Benoit Grangé, chief technology & product officer at Omada.
As organizations move increasingly faster through the digital world, it has become more important to give employees frictionless access to the tools they need for their jobs—lest productivity suffer. However, manually maintaining, approving and recertifying identity has long since become an impossibility, leading more organizations to seek out solutions with automated capabilities.
Artificial intelligence (AI) and machine learning (ML) can help with automation. In fact, they have the potential to transform how organizations conduct identity governance and administration (IGA) today.
In Search Of IGA Efficiency
Leaders are looking to balance productivity with security—which means they need the ability to quickly and accurately certify and recertify identities, provide access and so on. When it comes to identity security and governance from a business perspective, leaders are most concerned about how they can control the ecosystem.
There is a massive risk today of ransomware; if access isn’t secure, then neither is your infrastructure. How do they address all of the access they have to manage across all of the different environments? How do they make sure end users are getting the right access at the right time?
Another issue is managing employee and contractor identities and access in a quick, compliant and effective way. How are organizations going to onboard identities faster? How can they deliver just-in-time access to people? That’s where the market is moving: providing access to an application within 30 minutes, for instance.
Improving Identity Governance: AI And ML’s Expanding Role
To meet today’s identity demands, organizations can’t rely on manual activity alone. AI, ML and automation brings the potential to accelerate and improve this function. Here are three ways AI/ML can help:
Enhanced Data Mapping And Cleaning Using Large Language Models (LLMs)
Traditionally, the integration of IGA with a company’s ecosystem required substantial manual effort to ensure data consistency and accuracy. However, LLMs can analyze vast amounts of unstructured and structured data—identifying patterns, anomalies and relationships that might not be immediately apparent to human administrators.
By leveraging these capabilities, LLMs can automate the data mapping and cleaning process, ensuring the IGA system integrates seamlessly with the company’s existing infrastructure. This reduces the time and effort required for setup, leading to quicker deployment and more reliable data governance.
Intelligent Workflow Creation And Automation For Administrators
Using advanced algorithms, AI can analyze the organization’s current processes and recommend optimized workflows that enhance efficiency and compliance. Administrators can interact with AI to design, test and implement workflows tailored to their specific needs.
This not only simplifies the workflow creation process but also ensures the workflows are robust, secure and in line with regulatory requirements. Additionally, AI/ML can continuously monitor these workflows, making real-time adjustments and recommendations to improve performance and address emerging security threats.
AI/ML Assistants Integrated With Everyday Tools For End Users
The integration of AI/ML assistants into everyday tools like Microsoft Teams provides real-time support and recommendations, helping users with tasks such as access requests, role assignments and compliance checks directly within their familiar work environment. By integrating AI/ML capabilities into tools that users already use daily, the adoption and execution of IGA functions become more intuitive and less disruptive.
For instance, a user needing access to a particular system can interact with the AI assistant in Teams to request access, receive automated approvals based on predefined policies and get immediate feedback or instructions. This seamless integration not only enhances user experience but also ensures IGA processes are followed consistently and efficiently.
Getting Started With AI/ML In IGA: Best Practices
It’s a good practice to consider where some of the quick wins are in terms of deriving value from AI/ML in IGA. LLMs can help the user better understand what they’re doing, providing transparency. Even something as basic as being able to rely on an LLM to better explain to the user what they’re approving is a big step. Many times, administrators don’t understand what they’re approving. It’s really about making the user experience simpler and better.
Another best practice is to always keep data privacy front and center. There are always concerns about data leakage and data privacy, which have to be addressed in the IGA realm. Too often, AI can be something of a black box. When working with a vendor, transparency is key. Make sure they can explain what data the AI models are ingesting and how that data will be protected.
Setting Up For IGA Success
AI/ML is set to transform the IGA space by enhancing data integration processes, automating workflow creation for administrators and integrating intelligent assistants into everyday tools for end users. These advancements will accelerate the setup and integration of IGA systems, improve the accuracy and reliability of data, and make it easier for both administrators and end users to manage and comply with identity governance policies. Identity leaders need to understand these changes to optimize access and efficiency in a cloud-centric environment.
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