The organization that deploys an AI agent should assign an accountable owner for the agent and the cloud resources it can create or change. The cloud provider remains responsible for the managed services and infrastructure it supplies, but it does not take over the customer’s responsibility for data, identity, permissions, approvals, oversight, or governance. The precise division depends on the service, its configuration, and the applicable agreement.
Why an agent’s cloud activity creates an ownership question
An AI agent can do more than generate a response. It may plan a sequence of steps, call tools and APIs, write data, trigger workflows, retain memory, or use an identity or delegated token to act in a cloud environment. When one of those actions creates a database, virtual machine, storage object, or other resource, the agent is acting with authority configured by people and organizations.
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That makes responsibility a chain, not a single handoff. The agent may initiate an action, but an organization chose to deploy it, connected tools, granted permissions, and selected the account, subscription, or project in which it operates. A cloud provider may operate the underlying platform, but the provider’s role does not by itself make it the business owner of the agent’s workload or its decisions.
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A useful governance distinction is between where a resource resides and who is accountable for the system that caused it to be created. Treat the resource as belonging to the cloud account, subscription, or project in which it was created. Separately name the agent owner and the team responsible for operating the workload. This is a practical management pattern, not a universal legal rule about ownership or liability.
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How responsibility changes across SaaS, PaaS, and IaaS
Microsoft’s agent responsibility model illustrates how duties shift with the deployment model. In general, the more of the agent stack an organization builds and runs, the more of that stack it must secure and operate. The categories below are typical divisions, not guarantees for every product: a service’s configuration and agreement can change the details.
| Deployment model | Provider typically operates | Organization typically owns or configures |
|---|---|---|
| SaaS agent | The orchestrator, model, safety systems, and most tool connectors | Configuration, data-access scope, identity, usage, and approval decisions |
| PaaS agent | The managed runtime, model hosting, and platform safety controls | Instructions, tool and plugin selection, permissions, orchestration logic, memory design, identity, and authorization |
| IaaS agent | Physical infrastructure and potentially a hosted model API | Nearly the entire agent stack, including its runtime and orchestration |
In a managed SaaS agent, a provider may operate much of the software, but the customer still decides what data the agent can reach and what it may do with that data. With PaaS, the provider manages more of the runtime than it would in an IaaS deployment, while the customer configures important agent behavior and access. In an IaaS deployment, the organization generally operates far more of the runtime and orchestration itself.
These labels do not settle a particular dispute. Microsoft describes its framework as governance guidance, not a legal conclusion or a change to a service agreement. Use it to identify operational duties, then consult the agreement, configuration, and organizational obligations that apply to the actual workload.
Who should be accountable inside the organization?
Every deployed agent should have a named accountable owner: a person or team answerable for its business purpose, lifecycle, permissions, monitoring, and intervention. This need not mean the owner personally performs every security or operations task. It means there is a clear point of accountability when someone must approve a change, investigate an action, suspend the agent, or decide whether its work should continue.
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Microsoft recommends knowing which agents exist, who owns them, what they can access, and how to intervene. AWS likewise recommends a registry that records agent ownership, purpose, capabilities, and permissions. A registry turns those expectations into information operators can use rather than leaving the answer scattered across deployment notes or individual employees’ knowledge.
For each agent, record enough detail to connect its activity to people and controls:
- Owner and business purpose: the accountable team or person, and the task the agent is authorized to perform.
- Identity and access: the identity or delegated credentials it uses, the tools and APIs it can invoke, and the data and resource scope it can reach.
- Operational boundary: the account, subscription, project, or workload where it is allowed to act, plus applicable budget limits.
- Oversight and escalation: which actions require a human decision, who receives alerts, and who can pause or disable the agent.
- Lifecycle information: how the agent is reviewed, changed, retired, and associated resources are inventoried or cleaned up.
Assigning an owner is not a substitute for controlling the agent’s permissions. The owner should be able to explain both what the agent is meant to accomplish and the boundaries within which it is allowed to accomplish it.
Why the agent’s identity determines what it can create
An agent usually acts through an identity, credential, or delegated token. The privileges attached to that identity determine which cloud resources the agent can create, modify, or delete. If an agent can provision resources across a broad project, its potential impact is correspondingly broad—even if its intended task is narrow.
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Grant only the permissions required for the task, and define the resource scope as narrowly as the service allows. Separate the agent’s identity from a general-purpose human or administrator identity where possible, so its activity can be attributed and its permissions can be reviewed. Recheck authorization for each consequential action rather than assuming that an earlier grant is appropriate for every later tool call.
Permissions should match the action, not merely the agent’s label. An agent described as a “reporting assistant” may still be able to make changes if its connected identity permits writes. Conversely, a capable model cannot create or delete a resource through a cloud API if it lacks the authority to do so. The practical control point is therefore the combination of tool access, identity privileges, and the agent’s configured workflow.
Which actions need human approval?
Human review is especially important when an action can cause serious, costly, external, or hard-to-reverse effects. Microsoft’s guidance calls for approval gates for writes, deletes, payments, production changes, and external sends. Google Cloud also recommends explicit oversight for consequential decisions.
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- Payments and resource commitments: set an approval threshold or other review process appropriate to the financial impact.
- Production changes: make a human authorize changes that could affect live services or their users.
- External communication: review messages or other actions sent outside the organization when an error could have material consequences.
An approval gate is most useful when it shows the proposed action, the target resource, and the consequences a reviewer needs to assess. A vague prompt to “approve the agent” does not give a person a meaningful opportunity to catch an unsafe or mistaken operation. The organization must also decide who can approve and how a stalled or rejected request is handled.
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How to make resource creation observable
An organization cannot reliably govern actions it cannot connect to an agent, an identity, and a responsible team. Maintain an inventory of agents and their permitted resource scope, and log agent and tool invocations so operators can reconstruct what happened. AWS recommends tracking execution paths; this helps reveal not only the final API action but the sequence of steps that led to it.
For each resource-creating action, useful operational records include the agent or workload identity, the tool or API invoked, the target account or project, the time, and the action’s outcome. The exact fields available depend on the service and logging configuration. The key governance goal is to make it possible to link an event to the agent and its accountable owner rather than treating it as an unexplained cloud change.
Usage visibility matters alongside security logs. Google Cloud documents audit logs and billing dashboards and alerts as ways to monitor workload activity and spend. Monitor resource usage and billing so an agent’s activity does not become visible only after an unexpected charge or operational problem. Google Cloud’s guidance explicitly notes that customers remain liable for charges accrued by agents, including consumption on Google and third-party offerings: “Agent resource consumption and expenditures on Google and third-party offerings, as you remain liable for any charges accrued by your agents.”
Pair visibility with a response path. Decide in advance who investigates an unfamiliar resource, who can pause an agent, and who can authorize cleanup. Logging without an owner may explain what happened while leaving no one responsible for acting on the information.
What to do when an agent creates an unexpected resource
Start by identifying the resource’s account, subscription, or project, then find the agent owner and the identity or tool invocation associated with its creation. Confirm the resource’s scope and dependencies before removing it; deleting infrastructure can interrupt a workload or affect data beyond the immediate object.
- Establish scope: identify the affected project or environment and determine what resource or resources are involved.
- Trace the action: use available logs and inventory records to identify the agent, its owner, and the identity or tool that initiated the change.
- Contain carefully: if activity needs to stop, choose a reversible disable or stop action where that is suitable, and coordinate with the owner before irreversible deletion.
- Assess shared impact: check whether the operation affects other agents, services, or consumers before applying it at project or infrastructure level.
- Review the cause: examine the agent’s instructions, tools, authorization, and approval path, then adjust the relevant control before restoring activity.
Scope checks matter because a control boundary may be shared. Microsoft notes that a Foundry project can contain several agents, so project-level actions can affect them together. It also warns that infrastructure actions on multitenant applications can affect all consumers. Do not assume that an administrator’s action is isolated to the single agent that triggered the investigation.
Where a reversible stop or disable action can contain the issue, it may be preferable to immediate deletion. Microsoft advises favoring reversible operations and coordinating with owners before irreversible deletion. The right response still depends on the incident and the resource’s impact; preserving a dangerous resource is not automatically safer than removing it.
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A responsibility chart helps teams decide which controls to configure and who should operate them. It does not, by itself, determine legal liability, transfer a customer’s obligations to a provider, or amend a service contract. Microsoft expressly presents its model as illustrative governance guidance rather than a legal allocation.
For a real workload, check the terms for the specific service and the way it has been configured. Also account for the organization’s own rules on data, identity, approval, and oversight. The division can differ between two agents that appear similar if one is a provider-operated SaaS service and the other uses a customer-operated runtime or custom tool chain.
A sound operational answer is therefore specific: name the agent owner, identify the identity and permissions behind the resource action, record the cloud boundary where the resource was created, and define how the action is approved, monitored, and reversed. Then validate that arrangement against the applicable service agreement and internal obligations.
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