If you ask a CISO what keeps them up at night, the answer usually isn’t “lack of tools.” It’s uncertainty.
Uncertainty about what they don’t see.
Uncertainty about how far an attacker could move once inside.
Uncertainty about whether identity programs are actually reducing risk—or just managing symptoms.
Identity discovery sits at the center of that uncertainty. It is not glamorous. It does not get the same attention as AI-driven detection or zero trust initiatives. But it is the foundation of meaningful risk reduction.
Without comprehensive visibility into every identity across the environment, identity security programs operate with blind spots. And blind spots are where breaches begin.
Most identity security programs were designed for a simpler world: a central directory, a defined workforce, a clear boundary between inside and outside. That world no longer exists.
Workloads now shift dynamically across multi-cloud environments. Development teams deploy infrastructure through code. CI/CD pipelines create and destroy resources automatically. SaaS applications proliferate across business units. And now, AI agents and LLM integrations are being introduced into production environments at unprecedented speed.
Every one of these shifts generates identities.
Not just human users—but service accounts, cloud roles, workload identities, API keys, tokens, certificates, automation bots, and AI-driven agents. These identities are created programmatically, often with broad permissions to ensure functionality. They are replicated across environments, inherited through nested roles, and sometimes left behind when projects end.
Security teams can see pieces of this activity. They notice a new role in AWS. They see a new service principal in Entra. They detect a new Kubernetes service account. But seeing that something exists is not the same as understanding what it can do.
The real question isn’t “Does this identity exist?” It’s “What does it have access to—and what could it access next?”
Attackers exploit precisely this ambiguity. Modern breaches often do not begin with zero-day exploits. They begin with compromised credentials or misconfigured permissions. From there, attackers move laterally, leveraging excessive privileges, trust relationships, and identity inheritance paths that security teams didn’t fully map.
If risk reduction is the objective, visibility must come first.
The scale of the identity problem is not incremental. It is structural.
According to Delinea Labs, in 2025 the average enterprise has approximately 46 non-human identities for every human identity. That ratio fundamentally changes how organizations must think about identity risk.
Non-human identities now outnumber people by orders of magnitude. These include cloud workload identities, service accounts, automation scripts, API tokens, containers, RPA bots, and increasingly, AI agents operating semi-autonomously. They authenticate, request resources, call APIs, and access sensitive systems—often without direct human interaction.
Yet many organizations still rely on a patchwork of legacy tools to manage them. Privileged Access Management (PAM) handles certain administrative accounts. IAM platforms govern workforce access. Endpoint protection secures devices. Identity Threat Detection and Response tools monitor suspicious behavior.
Each solution serves a purpose. But each also operates within its own silo. There is no unified, common identity plane where every identity—human, machine, and AI—can be seen in context.
As a result, organizations struggle to answer fundamental questions about exposure. They pivot between consoles. They manually reconcile data from multiple platforms. They attempt to stitch together access relationships across cloud providers and identity systems. Meanwhile, identities continue to multiply.
The issue is not a lack of tooling. It is a lack of unified visibility.
Strategic identity discovery requires more than periodic audits or static inventories. It requires continuous, universal coverage across the entire identity lifecycle.
To accomplish this organizations must first achieve comprehensive identity coverage. Every identity—whether an IT administrator, developer, workforce user, service account, workload identity, or AI agent—must be discoverable the moment it is created. Visibility cannot begin weeks or months after deployment. It must be immediate.
But discovery alone is not enough. For each identity, organizations must understand their posture. Is it overprivileged? Is it stale or inactive? Is it unmanaged or non-vaulted? Does it violate policy? Does it create lateral movement risk?
Posture turns visibility into intelligence. It allows security leaders to prioritize remediation based on risk rather than assumption.
Second, identity visibility must extend across hybrid environments. Modern enterprises span multi-cloud platforms, on-premise infrastructure, SaaS ecosystems, and DevOps pipelines. Identity providers such as Okta, Ping, and Microsoft Entra each maintain their own access models and permission hierarchies. Cloud providers enforce distinct role and policy structures.
Without cross-environment visibility, organizations misjudge risk because they see only fragments. An account may appear compliant in one system while holding excessive privileges in another. A service identity may be governed on-premise but unmanaged in a cloud tenant. An AI agent may authenticate through one provider but inherit permissions across multiple platforms.
True hybrid visibility collapses these silos and exposes the full identity attack surface.
Third, and most critically, organizations must understand identity relationships. Risk does not reside solely in individual accounts—it resides in how identities connect.
Access inheritance, nested group memberships, trust relationships, policy attachments, and cross-account permissions create hidden escalation paths. These relationships are often invisible in traditional dashboards.
This is where identity graphing becomes essential.
An identity graph maps how identities relate to one another and to the resources they can access. It reveals not just what an identity can access directly, but what it can access indirectly. It shows escalation chains, lateral movement paths, and toxic identity misconfigurations.
This forms a common identity plane—a unified model where identities, access paths, and posture are visible in context.
Importantly, this visibility is not just for identity specialists. When presented clearly, an identity graph can be used by SecOps teams investigating incidents, by risk teams assessing exposure, and by compliance teams validating controls. It democratizes identity intelligence across the organization
Identity security has reached the board level. Gartner reports that 84% of organizations view identity security as a board-level concern vs. a technology concern.
Boards increasingly ask CISOs to quantify cyber risk. They want measurable indicators of exposure, progress, and resilience. They want clarity around AI adoption and machine identity risk. They expect more than technical explanations—they expect strategic insight. Identity discovery enables CISOs to answer two essential questions for every identity in the enterprise:
What does this identity have access to?
And what does it have access to next?
Privileges drift over time. Roles accumulate. Policies overlap. AI systems request additional permissions. Developers reuse credentials or hard-code them into applications. Temporary access becomes permanent. Without continuous visibility into how access evolves, organizations cannot accurately model breach impact.
Boards do not need to understand every technical detail. But they do need confidence that identity exposure is measured, monitored, and reduced over time. They need evidence that overprivileged accounts are being remediated. They need transparency into machine and AI identity risk. They need to see that identity posture is improving, not stagnating.
Full visibility into identity posture transforms identity security from an operational control into a strategic risk management discipline.
Many organizations attempt to enforce least privilege, rotate secrets, or deploy threat detection tools before establishing comprehensive discovery. These controls are valuable—but without visibility, they are incomplete.
You cannot reduce overprivilege if you do not know where it exists.
You cannot eliminate shadow admins if you cannot see them.
You cannot manage AI risk if AI identities are not discoverable.
Identity discovery is the prerequisite to automation, governance, and meaningful metrics. It establishes the baseline. It reveals the gaps. It prioritizes remediation. And it provides the data needed to demonstrate improvement over time.
In a threat landscape increasingly defined by credential misuse rather than software exploits, identity visibility is not optional. It is foundational.
Security leaders do not want more tools. They want clarity. They want to stand in front of their boards and speak with confidence about identity exposure, machine identity growth, AI governance, and measurable risk reduction.
Identity discovery delivers that clarity.
By illuminating every human, machine, and AI identity; by mapping access relationships across hybrid environments; and by tracking posture over time, organizations create a unified identity plane. Within that plane, risk becomes visible. And once visible, it becomes manageable.
Identity discovery is not a feature. It is a strategy.
To learn more about how comprehensive identity discovery can strengthen your organization’s risk posture, register for our webinar: Why Discovery is the Foundation for Identity Security.