A Comprehensive Study on the Business Application of Robotic Process Automation: Exploring Scalability, Integration, Cognitive Capabilities, and Governance

Abstract

This qualitative study investigates the key challenges, opportunities, and best practices in implementing Robotic Process Automation (RPA) systems for scalability, integration, cognitive capabilities, and governance in business applications. Through in-depth interviews with 118 respondents, the research aims to address seven research questions that encompass aspects such as RPA design optimization, seamless integration with legacy systems, incorporation of cognitive capabilities, RPA governance, human-robot collaboration, ethical implications, and performance measurement.
The findings reveal that addressing the challenges and opportunities in RPA implementation requires a multifaceted approach that includes robust architecture, platform selection, collaboration between IT and business teams, leveraging APIs and custom integrations, continuous monitoring, and employee training. Enhancing the cognitive capabilities of RPA systems necessitates the integration of AI and ML technologies, continuous learning and adaptation, incorporation of NLP and computer vision, collaborative development, and investment in R&D. Ensuring seamless RPA integration with legacy systems involves comprehensive change management strategies, employee involvement, training and upskilling programs, leadership support, and monitoring and evaluation of change management initiatives.
The study also highlights the importance of RPA governance, management, and human-robot collaboration in aligning RPA systems with business objectives and optimizing their performance. Ethical, social, and industry-specific implications of RPA adoption are discussed, along with strategies to mitigate potential negative impacts. Finally, the research emphasizes the development of performance measurement and bench-marking criteria for effectively evaluating the success and effectiveness of RPA implementations.
This study contributes to the existing body of knowledge on RPA by providing valuable insights into the challenges and opportunities associated with RPA implementation and adoption. The findings can serve as a guide for organizations looking to optimize their RPA systems and ensure their ongoing success in a dynamic business landscape.