###### Abstract  
The integration of artificial intelligence(AI) technologies into identity and access management (IAM) systems has greatly improved access control and management, offering more robust, adaptive, and intelligent solutions than traditional methods. AI-driven IAM systems enhance security, operational efficiency, and introduce new capabilities in industrial environments. In this narrative review, we present the state-of-the-art AI technologies in industrial IAM, focusing on methods such as biometric, comprising facial and voice recognition, and multifactor authentication for robust security. It addresses the challenges and solutions in implementing AI-based IAM systems in industrial settings, including security, privacy, evaluation, and continuous improvement. We present also the emerging trends and future directions, highlighting AI's potential to transform industrial security measures. This review aims to guide researchers and practitioners in developing and implementing next-generation access control systems, proposing future research directions to address challenges and optimize AI applications in this domain. identity and access management; artificial intelligence; industrial environments +
Footnote †: journal:  
0000-0001-6691-2000/0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-000000-000  
IAM systems are essential for ensuring the security and integrity of industrial facilities, protecting critical assets, and preventing unauthorized access [2]. AI is understood as a collection of technologies, including machine learning (ML), deep learning (DL), and data analytics, which are designed to improve decision-making, enhance security, and automate processes within IAM systems. Integrating AI technologies into IAM enhances security measures, improves operational efficiency, and enables new capabilities [8]. AI-based IAM systems are becoming essential for ensuring robust data security and governance across organizations, with market forecasts indicating a rising demand for these technologies. According to the report [9], the global identity and access management market size was valued at USD 15.93 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 12.6% from 2023 to 2030. As such, AI-based IAM systems are expected to grow in importance and adoption in the coming years. A systematic review of the literature conducted by [PERSON] et al. [10] from 2016 to 2021 highlights the growing focus on AI's role in IAM, with a significant body of work exploring its potential. This review lays a foundation for further research into AI's integration with IAM and its future developments. This paper reviews the current state-of-the-art AI technologies and their applications in industrial IAM. From an initial review of the differences between IAM systems in industrial environments and general ones, we delve into the technologies and algorithms that are driving the advancements in this field. Although several research initiatives have driven the deployment of AI solutions in the context of IAM systems, there are difficulties in assessing the real impact of this research, as companies often do not publish the outcome of such application. Due to the lack of sufficient evidence of successful industrial applications of AI in IAM systems, industrial adoption of the technology may be being mitigated. Furthermore, based on this assessment, the objective of our research is to propose a strategic road map to guide both researchers and manufacturers in the transition towards the integration of AI in industrial IAM systems, so the following research questions were formulated:  
RQ1: What are the main contributions of AI in identification and authentication with application in industrial IAM systems? RQ2: What are the advanced capabilities that AI can bring to IAM systems? RQ3: What are the main challenges and future lines of research?