---
title: "When AI Agents Get Access to the Physical World: Why Identity Governance Must Extend Beyond Humans"
description: Agentic AI is transforming enterprise automation. But when autonomous software agents can request credentials, authorize contractors, modify access ...
image: https://key2xs.com/hubfs/key2xs-statement-20261013-0911.png
---

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Physical Access Governance

# When AI Agents Get Access to the Physical World: Why Identity Governance Must Extend Beyond Humans

Oct 13, 2026 · 12 min read · by the Key2XS team

![Agentic AI & PAG](https://key2xs.com/hubfs/key2xs-statement-20261013-0911.png)

*Agentic AI is transforming enterprise automation. But when autonomous software agents can request credentials, authorize contractors, modify access permissions or interact with physical security systems, identity governance becomes a matter of operational resilience, not just cybersecurity.*

## The next identity security challenge is not human

For decades, enterprise security has been built around a relatively straightforward principle: people have identities, identities receive permissions, and permissions determine which systems, applications and resources they can access.

Identity and Access Management (IAM) established the technical mechanisms for authentication and authorization. Identity Governance and Administration (IGA) introduced the policies, approval processes, lifecycle management and accountability needed to ensure that access remains appropriate.

Now, Agentic AI is challenging the assumptions behind both. Unlike conventional automation, AI agents can interpret objectives, develop plans, invoke tools, communicate with other agents and execute sequences of actions with limited human intervention. They are increasingly capable of operating across enterprise applications, infrastructure management platforms, service management systems and operational technology environments.

An AI agent might receive a relatively simple instruction: "Arrange maintenance for transformer stations requiring inspection this week."

To complete that task, the agent could consult an asset management system, identify relevant maintenance contractors, create work orders, schedule appointments and request access permissions.

If the organization has connected its physical access infrastructure to enterprise workflows, the agent might also be able to initiate the issuance or activation of electronic keys. At that moment, an AI-generated decision has crossed the boundary between digital administration and physical infrastructure.

*The fundamental security question is no longer simply whether an AI agent can access a system. It is whether that agent should be allowed to initiate decisions that ultimately open a physical door.*

## Agentic AI introduces a new class of identity

Traditional IGA solutions primarily govern human identities and, increasingly, non-human identities such as service accounts, workloads and application credentials.  
AI agents belong to this broader category of non-human identities, but they introduce additional complexity. A conventional service account generally executes a predefined function. An autonomous AI agent may dynamically select tools, interpret information, delegate tasks and determine how to achieve an objective.  
This creates a governance challenge.

Consider an AI agent responsible for coordinating maintenance activities across a regional electricity distribution network. The agent has legitimate access to a maintenance platform. It can retrieve asset information, identify contractors and submit requests to other enterprise systems. However, its original authorization to coordinate maintenance does not necessarily include the authority to grant physical access. That distinction matters.

An agent authorized to create a work order should not automatically be authorized to approve that work order, select an access recipient and activate an electronic key. These represent different security responsibilities. Without appropriate governance, AI agents can accumulate effective privileges through combinations of otherwise legitimate system integrations.

The result is a new form of privilege escalation, not necessarily because the AI agent exploits a technical vulnerability, but because the organization has failed to establish boundaries around delegated authority.

## Why IGA must become the control plane for autonomous agents

The emergence of Agentic AI makes Identity Governance and Administration more important, not less. Every AI agent capable of performing enterprise actions should operate under a clearly defined identity with an accountable human or organizational owner. That identity should have a documented purpose, a limited set of permissions and an explicit lifecycle.

Just as organizations should not allow employees to retain unnecessary access after changing roles, they should not allow AI agents to retain privileges after completing an assignment. However, conventional identity lifecycle management is not sufficient on its own. Agentic AI requires governance of both the agent's identity and the actions it is permitted to perform.

An effective IGA architecture should establish several fundamental controls.

- **First, AI agents need individually identifiable, governed identities.** Shared administrative accounts make it difficult to determine which agent initiated an action and under whose authority it was performed.
- **Second, authorization must be contextual.** An agent's ability to request access should depend on the specific task, asset, time window, operational conditions and risk classification.
- **Third, segregation of duties must extend to autonomous workflows.** An agent that creates a maintenance request should not necessarily be allowed to approve its own request or independently issue the resulting physical credentials.
- **Fourth, privileges should be temporary.** Just-in-Time authorization is particularly important for agents that operate intermittently or execute high-impact actions.
- **Finally, accountability must remain explicit.** Every significant action should be traceable to the agent, its delegated authority, the governing policy and the relevant human or organizational owner.

This is not simply a technical implementation issue. It is a governance requirement. An AI agent can execute a decision, but it should not become an unaccountable source of authority.

## The dangerous gap between digital permissions and physical access

Most organizations have historically treated logical and physical access as separate security domains. An employee's access to Microsoft 365, SAP or an operational management platform might be governed through IAM and IGA.

The same employee's access to a transformer station, railway signaling cabinet, water pumping installation or telecommunications facility might be managed through an entirely different process.

Physical keys, electronic cylinders, access cards and local authorization databases frequently operate outside the enterprise identity governance lifecycle. This separation already creates security risks for human identities. Agentic AI can significantly amplify them.

Imagine an AI agent that is authorized to coordinate maintenance for a railway operator. The agent identifies a contractor, creates a work order and sends an access request to a connected electronic key management system. If that system automatically accepts the request without validating the underlying identity, delegated authority and access policy, the AI agent has effectively become an independent access administrator.

A compromised agent, a manipulated workflow or an incorrectly configured integration could then cause unauthorized physical permissions to be issued. The electronic lock itself might remain cryptographically secure. The credentials might be genuine. The access transaction might even appear technically valid. Yet the underlying authorization decision could be entirely inappropriate.

*A perfectly secure electronic lock cannot compensate for an ungoverned identity decision.*

This is where physical access governance becomes critical.

## From prompt injection to physical intrusion

One of the distinctive risks associated with Agentic AI is that its behavior may be influenced by information encountered during task execution. Consider a hypothetical attack against an AI maintenance coordinator.  
The agent retrieves a work order containing externally supplied text. Embedded in that text is an instruction claiming that an emergency maintenance procedure requires immediate access for a particular contractor. If the agent incorrectly treats that untrusted content as authoritative, it might initiate an access request that was never legitimately approved.  
This is an example of how prompt injection could influence a downstream physical access workflow.

The attack does not need to compromise the electronic cylinder or break its encryption. Instead, it targets the decision-making process upstream. The same principle applies to compromised agent tools, excessive API permissions, manipulated asset records or poorly governed agent-to-agent delegation.

A malicious or misdirected agent could potentially initiate requests to activate electronic keys, extend contractor access, alter authorized access windows or suppress exceptions, depending on the capabilities exposed by connected systems.

These are plausible threat scenarios, not evidence that any particular deployed system has suffered such an attack. Nevertheless, they demonstrate why protecting an AI model or its prompt is not sufficient. Security controls must be enforced independently at the point where an agent's requested action becomes an operational authorization.

## The missing link: governing the entire access decision

Reference architecture: governed agent-to-physical-access workflow

**AI Agent**

- Requests a maintenance-related action
- Delegated identity and task context

**IAM / IGA Governance**

- Identity verification, policy, SoD, approval, least privilege
- Authorized, time-limited access request

**Physical Access Governance**

Key2XS: policy mapping, execution, reconciliation, audit

- Controlled credential provisioning
- Electronic Key Systems
- iLOQ, ASSA ABLOY, others
- Critical Assets
- Energy, rail, water, telecom
- Events, status and exceptions feed back into governance and audit

Conceptual architecture. Approval requirements and enforcement points depend on the implementation and risk classification. The correct architectural approach is not to prohibit AI agents from participating in physical access workflows.

Their ability to automate administrative processes could create significant operational benefits. Instead, organizations should ensure that agents can only initiate actions within independently enforced governance boundaries.

An AI agent may identify that a contractor needs access to a specific transformer station. It may prepare an access request and submit the relevant work order. However, the authorization decision must remain subject to enterprise policies, identity validation, segregation of duties and, where appropriate, human approval.

Once approved, the resulting physical access permissions should be provisioned through a governed integration with the relevant electronic key management system. *The agent's ability to submit a request must never be confused with the authority to approve it.*

This distinction is particularly important in critical infrastructure, where the consequences of an incorrect authorization can extend beyond information security into operational disruption, equipment damage and public safety.

## How Key2XS connects AI governance to physical access governance

At Key2XS, we believe physical access should be governed as an extension of enterprise identity. Our platform connects IAM and IGA environments, including [SailPoint](https://www.sailpoint.com),[Microsoft](https://www.microsoft.com) Entra ID, [Okta](https://www.okta.com), [OpenText](https://www.opentext.com) and [One Identity](https://www.oneidentity.com), with electronic key management technologies such as[iLOQ](https://www.iloq.com)and [ASSA ABLOY](https://www.assaabloy.com) CLIQ.

![Beheerde agentische AI en fysieke toegang](https://key2xs.com/hs-fs/hubfs/Beheerde%20agentische%20AI%20en%20fysieke%20toegang.png?width=1536&height=1024&name=Beheerde%20agentische%20AI%20en%20fysieke%20toegang.png)

This architecture provides a foundation for bringing physical access permissions into established identity governance processes. Rather than treating electronic key permissions as isolated administrative records, organizations can align them with enterprise identities, roles, authorization policies and lifecycle events.

For Agentic AI, this creates an important architectural opportunity. An AI agent can participate in a maintenance or operational workflow without receiving unrestricted administrative control over physical access systems. Its requests can be routed through governed identity workflows, with Key2XS translating approved access decisions into the appropriate actions for connected key management platforms.

Depending on the integration and policy configuration, these workflows can support controlled provisioning, revocation, event reconciliation and audit evidence. Importantly, governance should not end when a command is issued.

A revocation request, for example, is not necessarily the same as confirmed revocation at the physical credential or lock. Offline electronic locking technologies may have synchronization dependencies. Organizations need visibility into whether an access change was accepted by the key management system and whether additional synchronization is required before it becomes effective. This becomes even more important when autonomous agents operate at machine speed.

*The objective is to maintain a traceable chain from the original business requirement through the identity decision to the resulting physical authorization.*

## Why this matters for CER, NIS2 and operational resilience

European critical infrastructure operators are already facing increasing expectations around cybersecurity risk management, resilience, access control and supply-chain security.

The [NIS2 Directive](https://digital-strategy.ec.europa.eu/en/policies/nis2-directive) establishes cybersecurity risk-management obligations for covered entities, while the [Critical Entities Resilience Directive](https://eur-lex.europa.eu/eli/dir/2022/2557/oj/eng) (CER) addresses broader resilience against disruptive incidents.

Neither framework should be interpreted as explicitly requiring a particular AI-agent governance architecture or a specific physical access governance product. However, uncontrolled AI-driven authorization creates risks directly relevant to the security and resilience objectives these frameworks address.

For an electricity distribution operator, a railway infrastructure manager or a drinking water utility, it is no longer sufficient to know that an electronic key was technically authorized. The organization should also be able to establish why access was granted, who or what initiated the request, which policy permitted it, who held approval authority and when the permission was withdrawn.

As autonomous systems become more deeply integrated into operational processes, these questions become more difficult to answer without consistent identity governance. The challenge is not just preventing unauthorized entry. It is maintaining demonstrable control over every decision that could lead to physical access.

## The future: Zero Trust must apply to machines, agents and physical assets

Zero Trust has fundamentally changed how organizations think about logical access. Access should not be granted merely because an identity is recognized or a request originates from a trusted environment.

Instead, authorization should be explicit, limited and evaluated against the relevant context. The same principle must apply to Agentic AI. An agent that successfully authenticates to an enterprise application should not automatically inherit authority over every downstream system connected to that application. An agent that is trusted to organize maintenance should not automatically be trusted to grant access to critical infrastructure. And an agent that receives authorization for one task should not retain that authorization indefinitely.

The convergence of AI agents, enterprise IGA and electronic physical access systems will therefore require a more comprehensive approach to identity governance. Human identities, machine identities and autonomous agents must operate within a consistent governance model, even when their responsibilities and risk profiles differ. The physical consequences of their actions must be governed just as carefully as their digital permissions.

This is the next logical evolution of Zero Trust. Not simply verifying who or what is requesting access, but ensuring that every consequential action is authorized, appropriately constrained and accountable.

## AI may initiate access, but governance must remain in control

Agentic AI promises to make critical infrastructure operations more efficient, responsive and automated. Maintenance coordination, contractor onboarding, emergency response and access administration are all areas where autonomous agents could deliver substantial value.

*But greater autonomy must not mean weaker governance.*

When an AI agent can influence who receives an electronic key, which physical locations become accessible or how long an authorization remains valid, its actions have consequences in the real world. Organizations that govern AI agents only at the application or API level risk overlooking the downstream physical permissions those agents can influence.

That gap must be closed. The answer is to connect AI-agent identity governance with enterprise IGA and physical access governance, enforcing clear boundaries between requesting, approving and executing access decisions.

At Key2XS, we see this as an essential part of securing tomorrow's critical infrastructure. Because in an agentic world, every physical access decision must still be an identity decision.

*Identity. Policy. Access. Controlled from one platform.*

**Key2XS | Full Digital Governance for Physical Access**

Further reading: [OWASP GenAI Security Project](https://genai.owasp.org/), [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework), [EU NIS2 Directive](https://digital-strategy.ec.europa.eu/en/policies/nis2-directive) and [Key2XS](https://key2xs.com/?hsLang=nl).

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**Written by the Key2XS team**

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