Identity management has long been treated as one of cybersecurity’s foundational disciplines, but not always one of its most dynamic. Organizations have invested in single sign-on, multifactor authentication, privileged access management, service account governance, and other core controls. These capabilities are vital, but they often operate quietly in the background. In many security programs, identity has been treated less as a strategic front line than as a necessary layer of access control. 

The rise of AI agents is changing that. 

As enterprises move from experimenting with large language models to embedding AI into workflows, applications, and business processes, they are also creating a new identity challenge. The users interacting with enterprise systems are no longer only employees, contractors, customers, or partners. Increasingly, they are also agents, service accounts, API-driven workflows, and other non-human identities acting on behalf of people or organizations. 

That shift has major implications for cybersecurity. Most identity management programs were not designed for a world in which non-human identities can proliferate faster than human ones, interact across systems at machine speed, and hold access to sensitive data and business functions. But this is the world businesses are operating in today. 

The Old Identity Model is Under Strain 

The human-centered model for identity management has never been easy to manage well, but it is at least understandable. The goal has been to understand who a user is and whether they should have access to certain information or systems.  

AI complicates that model because it dramatically expands the universe of identities that need to be governed. An employee using an AI tool might create multiple agents. Each of those agents might need access to data, applications, APIs, or business workflows. Some might connect to tools through an MCP server. Others might rely on API keys or service accounts. Some might operate in narrow, controlled contexts. Others might touch sensitive systems or make decisions that have a business impact. 

That creates a scale problem as well as a lifecycle problem. Historically, many organizations have not done a good enough job rotating service account credentials, retiring unused accounts, managing API keys, or limiting machine access to the minimum required. In a more static technology environment, those weaknesses were already risky. In an AI-enabled environment, they become much more urgent. 

An exposed API key, a long-lived service account, or a poorly governed agent identity can become an open door. And unlike a human user, an automated process can act continuously, quickly, and across systems. That does not make non-human identities inherently dangerous, but it does mean they require much stronger governance than many organizations currently have in place. 

AI Does Not Replace the Fundamentals 

Let’s be clear: Rethinking identity management for the agentic era does not mean organizations should abandon the basics. In fact, the opposite is true. Strong security hygiene remains one of the most important defenses against both traditional and AI-enabled threats. 

Organizations still need to patch systems. They still need endpoint detection and response. They still need logging, telemetry, backups, and tested recovery processes. They still need multifactor authentication, phishing defenses, access reviews, and a workforce that understands its role in protecting the enterprise. 

That human layer remains critical. Even as threat actors gain access to more sophisticated tools, many attacks will continue to begin with familiar tactics: stolen credentials, social engineering, malicious links, exposed secrets, or misconfigured systems.  

The better way to think about AI risk is that, rather than replacing the old security model, it puts pressure on the parts of that model that were already underbuilt. Identity is one of those areas. 

The Next Phase of Identity Must Reduce Friction and Risk 

One of the reasons identity management has lagged is that it has often been associated with friction. Security teams add controls. Users experience delays. Developers look for workarounds. Business teams push for speed. Over time, identity becomes a tug-of-war between security and productivity. 

That approach will not work in the agentic era. AI-enabled businesses will need to move quickly. The goal should be to reduce friction and reduce risk at the same time. 

That requires a more modern approach to identity lifecycle management, especially for non-human identities. Organizations should be moving toward short-lived credentials, automated key rotation, just-in-time access, stronger secrets management, and clearer ownership for every service account, API key, and agent identity. Access should be granted based on what an identity needs to do, limited to the time it needs to do it, and revoked when that need expires. 

This is especially important for AI agents. An agent should not inherit broad access simply because the user who created it has broad access. It should have bounded permissions and clear accountability. 

AI agents will create enormous opportunities for efficiency and business transformation. But they will also force enterprises to confront a reality that has been easy to ignore: Identity now extends beyond people. It encompasses every human, machine, service, workflow, and agent that can act inside or on behalf of the organization. The companies that recognize this now will be better positioned to adopt AI securely and at scale.