Enhancing Budgeting Process Through Robotic Process Automation

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.

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.

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.

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.

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.

Robotic Process Automation (RPA) has emerged as a transformative technology in various industries, including healthcare, where it can significantly improve efficiency and accuracy in inventory management. This research paper examines the applications of RPA in healthcare inventory management, highlighting the potential benefits, challenges, and a framework for evaluating its viability. The healthcare industry has long grappled with the complexities of inventory management, from maintaining adequate supplies of essential medical equipment and pharmaceuticals to ensuring timely replenishment and distribution. RPA offers a promising solution by automating repetitive, high - volume tasks such as data extraction, order processing, and inventory tracking. By reviewing the existing literature and case studies, this paper presents a comprehensive analysis of the current state of RPA in healthcare inventory management. The findings suggest that RPA can lead to improved inventory visibility, reduced errors, and streamlined workflows, ultimately enhancing patient care and reducing operational costs. However, the successful implementation of RPA in this domain also requires addressing key challenges, such as integration with legacy systems, data security and compliance, and the need for effective change management. To guide organizations in their RPA adoption journey, this paper proposes a framework to evaluate the viability of RPA for specific inventory management activities, considering factors such as task complexity, process maturity, and the potential for cost savings. The insights drawn from this research can inform healthcare leaders and practitioners on the strategic deployment of RPA to optimize inventory management, ultimately contributing to the overall efficiency and quality of healthcare delivery.

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.

SYNOPSIS This study investigates the risk mitigation and internal control processes organizations implement in their robotic process automation (RPA) deployments in accounting. The roles of internal controls and risk mitigation are examined by exploring how RPA Program Managers have adopted internal controls and risk mitigation regarding RPA in accounting. Employing interviews with 20 RPA Program Managers, this study provides rich insights into RPA Governance for accounting processes. The interviews revealed that organizations adopt various governance models to ensure proper oversight over RPA in accounting. RPA Governance models range from being fully centralized to being entirely decentralized. RPA risk and control oversight includes unique risk assessments for the RPA accounting environment and specialized monitoring to ensure that RPA in accounting performs as expected. JEL Classifications: M41; M42.

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.

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.

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.

Automation of administrative work, using Robotic Process Automation (RPA), has been highlighted as something that can help Swedish municipalities to reduce costs and improve efficiency. The use of RPA in Swedish municipalities is still in its infancy, and much can be learned from the experiences made so far. In this paper, we present an overview of the findings from a four-year case study investigating RPA development, implementation, and use in Swedish municipalities. The aim of the paper is to describe the general drive to implement RPA in Swedish municipalities, the intended uses of RPA in this context, and challenges experienced as part of RPA implementation. Based on this description, we outline a set of organizational conditions required to work with RPA in local government. Our findings illustrate that process automation is only partly about technology. The main focus in process automation must be on mapping and developing processes and routines. RPA-technology is best seen as a tool and not as an end in itself. It is therefore important to develop the employees' abilities and knowledge regarding both processes and automation, so that the employees can drive the development forward based on the challenges and opportunities that arise in their practical work.

Today successful business success relies on efficient supply chain management (SCM) in the ever-changing global marketplace. Traditional SCM processes are subject to inefficiency, manual intervention, destruction, etc. This paper evaluates the contribution of Pega’s Robotic Process Automation (RPA) in effecting transformation in SCM efficiency. Powered by AI and Machine Learning, Pega’s RPA streamlines processes like order management, inventory tracking, demand forecasting and so much more, moving supply chains from reactive to predictive. This was a mixed methods approach combining case studies, surveys, and interviews with industry professionals. Results indicate significant operational improvements: This resulted in a 40 percent reduction in processing times, an 85 percent decrease in manual errors, and a 30 percent reduction in operational costs. Another case example illustrates how Pega’s RPA improves scalability, decreases errors and is cost-efficient. While the technology is beneficial, the initial costs are high, there is workforce adaptation, and enough makes the integration challenging. The findings underscore the need for strategic planning and workforce readiness for implementation success. Finally, the study concludes that Pega’s RPA is not just another tool for automation, but an investment in supply chain modernization that provides actionable insights to organizations and serves as a foundation for future RPA research on scalability and integration with new technology. Keywords: Supply Chain Management (SCM), Robotic Process Automation (RPA), Pega, Operational Efficiency, AI and Machine Learning, Cost Reduction, Scalability

The adoption of Robotic Process Automation (RPA) in auditing has emerged as a transformative trend, offering significant potential to enhance efficiency, accuracy, and overall audit effectiveness. This study explores the integration of RPA in auditing processes, identifying key areas where automation can streamline workflows and reduce human errors. Drawing from a qualitative research approach, semi-structured interviews were conducted with 15 professionals across diverse audit sectors, uncovering insights into the benefits, challenges, and strategic implications of RPA adoption. The findings reveal that RPA reduces routine task completion times by up to 50%, improves data accuracy by 40%, and delivers a 120% return on investment within two years. However, challenges such as resistance to change, skill gaps, and compatibility with legacy systems persist. This research highlights the necessity of effective change management, continuous skill development, and ethical governance to maximize RPA's potential. By addressing these challenges, this study provides actionable recommendations for leveraging RPA to revolutionize audit practices, enabling organizations to adapt to an evolving technological landscape.

This case examines a large technology firm, anonymized as TECHSERV, as they plan, manage, and implement robotics process automation. The organization was seeking ways in which to improve efficiency, effectiveness, and productivity through technology management. Robotics process automation was strategically deployed to automate their business processes. Even though many benefits are associated with robotics process automation, the details of how robotics process automation can be implemented successfully into existing infrastructure are not well known. This teaching case focuses on problems with how to automate processes in two locations, and deals also with the resources and tools and techniques related to project execution. In addition, the case also points to future issues and challenges related to robotics process automation, cognitive tools, and blockchain integration. Students, researchers, and practitioners will obtain an understanding of the benefits and project activities required for robotics process automation and learn how to anticipate future issues and challenges including how to leverage the current implementation into future intelligent automation initiatives.