## 5 Discussion  
The proposed model (SIRAI) for the integration of Artificial Intelligence (AI) and Robotic Process Automation (RPA) within organizations is founded on a comprehensive approach that seeks not only to enhance operational efficiency but also to promote social and environmental responsibility. The results derived from analyzing the various stages of the model demonstrate that a careful implementation of these technologies can optimize resource utilization while achieving a balance between efficiency and sustainability. The theoretical findings indicate that the strategic integration of AI and RPA can lead to a substantial improvement in the efficiency of organizational processes. However, such enhancements should not come at the expense of social and environmental responsibility. Assessing technological requirements and organizational readiness highlights the importance of preparing teams for change, while minimizing both cultural and technical resistance. The recommendations provided to address limitations, such as inadequate \begin{table}
\begin{tabular}{c c c} \hline \hline
**Benefit** & **Articles** &
\begin{tabular}{c} **Proposed** \\ **Model** \\ \end{tabular} \\ \hline Process Selection for Automation & [24; 34; 40; 43; 48; 60] & X \\ Development of Governance Models for RPA & [29; 42; 51; 55; 63] & X \\ Financing Models & [28; 41; 53] & \\ ROI and Impact Assessment & [46; 57; 58; 64; 65] & \\ Identification and Classification of Impacts & & X \\ Ethical Considerations & & X \\ \hline \hline \end{tabular}
\end{table} 
Table 11: _Cont._infrastructure and resistance to change, are crucial to ensuring that the adoption of these technologies is both responsible and sustainable. The analysis of the impacts associated with the adoption of AI and RPA reveals a significant duality. On one hand, the integration of these technologies can yield considerable gains, such as:  
* Improved Operational Efficiency: The automation of repetitive processes frees up time and human resources, allowing teams to focus on more strategic and creative activities. * Increased Customer Satisfaction: With more agile and accurate processes, companies can provide higher-quality services, leading to a positive customer experience. * Cost Reduction: The efficiency brought about by automation can lead to a substantial decrease in operational expenses. On the other hand, there are also negative impacts that need to be carefully considered:
* Fear of Job Displacement: The implementation of AI and RPA may generate uncertainty among employees, who may be concerned about the possibility of being replaced by machines. This concern can affect team morale and organizational culture. While implementing AI and RPA can result in significant efficiency and productivity gains, one of the main concerns is the fear of job displacement. This is because automation technologies are seen as a threat to jobs, especially in areas where tasks are repetitive and rules-based. This apprehension is amplified by the lack of clear communication between business leaders and employees, often generating resistance to change and even organizational dissatisfaction. Furthermore, the absence of effective transition and reskilling policies can increase uncertainty among employees, fueling fears that their jobs are at risk. It is crucial that organizations not only implement technologies efficiently, but also develop strategies to minimize negative social impact. Investing in training and requalification, in addition to involving employees in the adaptation process, can help reduce the fear of job displacement and promote an organizational culture that is more open to change. * Data Privacy and Security Issues: With the digitalization of processes, organizations face challenges related to data protection and compliance with regulations such as GDPR. Another important aspect that must be considered during the adoption of AI and RPA is data privacy.