
2024 saw cybersecurity threats evolving at a pace never seen before. Recent statistics state that data breaches doubled in 2024 from the previous year with compromised credentials and privilege abuse as the leading cause.
Even with IAM solutions in place, organizations are under the radar of continuous cybersecurity attacks and threats. We can clearly see that traditional IAM solutions are dealing with issues they were not designed to handle.
To keep up with the cyber attacks IAM solutions are advancing by integrating Artificial Intelligence AI and Machine Learning ML. This integration helps IAM solutions to continuously learn through the environment and be prepared for upcoming attacks.Â
This article explains how AI/ML is going to change the IAM solutions.
Challenges Faced by Traditional IAM solutions:
Traditional IAM solutions involve a centralized identity management system, access control, password or hardware tokens-based authentication, and more. These days they struggle to handle hybrid or cloud-based environments, limited integration, static access control, and complex maintenance structures. Not just this, here is an extended list of challenges:
Predefined rules and policies are a major component of legacy IAM systems, and often lead to restrictive access controls.
Manual Identity Lifecycle management ILM increases the risk of errors and delays in granting and revoking access.
Being unable to react quickly enough to complex attacks including account takeovers, insider threats, and credential stuffing, often prone to Zero-day attacks.
The dynamic nature of businesses along with evolving technology, devices, and apps leads to difficulty in adjustments.
The massive volume of data produced each day makes it difficult to process, analyze, and prepare for an uninvited attack.
IAM Transformation through AI/ML Integration
The above challenges have forced the AI/ML integration with IAM. This improvement has advanced the capabilities along with better user experience, increased efficiency, and security. But how? Let us learn how this adaptation has improved traditional IAM solutions:
1. Identity Lifecycle Management ILMÂ Automation-Â
AI integration with Identity Governance and Administration IGA systems has automated the whole ILM. It helps identify and classify user roles, permissions, and entitlements more accurately hence automating the processes like provisioning, deprovisioning, and access reviews. In the end, the administrative burden is minimized and user identities are managed with accuracy.Â
2. Risk-Based Access Control-Â
AI integration has changed the way how access is granted. The AI-integrated systems evaluate real-time data that includes user behavior, device kind, location, and access time only then allowing the access. This is known as adaptive authentication. Thus the access is granted on risk bases in place of rigid standards used traditionally.Â
3. Analyzing Behavior to Identify Anomalies -Â
User behavioral analysis is made possible through AI and ML integration. AI solutions study user activities and analyze their behavior. While ML algorithms analyze usage trends, access requests, and login behaviors. AI-ML integration added an extra layer of security.Â
For example, in a recent incident in the healthcare sector, AI spotted an unusual admin access trying to get patient records outside the usual workflow. AI triggered an additional verification step to stop the data theft.Â
4. Enhanced Privileged Access Management
The safety of organizations has been improved by integrating AI and ML through uncovering and stopping suspicious access. This comprises analyzing privileged user access patterns, recording the sessions, and reviewing the system logs.
This helps in thwarting attempts of unauthorized access or credentialed privilege abuse.
Once unidentified access happens, a system can automatically eliminate these suspicious sessions, cut back on excessive privileges, and inform the security teams for deeper investigations.
5. Passwordless Authentication
Password-less methods are majorly powered by biometrics and AI and ML devices-based credentials. Passwords are expected to be completely discarded by big businesses and organizations by 2025 according to Gartner, increasing security while offering a smoother user experience.
Potential OutcomesÂ
Yes, we know AI/ML together with IAM are moving ahead to be at the front door of cybersecurity threats and breaches. There are a lot of potential outcomes such as Â
Reducing Cost: The Significance of AI in IAM for Cost Savings Automated procedures increase productivity while reducing operating expenses.
Faster Threat Detection: AI cuts the time it takes to find breaches from months to hours (from 280 days to hours, as per IBM data).
Better Compliance:Â AI-driven analytics provide thorough audit trails, which facilitate compliance with laws like GDPR and HIPAA.
Limitations of AI in IAM:
The potential outcomes do seem fascinating and exciting but there are some concerns associated with these advanced tech stacks like
 Data privacy: How are AI models trained with sensitive data?
 Algorithms without bias: AI judgments need to be impartial and equitable.
 Scalability: The solutions must be able to expand with the company.
Conclusion
Over the years, IAM has been saving organizations from cybersecurity threats and attacks. However, technological advancement has proved that they are not enough.
The alarming need for AI / ML integration with IAM solutions is highly needed to overcome significant challenges. These technologies will help IAM to become a proactive intelligent system. From better threat detection and real-time decision-making to greater user experience and operational efficiency.Â
With these advanced solutions centralized identity governance is made possible by AI-driven IAM solutions, which offer smooth integration with a variety of platforms. Additionally, AI can control machine identities, guaranteeing safe device-to-application connection, which leads to drastically improved security posture, reduced expenses, and increased productivity.
As artificial intelligence learns from the evolving environment similarly these attacks and breaches are also evolving at a pace never seen before. Thus organizations must adopt these technological updates to keep their digital ecosystem safe, sound, and secure from the ever-evolving future landscape.
To keep your organization safe, and secure from the present and upcoming cybersecurity threats, attacks, and breaches book a FREE CONSULTATION session with us at IDMEXPRESS

Sources:
IBM Cost of Data Breach Report 2024
Verizon Data Breach Investigations Report 2024
Gartner Research on Passwordless Authentication Trends 2023
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