management. The results show where to spend time and money to eliminate the obstacles. The study’s management implications may benefit construction safety managers, project managers, and company owners. The findings may help the building industry plan RPA safety management in tall projects and overcome hurdles. This study contributes to construction safety management and RPA deployment theory by identifying and analyzing the main barriers to using RPA for safety management in high-rise buildings. This research can help solve the problems preventing RPA from being used in construction project safety management.

The technological development of enterprises is one of the key challenges faced by modern entities. Enterprises are looking for more and more easily adoptable low-code technologies, an example of which is RPA. The success of implementations depends to a large extent on the professional competences and knowledge of entities implementing RPA projects. The literature on the subject contains many studies on the RPA technology itself or its applications in enterprises. However, there are few studies on the management of organizations focused on implementing RPA projects. The article fills this gap. The aim of the article is to analyze and evaluate the management of the RPA department on the example of a company providing SAP and RPA services. The article uses literature analysis and a case study of a company providing SAP and RPA services operating on the Polish market as a research method. One of the key conclusions from the conducted research was that there is little complexity in the integration of the use elements of the 7S model in the RPA department,and the implementation of soft elements of the 7S model is important to create market advantage. Surprisingly difficulties were identified in adapting the hard elements of the model to the requirements of the parent company, related to poor understanding of the characteristics of the RPA team’s operation in the post-transactional integration process.

Automation technology is changing and transforming innovation into the industrial landscape and Human Resources (HR) should ensure to adapt and practice its deployment to realise its benefits in time and for cost savings. The implementation of Robotic Process Automation (RPA) in HR can help to offer better service to ensure compliance of the processes with standards and regulations. RPA is a software technology that manages software robots to emulate human actions when interacting with digital platforms. RPA is a solution that could perform repetitions to take over activities carried out by humans. However, a robot is not thought to be able to replace the HR but is, instead, useful to support driven processes. The purpose of the study is to prove the efficiency and effectiveness of RPA in the Human Resource Management System (HRMS) compared to the manual process performed by a human. Different types of components and characteristics were identified to adopt RPA in HRMS based on the data measurement in the implementation process. This study designs and develops an HRMS model using RPA tools to achieve the target process. The model was developed based on a case study of an existing model of RPA in HRMS from an IT consultancy industry. In the HR process, the project uses an application focusing on the parameters of gathering, storing and accessing employees’ information from other modules. Lastly, the gaps in the HRMS to improve productivity are evaluated and explained.

New digital solutions that automatise white-collar work have received considerable attention in contemporary news and caused speculation about the future of various professions. In this chapter, the authors address robotic process automation (RPA) and the revitalised extinction prophecy related to the accounting profession. In the context of the extinction prophecy, they analyse the portfolio of accounting tasks and review the accounting literature, with a focus on RPA as a digital solution. The portfolio of accounting tasks analysis demonstrates that RPA mainly targets administrative tasks, leaving more analytical tasks unaffected. They review the current state of research on RPA in the accounting field but fail to find explicit support for the extinction prophecy. Therefore, the authors suggest a sceptical view of this alongside an acknowledgement of the opportunities provided by RPA.

The integration of Artificial Intelligence (AI) and Robotic Process Automation (RPA) within Pega’s Intelligent Process Automation (IPA) framework is fundamentally transforming enterprise workflow management. Traditional RPA, while effective in automating repetitive, rule-based tasks, lacks the adaptability and cognitive capabilities required for handling dynamic business processes. AI-enhanced RPA, on the other hand, leverages machine learning (ML), natural language processing (NLP), predictive analytics, and decision-making algorithms to enable self-learning automation systems that optimize workflows, reduce errors, and improve operational efficiency. This study conducts a comparative analysis between traditional RPA and AI-powered RPA within the Pega ecosystem, focusing on key performance indicators (KPIs) such as process execution time, accuracy, cost-effectiveness, scalability, and adaptability. By evaluating empirical data from real-world implementations, this research identifies the tangible benefits of AI-enhanced RPA in automating complex business operations across industries such as finance, healthcare, and e-commerce. The comparative assessment is structured around efficiency gains, error reduction, financial viability, and scalability, providing quantifiable insights into the transformative potential of AI-driven process automation. Using real-world case studies and industry benchmarks, this study demonstrates how AI-enabled automation in Pega improves workflow orchestration, predictive decision-making, and end-to-end automation of critical business functions. AI-powered bots can analyze data, predict process bottlenecks, automate exception handling, and enhance customer interactions, thereby surpassing the limitations of traditional RPA. The findings from this research emphasize the strategic advantages of AI-enhanced RPA in digital transformation efforts. Organizations that integrate AI-powered IPA within their automation strategies gain a competitive edge by achieving greater operational efficiency, reducing costs, and enabling scalable, intelligent automation solutions that adapt to changing business needs. This paper provides actionable recommendations for enterprises looking to leverage AI in Pega-driven automation frameworks, ensuring a seamless transition from rule-based automation to intelligent, self-optimizing workflows. Ultimately, the study concludes that AI-driven RPA in Pega is not just an incremental improvement over traditional RPA but represents a paradigm shift toward autonomous and cognitive automation, setting a new standard for enterprise-level process management.

Robotic process automation (RPA) is transforming the healthcare industry through the automation of jobs, optimisation of workflows, and improvement of operational efficiency. This chapter examines the revolutionary capacity of robotic process automation (RPA), emphasising its various uses, advantages, and ethical implications. Although RPA enhances the efficiency of resource allocation and enhances the quality of patient care, it is crucial to tackle concerns such as job displacement and data privacy. Empirical case studies provide concrete evidence of the tangible effects of robotic process automation (RPA) on the delivery of healthcare services. Anticipating and adopting the progress of robotic process automation (RPA) with ethical accountability holds the potential for a more streamlined and patient-focused healthcare system.

Background/Objectives: Robotic Process Automation (RPA) offers a potential solution for reducing the manual burden of clinical data abstraction, yet empirical evidence of its effectiveness in real-world electronic health record (EHR)-integrated cancer registries remains limited. This study aimed to evaluate the post-implementation effectiveness of RPA for cancer registry data abstraction in a tertiary hospital and to explore multidisciplinary stakeholder perceptions regarding its deployment. Methods: We implemented RPA for gastric and breast cancer registries within a production EHR system. Quantitative effectiveness was evaluated by comparing per-patient data extraction time using descriptive statistics. To ensure data integrity, all RPA-extracted outputs were entirely verified manually by researchers against source records. Qualitatively, semi-structured interviews were conducted with 14 participants and analyzed via thematic analysis based on the Promoting Action on Research Implementation in Health Services (PARiHS) framework (Evidence, Context, and Facilitation). Results: RPA was applied to 70 gastric cancer variables and 83 breast cancer variables. For the gastric cancer registry, the mean abstraction time per patient decreased by 74% (19.5 ± 3.0 to 5.1 ± 1.8 min). For the breast cancer registry, time decreased by 30% (25.4 ± 6.9 to 17.8 ± 5.5 min). Based on 2024 surgical volumes, this translates to an estimated saving of over 260 h of manual labor per year. Qualitative findings revealed that while participants recognized RPA as ideal for repetitive tasks, successful implementation was contingent on clinician cooperation and continuous output monitoring. Conclusions: RPA implementation significantly improved data abstraction efficiency in a real-world clinical research workflow. The disparity in time savings highlights that efficiency gains are contingent upon registry complexity. While formal quantitative assessments of data accuracy were not performed, RPA is a readily deployable tool for enhancing clinical data workflows when aligned with organizational readiness and robust monitoring.

Robotic process automation (RPA) is a rapidly emerging field of computer science. It refers to the use of software robots or similar virtual assistants, which are programmed to complete repetitive and labor-intensive tasks. It has been shown that RPA offers technologically advanced solutions to businesses around the world and can cut costs, raise levels of efficiency, and improve quality. In the effort to remain competitive in the market, RPA has become a powerful and competitive tool for companies spanning a range of different industries. In this chapter, the authors’ focus is on the role of RPA in the banking sector. In this chapter author will analyze the existing scientific research in this area, with a focus on the process requirements for implementing RPA in banks, RPA vendors, and the general benefits of robotization in banking. The chapter will provide additional value through a list of suggestions for the practical use of RPA in the banking industry.