Human vs. Non-Human Identities: Key Differences, Security Risks, and Governance Best Practices

First, there were human identities, and now there are Non-Human Identities (NHIs). Your traditional enterprise Identity and Access Management (IAM) was primarily built for your employees, vendors, or contractors, and often lacks governance capabilities for NHIs at scale - this is the first problem.

The second problem is that your employees are no longer the majority in your organization. As per the report by the Cloud Security Alliance (CSA), in 2024, the ratio of machine to human identities was 20 to 1, with some predictions of the ratio being 92 to 1, showing a significant upward curve.

Since NHIs are currently dominating the market, it is paramount to understand the difference between humans and machines. Because the way you secure something depends entirely on how it behaves, and humans and machines behave nothing alike.

Comprehending the difference helps in effective IAM and identity governance in the modern enterprise ecosystem. This blog breaks down what each identity type looks like, how they’re connected, where the risks lie, and how to govern both without losing your mind.

Human and Non-Human Identities: A Quick Overview

Humans and non-human identities — these two are different, not just in what they are, but in how they behave, how they’re created, and how they go wrong.

What Are Human Identities?

Human identities comprise real people who interact with your systems. They log in, make decisions, access data, and operate under organizational roles and policies.

Common examples include:

• Employees accessing internal apps and corporate resources
• Contractors who are brought in for specific projects and need temporary access
• Partners from external organizations collaborating on shared systems
• Vendors who require access to specific tools or data to deliver services

Human identities are tied to a person’s intent, accountability, and behavior. When something goes wrong with a human identity, there’s a person at the center of the incident.

What Are Non-Human Identities?

Non-Human Identities (NHIs) are digital entities that operate programmatically. They access resources and execute tasks, but without a person actively driving them.

Examples include:

• Service accounts running scheduled jobs or backend processes
• Applications connecting to third-party platforms or databases
• APIs that are exchanging information between systems and microservices
• Workloads in cloud environments
• Containers provisioned dynamically in DevOps pipelines
• Bots automating repetitive workflows and tasks across platforms
• AI agents making autonomous decisions, orchestrating systems, and calling APIs.

NHIs operate at machine speed, often without human oversight and in real-time. That’s what makes them so powerful and risky.

The Identity Explosion: How We Got Here

Almost a decade ago, non-human identities existed in most organizations, but they were manageable, and IT teams knew where they were.

The shift began with cloud adoption. As enterprises moved workloads to Azure, AWS, and GCP, they stopped thinking in terms of static servers and started thinking in terms of services. Each service needed credentials to talk to the others. This is how identity sprawl began quietly.

After this, DevOps amplified the machine identity sprawl through CI/CD pipelines, container orchestration tools like Kubernetes, cloud automation, and infrastructure-as-code, making it a practice to provision identities programmatically.

Developers created dozens of service accounts without formal governance processes. Many of those accounts are still active today, owned by projects that no longer exist.

An AI agent doesn't just hold one identity; it may orchestrate dozens of actions, calling APIs, accessing databases, and spawning sub-agents, each with their own access requirements. Managing these identities with traditional IAM tools is like trying to track a wildfire with a garden hose.

How Are Human and Non-Human Identities Linked Together?

Every machine identity has a human origin story.

A developer creates a service account to automate a deployment pipeline. An admin provisions API credentials so a third-party integration can pull data from your CRM. A security engineer sets up a workload identity for a cloud function. An IT team grants an AI agent permissions to access the ticketing system. In every case, a human made a deliberate decision to create that non-human identity and grant it access.

That human-machine link is where risk accumulates silently. When the developer who created that service account leaves the organization, the account doesn't automatically go with them. When the project that needed that API key wraps up, the key often lingers. When an AI agent inherits permissions from its human owner, those permissions may be excessive, and now they're operating at machine speed with no human in the loop.

Here’s how human and NHIs are intertwined:

• Both humans and cloud resources access crucial information via shared role identities.
• Machine-created keys and tokens inherit permissions from humans and maintain a separate access process.
• While human identities govern standard IaaS and SaaS users, service accounts exist as distinct identity objects tailored specifically for automated processes.
• Traditional identity boundaries are blurred because human employees create and manage service accounts and their secrets.

This interconnection also means that identity governance must be holistic. A unified view of both humans and NHIs, mapped to each other. This is the only way to understand your true access risk.

Human vs. Non-Human Identities: Key Differences

Here is a list of differences between human and non-human identities:

Here, the differences aren’t just technical. They reflect fundamentally different management philosophies, which is why a single, unified approach to identity lifecycle management matters so much.

Why Are Non-Human Identities Growing Faster Than Human Identities?

Human headcount grows at a predictable pace. But non-human identities grow exponentially. Here’s why:

1. Cloud Adoption

With organizations going to the cloud, here’s what’s happening: when a deployment team deploys a single app, they need a managed identity to call external APIs, a service principal to query a database, and a role to write logs. This has created three NHIs already.

Enterprises have no accurate count of how many machine identities exist across their cloud environments, let alone who owns them or whether they’re still needed.

2. DevOps Automation

Modern DevOps practices rely on automated pipelines for building, testing, and deploying software.

Each step in those pipelines typically requires credentials to access repositories, push container images, update configurations, or trigger deployments. These are machine identities, and they multiply with every new pipeline.

3. API-Driven Integrations

The average enterprise uses several SaaS apps, most of which offer APIs for integration. Every integration requires authentication, typically API keys or OAuth tokens. As the SaaS stack grows, so does the number of API credentials in circulation, many of them untracked.

4. AI Agents and Autonomous Systems

AI agents are the newest driver of NHI growth, and the most complex. An autonomous AI agent may need access to email, calendars, databases, ticketing systems, and external APIs all at once.

As agentic AI becomes mainstream, AI agent identities will represent a significant and rapidly expanding category of non-human identities that most organizations are not yet equipped to manage.

Security Risks Associated with Human Identities

Human identities are well-understood attack targets. Attackers have spent decades refining techniques to compromise them.

1. Credential Theft

Stolen credentials remain the most common entry point into enterprise environments. It can take place through data breaches, malware, or credential stuffing attacks using leaked databases.

2. Phishing Attacks

Phishing attacks take place via malicious links shared via email or SMS. It can also happen via calls. The hackers trick the users into revealing their credentials through these fake links.

Despite security awareness training, phishing remains one of the most effective attack techniques because it exploits human psychology, not technical vulnerabilities.

3. Privilege Misuse

Users with excessive permissions, whether through role creep or misconfigured access, can access data and systems far beyond what their job requires. Even without malicious intent, over-privileged users represent a significant risk if their credentials are compromised.

4. Insider Threats

Not all threats come from outside. Disgruntled employees, negligent insiders, or staff who are being coerced represent genuine risks. Insider threats are particularly dangerous because they start with legitimate access.

5. Social Engineering

Beyond phishing, attackers use vishing (voice phishing), pretexting, and impersonation to manipulate employees into granting access or sharing sensitive information. Social engineering exploits trust, not technology.

6. Brute Force Attacks

Brute force attacks are those where attackers try out different combinations of usernames and passwords to break into an account. These credentials are acquired from the dark web or pre-leaked data.

Automated tools can attempt a lot of password combinations. Accounts without MFA, particularly those with weak or reused passwords, are vulnerable to brute force and credential stuffing attacks.

Security Risks Associated with Non-Human Identities

The risk profile for non-human identities is different — and in many ways harder to manage because these identities operate silently, at scale, and without human oversight.

1. Orphaned Service Accounts

When the employee who created a service account leaves the organization, the account typically stays behind; this is an orphan account.

Orphaned accounts retain their original permissions indefinitely unless someone actively tracks and removes them via an orphaned account management solution. Attackers specifically hunt for these forgotten accounts to get into the system.

2. Excessive Privileges

Service accounts and API credentials are frequently provisioned with broad permissions for convenience. Over time, those permissions are never scaled back. An overprivileged service account is a lateral movement goldmine for any attacker who gains access to it.

3. Hardcoded Secrets

Hardcoded secrets are sensitive credentials, such as API keys, authentication tokens, or passwords, written directly into the source code. Developers sometimes embed them directly in source code.

These secrets end up in version control systems, sometimes public ones. Once a hardcoded secret is leaked, it can be exploited before anyone notices it's exposed.

4. Untracked API Keys

API keys are often created informally, outside of centralized governance processes. They accumulate in spreadsheets, email threads, and individual developer environments.

Without a centralized inventory, organizations have no way to know how many keys exist, who created them, or when they were last used.

5. AI Agent Access Risks

AI agents present a unique challenge. They may be granted broad permissions to function effectively, but those permissions can be exploited if the agent is compromised, manipulated through prompt injection, or left running after its intended purpose is fulfilled. AI agent identities require purpose-specific, least-privilege access controls.

6. Unauthorized Access

Misconfigured non-human identities can inadvertently gain access to resources they were never intended to reach. In complex multi-cloud or hybrid environments, a misconfigured workload identity can access sensitive data or cross security boundaries without triggering obvious alerts.

How Does IAM Handle Security Risks for Human Identities?

Traditional Identity and Access Management (IAM) was purpose-built for human identities — and it does that job reasonably well.

Core IAM capabilities that protect human identities include:

• Multi-Factor Authentication (MFA) to add an extra layer during login, preventing account compromise
• Single Sign-On (SSO) to reduce password fatigue and centralize authentication
• Role-Based Access Control (RBAC) to ensure users only access what their role requires
• Adaptive Authentication to analyze contextual and risk-based signals, such as device, time, location, IP, and user behavior during login attempts
• Passwordless logins to prevent credential-based attacks, password fatigue, brute force attacks, and credential thefts
• Privileged Access Management (PAM) to control and monitor high-privilege human accounts.
• Access reviews and certifications to periodically validate that human access entitlements remain appropriate
• User behavior analytics to detect anomalous activity that may indicate a compromised account

These controls are mature, well-understood, and supported by a deep ecosystem of tools and standards. For human identity management, the fundamentals are established. The challenge lies in applying equivalent rigor to non-human identities, where traditional IAM often falls short.

Why Traditional IAM Falls Short for Non-Human Identity Management

IAM platforms were designed around the assumption that identities are attached to people. That assumption breaks down completely when applied to machine identities at scale.

Here’s where the gaps appear:

• Lack of visibility: Organizations don’t have a complete inventory of their NHIs, creating a visibility gap.
• Identity sprawl: When thousands of service accounts, API keys, and certificates exist across cloud, on-premises, and SaaS environments, tracking them with spreadsheets or basic IAM tools is not realistic.
• Inconsistent ownership: Unlike human identities, which have clear ownership, NHIs often have ambiguous or outdated ownership (if the person who created the NHI has left the organization).
• Manual lifecycle management: Lack of automated provisioning and deprovisioning of employee accounts makes it difficult to manage lifecycles.
• Compliance gaps: The traditional IAM is not designed to capture machine identity compliance, leaving security teams struggling to meet the audit requirements.

These gaps are exactly why machine identity governance and dedicated non-human identity management capabilities are becoming essential components of modern identity programs.

How Does Identity Governance Help Manage Human and Non-Human Identities?

Identity governance extends beyond basic IAM to address the full lifecycle, visibility, and accountability requirements for all identity types.

Here's how it works in practice.

1. Identity Discovery and Visibility

Effective governance starts with knowing what exists. Identity governance platforms scan across directories, cloud environments, SaaS applications, and infrastructure to build a comprehensive identity inventory (human and non-human) with context about what each identity can access.

2. Least Privilege Enforcement

Governance platforms analyze access entitlements against actual usage patterns. Permissions that have never been used or haven't been used in months are flagged for removal or right-sizing. This applies equally to over-privileged human users and over-permissioned service accounts.

3. Secrets and Credential Management

For non-human identities, governance integrates with secret management solutions to enforce rotation policies, detect hardcoded credentials, and ensure that API keys and tokens are stored securely rather than scattered across codebases and configuration files.

4. Role-Based Access Controls (RBAC)

Well-defined roles reduce the risk of excessive privilege for both humans and machines. Governance platforms help organizations build, maintain, and enforce role structures that align with business functions, and flag deviations from established patterns.

5. Lifecycle Management

Identity lifecycle management covers the full arc: provisioning when a human is hired or an application is deployed, access changes as roles evolve, and deprovisioning when the identity is no longer needed. For non-human identities, this means tying service account lifecycle to project or application lifecycle, not just employee records.

6. Access Reviews and Certifications

Periodic access certifications ask the right people whether a given identity still needs the access it has. For non-human identities, this includes validating that service accounts are still tied to active workloads and that API keys are still in use by active integrations.

7. Continuous Monitoring and Audits

Machine identities follow predictable patterns: a service account that runs a nightly sync job behaves the same way every night. The moment it starts accessing resources it has never touched before, or making requests at unusual hours, something is wrong. Continuous monitoring establishes those behavioral baselines and flags deviations in real time, before an attacker has had time to move laterally or exfiltrate data.

For human identities, the same logic applies. A user downloading records at midnight, accessing systems outside their usual scope, or logging in from two locations within an hour; these signals are captured during monitoring.

Beyond threat detection, ongoing audit trails serve a second purpose: compliance. Regulators don't want a snapshot of your access controls from last quarter. They want evidence that your controls were active, enforced, and reviewed consistently over time. Continuous monitoring gives you that evidence automatically, turning audit prep from a fire drill into a routine export.

Best Practices for Managing Human and Non-Human Identities

1. Discover and Classify Identities

You cannot manage what you cannot see. Run a full discovery sweep across all environments to build an authoritative inventory of every identity, human and non-human.

Classify them by type, sensitivity, owner, and access level. Treat this as a living inventory that updates continuously, not a one-time audit.

2. Automate Provisioning and Deprovisioning

Manual processes are where orphaned identities are born. Connect your identity governance platform to your HR system, project management tools, and cloud orchestration layers so that identities are provisioned and deprovisioned automatically.

3. Train Users and Administrators

Human error remains a significant contributor to identity risk. Security awareness training should cover not just phishing and password hygiene, but also responsible service account management.

It should also include proper secret handling and the governance implications of creating machine identities without following established processes.

4. Rotate Secrets and Credentials

Treat secrets like perishables. Establish rotation policies for API keys, service account passwords, certificates, and tokens. Use a secrets management platform to automate rotation wherever possible.

For AI agent identities specifically, consider short-lived, scoped credentials that expire automatically rather than long-lived static secrets.

5. Govern AI Agent Identities

AI agents need to be treated as first-class citizens in your identity governance program. Assign each AI agent a defined identity with documented permissions, a clear owner, and a purpose boundary.

Enforce least privilege aggressively: an AI agent that only needs to read from a specific database should have exactly that access and nothing more.

How Does miniOrange Help Secure and Govern Human and Non-Human Identities?

miniOrange provides a unified identity governance platform designed to handle the full complexity of modern enterprise identity — both human and non-human.

• Unified identity governance: miniOrange gives you a single pane of glass for managing human identities and NHIs across environments.
• Shadow AI governance: Discover, monitor, and secure unauthorized or unapproved AI tools used by employees without the IT team’s knowledge.
• Automated identity lifecycle management: Get automated provisioning and deprovisioning, and everything in-between. Also, avoid the accumulation of orphaned accounts.
• Access certification and reviews: Streamline periodic access certifications with automated campaigns, reviewer workflows, and audit trails.
• Role-based access governance: Enforce roles that align with least privilege principles.
• Visibility across human and non-human identities: Discover service accounts, API credentials, and workload identities across your environment.
• Compliance and audit readiness: Includes built-in reporting, product aligns with major frameworks, and encompasses an audit trail.

Ready to take control of your full identity landscape? See how miniOrange's identity governance platform helps you manage human and non-human identities with confidence.

FAQs

What is the difference between human and non-human identities?

Human identities represent real people: employees, contractors, partners, and vendors, who interact with systems interactively. Non-human identities represent digital entities like service accounts, APIs, applications, bots, and AI agents that operate programmatically.

Why are non-human identities important?

Non-human identities (NHIs) are important because they run cloud workloads, automate processes, and operate at a fast pace. This improves productivity at workplaces, and they are convenient to use.

Are AI agents considered non-human identities?

Yes, AI agents are a category of non-human identity. They authenticate to systems, access resources, call APIs, and take actions just like other machine identities.

How do organizations manage non-human identities?

Effective non-human identity management requires discovery to build a complete inventory, ownership assignment to establish accountability, lifecycle automation to prevent orphaned accounts, secrets management to protect credentials, least privilege enforcement to limit blast radius, and continuous monitoring to detect anomalous behavior.

What role does identity governance play in managing non-human identities?

Identity governance provides the policy, process, and tooling framework that makes NHI management scalable and auditable.