AI in Identity and Access Management

Identity and Access Management (IAM) plays the critical role of controlling and managing how users access technology-based resources such as data, apps, and other business systems within the organization. Despite this valuable role that IAM plays, many companies still find it challenging to ensure that IAM is always performing optimally. Luckily, the advent of Artificial Intelligence is proving to be the ultimate answer to the various IAM challenges that companies have been facing.

As a leading IT company that has worked with many organizations to drive their digital transformation journeys through cutting-edge innovative solutions, we are glad to walk you through this exciting landscape of bringing AI into Identity and Access Management.

It’s not just about the convenience that comes with applying artificial intelligence in IAM. It’s also about the super-efficient features that Artificial Intelligence offers.

So, why is this the right time to incorporate AI into your Identity and User Management procedures? Let’s explore.

Also Read: AI for Knowledge Management

Importance of AI in Identity and Access Management

The integration of AI into Identity and Access Management boosts IAM in many ways, and delivers these core benefits:

1. Workflow automation

Artificial Intelligence can be used to automate access requests and repetitive manual tasks in IAM. Some of the examples of IAM tasks that can be easily automated with AI include:

• Password management including resets
• Automated role assignments
• Provisioning of user accounts
• De-provisioning of user accounts

AI is capable of automating these tasks and more through technologies such as Natural Language Processing and Machine Learning. It can, for example, understand access requests and confirm user identities before allowing them to access systems.

For example, an AI-driven IAM system can use programmed policies to revoke access privileges should it detect an anomaly.

2. Identity Governance and Administration (IGA)

As the name suggests, this involves the use of AI to govern the procedures around access and identities.

With AI, you will simplify the governance of all the access rights related to different users, making it easy to have greater control which is critical for enhanced governance.

3. Mitigation of entitlement sprawl

Entitlement sprawl refers to the unchecked accumulation of excessive permissions and access rights given to users over a period of time. If left unchecked, users will easily accumulate unnecessary access privileges that could lead to potential security risks.

Besides the risks, entitlement sprawl can lead to inefficiencies as users may get overloaded with so many privileges that they get confused about which ones to use for specific tasks. This can waste time as some may end up using the wrong access privileges for some tasks, which can lead to repetition of overwriting tasks that may have already been performed by other users.

AI can be instrumental in mitigating this phenomenon by simply analyzing user behavior and automatically adjusting access permissions to align with actual needs.

4. Compliance

We all are aware that failure to comply with laws around privacy and security will have your company slapped with hefty penalties.

For IAM, some of the key compliance regulations demand that organizations limit user access only to those who need certain information for specific work. Those who do not need some information must not be allowed to access it because this can increase the risk of sensitive customer information getting to the wrong hands. This requirement might sound simple to implement, but it’s not. Imagine, for example, limiting some customer care staff from accessing certain information relating to the same customers they are serving. This can be a challenge, especially for organizations that do not have the budget to develop sophisticated systems.

Luckily, you can leverage AI and ML to implement continuous compliance monitoring and compliance-based restrictions that swing into action during user sessions.

5. Enhanced security

AI solutions like the custom ones we develop at Tricenson through Domain AI have capabilities that can detect user anomalies and highlight potential threats before they can lead to damages.

An AI-driven IAM system will review the following items related to access:

• Login patterns e.g what time the user normally logs into specific apps
• Duration of use i,e how long does a user normally spend
• Intensity of activities.

AI-driven anomaly detection is possible through use of detection algorithms that analyze items such as user behavior to pick out patterns that fall outside the normal behavior.

With such a level of analysis, the system will employ intelligent user profile management and come up with what can be classified as the normal pattern. Whenever this normal pattern is side-stepped, the system will prompt advanced authentication levels such as multi factor authentication.

For example, an unusual login attempt or data download can be easily flagged by an AI-based IAM system. The system then blocks these unauthorized access attempts and alerts the administrators or affected users to take actions like changing passwords and scan devices.

Also Read: Password Security Fundamentals and Strong Password Policy

6. Personalized experiences for users

How about delivering personalized experiences for users whenever they are logged into different systems? Yes, this is possible when you incorporate AI into Identity and Access management.

A good example is what we call Adaptive Authentication, where machine learning algorithms are used to analyze user behavior on a continuous basis and use the results to guide continuous user authentication. This helps to determine the level of risk associated with any user.

The system then uses these insights to offer different levels of experiences to different users whenever they gain access to resources within the organization.

For example, an IAM system can adjust security measures from one user to another. What this means is that the steps that user A will have to go through in order to log in, for example, will not be the same as the steps that will be required of user B.

This personalized approach taps into each user’s unique behavior, ensuring that users whose behavior presents the least risk do not have to go through intense processes or restrictions.

Steps to get started with AI in Identity and Access Management

1	Identify areas of use	Identify those areas in IAM where the use of AI will bring the greatest value
2	Data	Get the right data, based on the use cases you will have identified above. Needless to say, AI models need lots of data to be able to function efficiently. The collected data, e.g event logs, ought to be up to date and clean
3	Implement in phases	Start small and implement the AI solution in a phased approach. You can do this by targeting a specific group of users to get an idea of how well the system actually operates. After this, you can scale up to more groups.
4	Governance	Create and implement robust governance models to ensure that sensitive data will always be secure and out of reach of risky users who can escalate the risk of exposure to cyber criminals. If you already have a data governance policy, be sure to include aspects that directly govern the use of AI in IAM and how the data should be handled responsibly.
5	Monitoring	Develop a monitoring system to ensure that the AI-driven IAM systems are always functioning at optimal level. The monitoring system should incorporate risk assessment protocols designed to spot new risks, classify and recommend measures to ensure they do not lead to damages such as data breaches

Data challenges associated with AI-driven IAM

While AI is great for driving the modern IAM systems, it can only be as good as the data that is available to it.

Biased data will automatically result in biased processes, which can lead to unfair decisions affecting users. The affected users will feel that they have been targeted unfairly and this can dent their morale in the workplace.

Besides the quality of data, there is also the challenge of ensuring that the AI systems are always working with the latest data. The ability to acquire this type of data on a constant basis is a challenge for many organizations, due to budget constraints.

Also Read: How to Overcome Challenges in AI Adoption

Best practices to make the most of AI in IAM

• Make user feedback part and parcel of the AI-driven IAM system. Involve them from the beginning so they can buy into the system as a friendly ‘partner’ whose sole aim is to enhance their experiences while protecting their identities and the company’s data. A continuous user feedback loop can be used to make incremental changes that ultimately culminate in a sound system that everyone enjoys to use.
• Take advantage of emerging trends across AI in IAM. Good examples include blockchain-driven identity verification and biometric authentication.
• Design the AI-driven IAM system in such a way that it can unearth useful insights that can be used to improve various aspects of IAM, especially access policies and processes. It should have the capability to generate reports that show key areas that need attention. These insights are valuable for security managers who can use them to optimize the IAM system. For example, AI can suggest the best restrictive measures for different users.

Conclusion

Artificial Intelligence is quickly changing how organizations apply technology across different operational functions. From customer care to sales and marketing, AI is getting entrenched in many organizations’ activities. In this AI revolution, the field of IAM is one of those domains that will be greatly impacted by AI.

When you back your IAM systems with AI, you automatically transform how users access important company resources including tools and applications. This ensures that each user’s access is efficiently authenticated and their identities secure.

The power of AI transforms IAM to a brand new world where, for example, passwords will no longer be necessary. In the place of passwords, behavioral access patterns will be the key avenue for authenticating users. Machine Learning algorithms will accurately detect any breach attempts and thwart them before they occur.

Essentially, AI transforms IAM into a smart system that is not only user friendly but extremely fast and accurate.

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