Robotic Process Automation (RPA), which automates repetitive, rule-based operations, is becoming a crucial component of today’s enterprises as they compete in more dynamic business contexts. This study intends to provide implications on the Benefits Realization Key Success Factors (BRKSFs) appropriate for RPA projects, given that between 30% and 50% of RPA initiatives fail. The methodology of this study comprises three stages: identify the main contributing BRKSFs, develop a hierarchical relationship model for BRKSFs, and provide real-world examples to show the usability of BRKSFs using two case studies. The results show that having a clear, well-defined, and unchanging process is the most important BRKSF because of its strong influence over other factors. Three factors, namely, aligning the objective of the RPA initiative with the organization’s strategic objectives, choosing the right process for automation, and change management, have lower driving powers but high dependence powers than other factors. The five factors that have both high driving and high dependence powers are: prioritizing the benefits that can be obtained through the RPA initiative, performing a feasibility study, assembling a cross-functional team, having a team leader and receiving support from top management. This study sheds light on the interdependencies between BRKSFs for academics and business professionals, enabling them to determine which variables need to be considered most for RPA initiatives.

Intelligent Robotic Process Automation (IRPA) combines Artificial Intelligence (AI) and Robotic Process Automation (RPA) to automate complex unstructured tasks, improve decision-making, and cope with changing scenarios. A process analysis framework for IRPA adoption was developed by identifying key factors through a literature review and semi-structured expert opinion survey. The employed experts in the survey comprised RPA/IRPA consultants, RPA/IRPA initiative team leaders, and RPA/IRPA developers with three years or more experience. For the initial factor collection phase, there were a total of eighteen (18) responses, and for the factor evaluation phase, a total of twenty-six (26) experts were used to collect responses. Identified factors were shortlisted and evaluated using a Relative Importance Index (RII) analysis. The study’s findings are presented through a Causal-Loop Diagram (CLD) to illustrate the relationships between factors. The framework provides practical guidance for organizations planning to adopt IRPA, informing decision-making, resource allocation, and strategy development. The final process analysis framework highlights the importance of accuracy, level of human involvement in a task, and standardization as the main three primary factors for successful IRPA adoption. Three major secondary factors were identified: digital data input, integration with existing systems, and the cost of adopting new technologies. This research contributes to the added value to existing knowledge and serves as a foundation for future research in IRPA adoption.