## 1 Introduction  
The integration of Artificial Intelligence (AI) and Robotic Process Automation (RPA) has emerged as an increasingly relevant topic in contemporary organizational contexts. As companies strive to enhance operational efficiency and adaptability within a rapidly evolving market, the combination of these technologies presents an innovative and potentially transformative solution. AI, with its capacity to learn and adapt, in conjunction with RPA, which automates repetitive and rule-based tasks, creates an environment where organizations can not only optimize internal processes but also respond more agilely to customer needs and market demands [1].  
The importance of this study lies in the pressing need to understand how the integration of AI and RPA can be achieved to improve operational efficiency without adversely affecting social and environmental factors. Although the literature surrounding these technologies has expanded considerably in recent years, a significant gap remains in analyzing the social and environmental impacts of their implementation. Issues related to data privacy, cybersecurity, and potential job displacement warrant further investigation [2]. This article seeks to address this gap by presenting a systematic review of existing literature and proposing a model that takes these critical factors into account [3].  
To effectively discuss the integration of AI and RPA, it is essential to clearly define several key concepts. Strategic integration refers to aligning these technologies with an organization's long-term objectives, ensuring that the adoption of AI and RPA maximizes benefits while minimizing risks [4]. Operational efficiency, in this context, can be assessed through metrics such as cost reduction, service quality improvement, and decreased processing times. Sustainability encompasses environmental, social, and economic dimensions, acknowledging that organizational effectiveness should not be achieved at the expense of societal well-being or environmental preservation [5].  
The objectives of this study are multifaceted. Firstly, it seeks to analyze the existing literature on the integration of AI and RPA, identifying gaps and areas requiring further research. Secondly, it aims to develop a model that optimizes operational efficiency while balancing the social and environmental implications arising from the implementation of these technologies [6]. Finally, the study intends to offer practical recommendations for organizations aiming to adopt these innovations responsibly and sustainably [7].  
This article is structured into several sections. Section 2 presents a detailed literature review, examining the evolution of AI and RPA technologies, as well as the challenges and opportunities their integration poses. Section 3 outlines the methodology applied in the systematic literature review, justifying the selection of the PICO approach and explaining the hypothesis formulation process. Section 4 introduces the proposed model, highlighting its key features and the advantages it offers over existing models. In Section 5, the research findings are analyzed, discussing the implications of AI and RPA integration with respect to operational efficiency and social and environmental sustainability. Finally, Section 6 concludes the article, summarizing the key findings and suggesting directions for future research.  
In summary, this article seeks to contribute to the understanding of the intersection between Artificial Intelligence and Robotic Process Automation, proposing a model that not only promotes operational efficiency but also incorporates social and environmental responsibility, aligning with the demands of an increasingly digital and interconnected world.