AI-Driven Identity and Access Management in Enterprise Systems

Identity and Access Management (IAM) is essential for cybersecurity architecture because of the increasing complexity of the digital enterprise. The research investigates how Artificial Intelligence (AI) transforms Identity and Access Management (IAM) by establishing context-aware systems that function adaptively through automated identity governance capabilities. Concepts from traditional IAM infrastructure face challenges when implementing dynamic access models because they base their function on manual processes and static policies in their design. Machine learning combined with behavioral analytics and orchestration capabilities installed across the entire IAM lifecycle by AI can solve these issues, from authentication procedures to authorization functions and continuing through entitlement governance until policy execution. AI integration establishes continuous authentication with behavioral biometrics and conducts real-time anomaly detection through unsupervised learning models to enable proactive threat mitigation through risk-adaptive access controls. Through AI, the discovery and automation of access rights become possible because systems use actual user activities and organizational settings to refine and certify proper access definitions. The automation systems help organizations comply with GDPR and HIPAA by delivering immediate policy changes while providing auditable access decision logs. The research document evaluates how AI contributes to creating IAM infrastructure that can adapt because it uses predictive load-balancing techniques, self-healing orchestration mechanisms, and autonomous incident response capabilities. The document shows how IAM unites with Security Operations Centers (SOCs) by correlating identity signals with wider security monitoring data to enhance security detection visibility and coordinated response. This report reveals through technical precision and industry examples that AI-driven IAM functions as a security defense system and a business-enabling power for operational speed, compliance adherence, and digital safety in organizational networks. The research highlights AI's critical position in creating security for contemporary identity perimeters.

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Institutions

Publication Details

Journal
International journal of IoT
Published
2025-05-10
DOI
https://doi.org/10.55640/ijiot-05-01-05
Citations
2
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
4.57
Controls
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article

AI-Driven Identity and Access Management in Enterprise Systems

R Hariharan
2 citations
International journal of IoT
Business Process Modeling and Analysis
4.57
article

AI-Driven Identity and Access Management in Enterprise Systems

R Hariharan
article en
2 citations

Abstract

Identity and Access Management (IAM) is essential for cybersecurity architecture because of the increasing complexity of the digital enterprise. The research investigates how Artificial Intelligence (AI) transforms Identity and Access Management (IAM) by establishing context-aware systems that function adaptively through automated identity governance capabilities. Concepts from traditional IAM infrastructure face challenges when implementing dynamic access models because they base their function on manual processes and static policies in their design. Machine learning combined with behavioral analytics and orchestration capabilities installed across the entire IAM lifecycle by AI can solve these issues, from authentication procedures to authorization functions and continuing through entitlement governance until policy execution. AI integration establishes continuous authentication with behavioral biometrics and conducts real-time anomaly detection through unsupervised learning models to enable proactive threat mitigation through risk-adaptive access controls. Through AI, the discovery and automation of access rights become possible because systems use actual user activities and organizational settings to refine and certify proper access definitions. The automation systems help organizations comply with GDPR and HIPAA by delivering immediate policy changes while providing auditable access decision logs. The research document evaluates how AI contributes to creating IAM infrastructure that can adapt because it uses predictive load-balancing techniques, self-healing orchestration mechanisms, and autonomous incident response capabilities. The document shows how IAM unites with Security Operations Centers (SOCs) by correlating identity signals with wider security monitoring data to enhance security detection visibility and coordinated response. This report reveals through technical precision and industry examples that AI-driven IAM functions as a security defense system and a business-enabling power for operational speed, compliance adherence, and digital safety in organizational networks. The research highlights AI's critical position in creating security for contemporary identity perimeters.

International journal of IoTVol. 05(01)
Microsoft (United States) (US)
Openalex Percentile: Top 6%
Business Process Modeling and Analysis
4.57
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AI-Driven Identity and Access Management in Enterprise Systems — R Hariharan · International journal of IoT (2025) | TGRS Research Map | TGRS