## 2 Background
Organizations aiming to automate operational processes must consider not only tangible benefits such as cost reduction and efficiency gains but also intangible factors such as usability, integration with legacy systems, and employee acceptance. Critical engagement involves recognizing that not all cutting-edge solutions are suitable for every business context. RPA implementation should be preceded by an in-depth analysis of existing processes, identifying bottlenecks and opportunities for optimization. Furthermore, strategic alignment between technology and organizational objectives is imperative to ensure that automation delivers tangible value. Another key consideration is the human impact of automation. Resistance to RPA adoption may emerge due to concerns over job displacement, necessitating proactive change management strategies. Investment in training and the redefinition of organizational roles are essential to facilitate a smooth transition. Consequently, implementing RPA not only enhances operational efficiency but also strengthens employees' roles, allowing them to focus on higher-value tasks. Integrating Requirements Engineering, DevOps, and RPA presents multiple challenges that must be addressed to ensure successful automation projects [23]. To guarantee the efficacy of RPA-driven process automation, a structured technical approach focused on process readability must be adopted. From a technical perspective, requirements analysis should be conducted with utmost precision, ensuring that business rules are well-defined and comprehended before implementation. This approach mitigates risks associated with erroneous or inconsistent process automation, ensuring that bots function efficiently. Integrating RPA with existing systems presents a technical challenge, requiring compatibility with APIs, databases, and communication protocols. Selecting RPA platforms that support native integration with enterprise systems such as ERPs and CRMs simplifies deployment and reduces development time. Additionally, information security must be prioritized to ensure compliance with regulatory guidelines and safeguard sensitive data. The readability of automated processes is another critical factor. Comprehensive documentation, including flow diagrams and detailed process descriptions, facilitates the comprehension and maintenance of bots. Practices such as script versioning and the implementation of logs to monitor execution are indispensable for ensuring the transparency and auditability of automated operations. Lastly, the continuous monitoring of bots is essential to detect potential failures and implement necessary adjustments promptly. The integration of techniques with rigorous requirements, secure system integration, and meticulous documentation practices ensures that RPA is deployed in a robust, comprehensible, and efficient manner, thereby maximizing its positive impact on organizations. * Challenges in Requirements Engineering: The complexity of defining requirements for RPA processes can be a significant impediment, particularly as these requirements may evolve throughout the project's lifecycle. Ambiguities or a lack of detail in requirement specifications can adversely affect RPA implementation. Additionally, the dynamic nature of requirements necessitates a flexible and adaptive approach to Requirements Engineering [23]. * Challenges of DevOps in RPA Projects: Adapting traditional software development methodologies to accommodate the specific demands of RPA presents further challenges. The automation of testing and monitoring, as well as the continuous deployment of RPA bots, necessitates specialized tools and methodologies, as well as the capability to manage and oversee bot updates in real time. Continuous collaboration between development and operations teams is essential in order to address the complexity and frequency of updates [23].