Governing Non-Human Identities in the Age of AI

Governing Non-Human Identities in the Age of AI

The Identity Governance and Administration (IGA) world is observing a major change from a manual, rule-based approach to an intelligent, adaptive, and predictive approach. The reason behind this evolution is mainly brought about by artificial intelligence (AI), from reactive to proactive security.

To understand this evolution better, it is important to know the difference between IGA with and without AI.

IGA without AI

Traditionally, IGA relied on predefined rules and human intelligence. These are the things that were handled manually:

• Automation based on predefined rules: A Predefined set of logics was used for automating processes like user provisioning and password resets. This was a very simple, straightforward, and predictable process, but it came along with complexity and exceptions.

  
  

• Manual Reviews: This process consumes a lot more time in issuing and reviewing accesses, which often leads to major administrative overhead and related errors or lapses.

• Static Access Control: Access is typically granted based on a user's role (Role-Based Access Control, or RBAC), utilizing a "authenticate once and trust" model. This can result in users having excessive or unused access rights for long periods.

  
  

• Reactive Security: Security teams typically react to known threats or policy violations after they have occurred. The system also lacks the ability to predict future risks.

  
  

• Data Limitations: Traditional methods struggle to process vast amounts of data and identify complex relationships, leading to blind spots and inconsistent entitlement models.

IGA with AI (Modern Approach)

The AI-driven modern IGA approach uses machine learning and analytics to analyze patterns, recognize causalities, and make contextual decisions.

• Contextual & Dynamic Access: Access-related decisions are made dynamically rather than governed by static rules, proving efficient when it comes to adapting to changing risk levels. This is enabled by AI, making authentication more adaptive and continuous by evaluating multiple risk factors in real-time (user behavior, location, device, time, resource sensitivity)

  
  

• Predictive Risk Analysis: AI analyzes historical data to establish baseline behaviors and identifies potential security risks before they materialize, allowing security teams to act proactively.

  
  

• Enhanced Governance and Compliance: AI's analytics can easily smell excessive access rights, detect disruptions happening in policy, and accordingly recommend role adjustments. This helps in improving compliance and reducing efforts by 60%.

  
  

• Behavioral Analytics: Regular monitoring of user behavior (e.g., typing patterns, mouse movements) with AI has the ability to detect activities that can compromise accounts in real-time without interfering with the user experience.

  
  

• Managing AI Identities: As AI agents and machine identities become prevalent, manual governance is unfeasible. AI in IGA provides automated, dynamic, and granular management for these non-human identities, which operate at machine speed. 

In the end, we can sum up by analyzing that AI in IGA is here to provide us with a more secure, adaptive, and efficient approach. The shift from static rules and human processes to an intelligent one that is continuous and intelligent is, anyway, far more efficient and useful.

Though AI has reformed the IGA world, human efforts and intelligence remain unmatched.

While organizations concentrate on their growth, we at IDMEXPRESS are focused on cyberproofing them by providing IAM and PAM implementation and 24/7/365 managed services. If you are looking for an implementation and managed service partner, contact us today to secure your tomorrow.\

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