Non-Human Identity Management: Identity Governance for AI Agents

Today’s businesses must manage an ever-growing number of digital identities – and do so across an expanding set of systems. They also have to manage bigger operational demands like stronger security, new and existing compliance requirements, greater scalability and faster onboarding. This must all be done with accuracy and speed, and that means they need to embrace a new way to deal with identity governance that can both handle today’s challenges and those on the horizon.

What’s a Non-Human Identity?

Human identities are what we’re most familiar with: the employees, contractors and even some partners or customers who need access to the corporate network, apps and data. Non-human identities (NHIs) are their digital counterparts: application keys, devices, bots, service accounts and other digital components. Each of these must have a unique identifier.

Organizations must manage these NHIs effectively so that they can authenticate and validate machine-to-machine interactions. It’s another way to prevent unauthorized access to the company’s crown jewels. Organizations need to govern the permissions of these identities, along with which humans are accessing them. NHIs must be safeguarded and verified so that malicious actors can’t manipulate them.

The Challenges of Non-Human Identities

With the rising enterprise adoption of generative AI, this technology is being embedded in workflows. This creates a new realm of security challenges related to identity, specifically the digital identities of AI agents. Such NHIs are used as documentation tools, legal aides, customer service assistants and similar roles, and this means they need access to sensitive data and systems. However, NHIs also create additional complexity in terms of ethical use, data minimization and accountability.

The rise of AI agents is rapidly impacting legacy Identity Governance and Administration (IGA) methodology. At the same time, enterprises are confronted by new compliance requirements. In the European Union, this is especially important for companies because of the EU’s insistence on localized infrastructure and data sovereignty.

For IGA, AI is both a blessing and a curse. It introduces governance risk, which means it needs role-based control and monitoring. But AI is also a governance tool that has the capacity to analyze patterns of access, improve decision-making and make user experiences simpler. Enterprises need to learn how to keep a tight rein on these new identities yet at the same time use AI to improve operational efficiency and security.

The challenge of app sprawl figures in, too. Every new SaaS solution, including AI tools, introduces new access to grant and manage. In a 2024 report, 72% of CIO participants noted that app sprawl was concerning. The Zero Trust approach and today’s diverse threat landscape demand tight integration between cybersecurity tools and IGA to manage these expanding attack surfaces.

Gartner analysts noted in their publication from June of this year, Strategic Roadmap for Modern Machine IAM: “The maturity of machine identity and access management (IAM) for most organizations lags significantly behind human IAM, leading to increased security risks and compliance issues. This is due to fragmented and inadequate machine IAM practices that rely on outdated methods.”

Regulatory Hurdles

Organizations must also address the ongoing additions to the regulatory slate. Compliance is not just about adhering to the law; it adds another layer of security for companies and maintains trust. Organizations face many regulations and standards that include strict controls for sensitive data and IT systems: GDPR, NIS2 and DORA in the EU; the NIST Cybersecurity Framework (NIST CSF), Sarbanes-Oxley (SOX) and the California Consumer Privacy Act (CCPA) in America, among others. Noncompliance can lead to fines, disrupted operations and damage to your reputation.

NIS2 (Network and Information Security Directive 2) became law in the EU in October 2024. This has caused enterprises to reconsider whether on-premises or cloud deployments are best. NIS2’s aim is to improve the cybersecurity of member states by establishing a common baseline for information and network systems. It requires organizations to have stricter cybersecurity protocols and measures related to incident reporting.

Ensuring Governance of NHIs

It’s clear from the challenges discussed above that organizations need automation for the standard IGA processes like Joiner/Mover/Leaver as well as for access requests for business applications and systems. Gartner analysts noted in the above-mentioned report the need to “regain control of an essential capability that underpins every critical business function by creating a machine IAM strategy that is focused on ‘stopping the bleeding’ as a first priority and move towards an efficient and secure enablement of critical business operations through machine-to-machine interactions.”

So, companies must integrate their new accounts and permissions for applications into the concept of enterprise access management and governance to overcome app sprawl. Companies need a logical application management layer, even if they manage authentication and authorization through EntraID, AWS or GCP, for instance.

This gives identity and access managers a business-focused method for requesting, approving and reviewing access. The role-based approach to access management helps structure permissions, manage access at the business level, and more easily meet compliance requirements.

It’s imperative to automate governance processes as access and its requirements become more complex – including AI support and automated workflows for access recertification. It also means that effective responses to cyber threats are only possible when IGA and other Identity Fabric components are integrated and support event-driven defense actions.

One real-world example is detecting of anomalies, sending alerts and automatically shutting down access. Administrative-level automation involves ongoing monitoring of responsibilities and role- and entitlement-related risks. In addition, cost-effective compliance must have efficient analytics and reporting abilities that address audit requirements.

AI agent-based ecosystems demand precise authorization management. Different agents require different access: one agent might update employee calendars by accessing schedules and availability; another might collect sensitive financial data to manage portfolios and execute transactions; a third might oversee codebases to merge features and fixes.

Just as doctors and nurses access patient records only when clinically justified, AI agents need role-specific access controls. It’s neither sustainable nor secure to grant carte-blanche access to all organizational data. If the financial agent also accessed employee calendars or codebases, organizations would face data leakage and compliance violations.

The challenge extends beyond verifying an agent’s identity to controlling each agent’s authorized behavior in constantly changing environments.

Role modeling, risk detection, clean-up, improvement suggestions, reporting and similar tasks get an upgrade with the new possibilities provided by AI features. If, for instance, you want a certain report, the AI will translate your request into a technical query or filter set and generate that report in seconds.

Organizations need a new method for orchestrating the deluge of human and non-human identities. The emerging crop of IGA tools provides granular policy management, lifecycle automation and advanced authorization workflows. For all manner of identities, these tools gather all the information companies need to create and enforce rules. And to ensure that trust boundaries and permissions remain in place as AI agents scale, IGA tools must interweave seamlessly with generative models and AI frameworks.

Solving The Identity Crisis

Modern organizations can’t “wait and see” when it comes to the profusion of human and non-human identities; they need a decisive and immediate plan to meet this challenge. Identity governance solutions are incorporating AI and automation to help with this change, emphasizing advanced role-based access design and cross-system integrations. Companies need to remain efficient, and with IGA, that translates to automation of important functions like reporting and recertification. Regulated verticals must remain compliant, and IGA must be a key enabler of that. To keep up with digital transformation, identity governance needs to possess both control and adaptability.