## 2 Background
Together, these models create a layered security approach for managing diverse access needs in industrial systems. * Enhanced Security: IAM systems in industrial contexts enhance security by enforcing unified policies across various platforms, addressing both access control and data protection through multiple layers of security measures. By centralizing authentication, authorization, and role management, IAM reduces the risk of unauthorized access by maintaining consistent security protocols that prevent data breaches, especially in cloud or multi-platform environments [18]. Furthermore, IAM frameworks, when optimized, can detect and minimize unnecessary permissions that could be exploited, thereby reducing the risk of insider threats and external attacks [19]. These systems also ensure that security policies dynamically adapt to changing network conditions, protecting industrial systems from unauthorized data flow across diverse trust domains [20]. Ultimately, IAM enforces security policies with both efficiency and adaptability, strengthening the industrial environment's resilience to cyber threats. At the same time, industrial IAM systems play a vital role in ensuring regulatory compliance by providing detailed access logs and audit trails, which are essential for meeting industry standards and legal requirements [21]. In addition to compliance, these systems help reduce operational costs by automating access control processes, minimizing manual interventions, and lowering help desk demands [22; 23; 24]. They also offer self-service functionalities, enabling users to manage their own access rights, which lightens the load on IT staff [22]. To keep pace with the expanding complexity and scale of industrial environments, IAM systems must provide scalability and performance, supporting a growing number of users, devices, and applications with high reliability [18; 24]. Finally, effective IAM solutions ensure integration with other systems, harmonizing data and improving security by analyzing identity and access information across platforms, which enhances both operational efficiency and overall security [2; 25]. IAM plays a pivotal role in industrial environments by centralizing user management, enhancing security, improving efficiency, and ensuring compliance. The integration of IAMwith other systems and the use of RBAC further strengthen its effectiveness. As industrial environments continue to evolve, the importance of robust and scalable IAM systems will increase, making them indispensable for maintaining security and operational efficiency. All this has been represented in the schematic of Figure 1, which comprised the main components of an IAM system. It shows how the identity manager subsystem (Figure 1b) deals with the identities associated through the identification and authentication mechanisms (Figure 1a) distributed throughout the industrial environment. The access manager subsystem (Figure 1d) grants or denies a user access to a specific component of the industrial environment (Figure 1e), be it production, management, or business, based on the information stored in the IAM system. The system database (Figure 1c) centrally maintains model, policy, audit, and log data through an appropriate front-end and back-end platform. The integration of artificial intelligence (AI) into IAM systems has transformed how access is controlled and managed, offering more robust, adaptive, and intelligent solutions compared to traditional methods. This state-of-the-art review explores current advancements in AI applications for IAM in industrial settings, highlighting key technologies, methodologies, and their impacts on industrial security. The focus is on integrating AI technologies such as machine learning, computer vision, and biometric recognition into IAM systems, as well as the advanced capabilities that AI brings, including real-time monitoring, anomaly detection, and predictive analytics.