Every agent · Workflow automation and internal agents · Microsoft

Microsoft Copilot Studio

Q: What can Microsoft Copilot Studio act on?

Executes autonomously. A low-code builder for agents that answer questions and take actions through Power Platform connectors, often published to Teams or a website by someone outside IT. Each agent is only as safe as its connector permissions and its publishing scope.

Q: Is a human in the loop with Microsoft Copilot Studio, and does data leave the tenant?

Human in the loop by default: configurable. Data leaves the tenant by default: configurable. It executes on its own, so it needs the controls of an account that acts: a log you can read, a scope in writing, and a person who can switch it off. Whether data leaves your tenant depends on how it is deployed.

A low-code builder for agents that answer questions and take actions through Power Platform connectors, often published to Teams or a website by someone outside IT. Each agent is only as safe as its connector permissions and its publishing scope.

executes autonomously

acts on

configurable

human in the loop by default

configurable

data leaves the tenant by default

Whatever connectors the maker adds: SharePoint, Dataverse, Salesforce, ServiceNow, HTTP, and the channels it is published to

reaches by default

What that means for the register

It executes on its own, so it needs the controls of an account that acts: a log you can read, a scope in writing, and a person who can switch it off. Whether data leaves your tenant depends on how it is deployed. Pasted with only its name it lands as control until an owner is named.

This week

Pull the list of agents from the Power Platform admin centre, with owner, connectors and channels, and review any published externally.

What holding it is evidence for

Requirement text and artefacts from a human-verified corpus licensed to Agent Register.

Agents that execute without approval ISO 42001 A.6.2.6 · ISO 42001 A.9.4 · ISO 42001 A.6.2.8 · EU AI Act Art.14 · EU AI Act Art.26 · EU AI Act Art.12

ISO 42001 A.6.2.6 AI system operation and monitoring

AI systems shall be operated and monitored according to organizational and operational requirements throughout their lifetime. Operational guidance shall be available to operators.

Evidence an auditor accepts: Operations runbooks; Monitoring dashboards; Incident logs

ISO 42001 A.9.4 Intended use of the AI system

The organization shall ensure that the AI system is used according to the intended uses of the AI system and its accompanying documentation.

Evidence an auditor accepts: Intended use statements; Use case approval records; Monitoring of use

ISO 42001 A.6.2.8 AI system event logging

Event logs shall be generated and recorded during AI system operations to enable monitoring, accountability, and incident investigation.

Evidence an auditor accepts: Logging standards; Log samples; Log retention policy

EU AI Act Art.14 Human oversight

High-risk AI systems shall be designed and developed in such a way that they can be effectively overseen by natural persons during the period in which they are in use. Oversight measures shall enable persons to understand the relevant capacities and limitations and monitor operation, remain aware of...

Evidence an auditor accepts: Human-oversight design (UI, controls, alerts); Oversight-personnel training and authority

EU AI Act Art.26 Obligations of deployers of high-risk AI systems

Deployers shall use high-risk AI systems in accordance with the IFU; assign human oversight to appropriately competent natural persons; ensure input data is relevant and sufficiently representative; monitor operation and inform the provider of risks/incidents; retain automatically generated logs for...

Evidence an auditor accepts: Deployer monitoring records; Logs retained at least 6 months; DPIA where applicable

EU AI Act Art.12 Record-keeping (logs)

High-risk AI systems shall technically allow for the automatic recording of events (logs) over the lifetime of the system, ensuring a level of traceability appropriate to the intended purpose; logging capabilities for biometric remote-identification AI systems include the period of each use, the ref...

Evidence an auditor accepts: Logging capability design evidence; Log-retention policy aligned with the intended purpose

Broad system reach or write access to a system of record ISO 42001 A.4.4 · ISO 42001 A.4.5 · ISO 42001 A.6.2.5 · ISO 42001 A.5.2 · EU AI Act Art.15 · EU AI Act Art.9

ISO 42001 A.4.4 Tooling resources

The organization shall document information about the tooling resources utilized for the AI system.

Evidence an auditor accepts: Tooling inventory; Tool risk assessments; Development frameworks, libraries, MLOps platforms

ISO 42001 A.4.5 System and computing resources

The organization shall document information about the system and computing resources utilized.

Evidence an auditor accepts: Infrastructure inventory; Capacity plans; Compute (CPU/GPU), storage, network resources

ISO 42001 A.6.2.5 AI system deployment

The organization shall document a deployment plan and ensure requirements are met before deployment.

Evidence an auditor accepts: Deployment plans; Go-live checklists; Approval records

ISO 42001 A.5.2 AI system impact assessment process

The organization shall establish a process to assess the potential consequences of the AI system for individuals or groups and societies.

Evidence an auditor accepts: AI impact assessment procedure; Assessment template; Methodology covering individuals, groups, societies

EU AI Act Art.15 Accuracy, robustness and cybersecurity

High-risk AI systems shall be designed and developed in such a way that they achieve an appropriate level of accuracy, robustness, and cybersecurity, and shall perform consistently in those respects throughout their lifecycle. Resilience to errors, faults and inconsistencies; protection against atte...

Evidence an auditor accepts: Accuracy/robustness measurements relevant to the intended purpose; Adversarial/data-poisoning threat modelling and mitigation; Cybersecurity controls aligned with state-of-the-art

EU AI Act Art.9 Risk management system

Providers shall establish, implement, document and maintain a risk management system as a continuous iterative process planned and run throughout the entire lifecycle of a high-risk AI system, including identification and analysis of known and reasonably foreseeable risks, estimation/evaluation of r...

Evidence an auditor accepts: Risk management system documentation; Lifecycle risk analysis records; Post-deployment risk monitoring

Do this for every tool your teams use

Paste the list and get this classification for every entry at once, with the owner column, the findings per department, and the controls the register is evidence for. Ten entries free, no account.

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