The safest way to choose an AI agent platform is to trace two or three real workflows from the data the agent reads to the action it takes. For every step, identify the connector and operation, the identity used, the source-system permissions that should apply, the channel where the agent runs, and the controls that let administrators monitor or revoke access. A long integration catalog is only a starting point: it does not prove that the required action exists or that authorization is enforced when the action runs.
Shortlist platforms against that workflow map, then validate each candidate in your own tenant with a low-risk account and a deliberately denied-access case. The result should be an evidence-based decision about coverage, identity, runtime enforcement, governance, and the effort required to operate the integration—not a generic ranking by feature count.
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Why integration and permission details matter
An agent usually does more than retrieve information. It may read a customer record, create a ticket, update a deal, send a message, or call an external API. Those operations can have very different risk levels and permission requirements. A connector listed in a product catalog may support only read operations, may require a separate action, or may authenticate with a broad service account instead of the person who asked the question.
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Evaluate each integration at the operation level. Ask whether the platform supports the exact read and write actions your workflow needs, whether the connector is maintained for your edition and region, and which administrator owns both the credentials and the source-system permissions. Then determine what the platform checks when the agent actually executes the call. Configuration screens and catalog descriptions do not establish runtime behavior.
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Start with a real workflow, not a feature list
Write two or three concrete tasks
Choose representative tasks that include both information retrieval and a consequential action. For example, a support agent might read an account record, check an open case, and draft—but not send—a reply. A sales workflow might read opportunity data and create a follow-up task. Record the data involved, the requested action, the people allowed to invoke it, and the channel they will use.
| Workflow detail | What to record | Why it affects platform choice |
|---|---|---|
| Source data | System, objects or tables, fields, attachments, and sensitivity | Determines whether a native connector or a controlled custom interface is needed |
| Action | Exact operation, such as read, create, update, delete, send, or approve | Connectors often expose different permissions for different operations |
| Audience | User groups, guest users, administrators, and service processes | Determines whose identity and eligibility must be enforced |
| Channel | Teams, a web chat, an embedded application, an API, or another channel | Policy and authentication behavior can change by channel |
| Failure consequence | What happens if the call is denied, delayed, duplicated, or made with stale data | Indicates the logging, approval, retry, and rollback controls required |
Map every task to a connector and operation
Create a mapping for each workflow rather than checking whether the vendor supports a system in general. Name the connector, the specific operation, any required custom action, and the owner who will maintain it. If the required operation is absent, a platform may still be usable through a custom connector, REST tool, or MCP server, but those paths can have different identity and policy semantics.
Define the acceptable authorization result
Write down what should happen for an authorized user, an unauthorized user, a user who can see the record but cannot edit it, and a user whose access is revoked while the agent is still published. These expected outcomes become your acceptance tests. They also prevent a vague claim such as “the agent uses our permissions” from being treated as proof.
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Every candidate should answer one question unambiguously: whose identity is presented to the source system? The common models are an authenticated end user, the person who built or published the agent, or a dedicated service identity. Each can be valid, but they produce different security and operating responsibilities.
| Identity model | Questions to ask | Main risk to control |
|---|---|---|
| Authenticated user | Is the user identity passed through for every operation? Are source licenses, sharing rules, and field permissions evaluated at execution time? | The agent may fail for users who lack a required license or permission; that failure should be visible rather than bypassed |
| Maker or publisher | Does the agent run with the creator’s rights? Can a less-privileged user invoke actions that the creator can perform? | Privilege concentration and accidental delegation of the maker’s access |
| Service identity | Who owns the account, how narrowly can its actions be scoped, and how are credentials rotated and revoked? | Broad, persistent access that is difficult to attribute to an individual |
Ask whether permissions can be restricted to individual operations or whether granting a connector exposes a broad set of tools. A connector-level grant may be acceptable for a tightly isolated service account, but it is materially different from an operation-specific grant. Require the platform owner to show the actual permission object, not just a product diagram.
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Separate configuration-time permissions from runtime enforcement
Configuration determines what an agent is set up to call. Runtime enforcement determines whether a particular call is allowed when it happens. Treat these as separate controls in your evaluation.
Microsoft Copilot Studio’s documented model
Microsoft says new Copilot Studio agents automatically receive Microsoft Entra Agent IDs. Agents created before Agent ID became available in May 2026 continue to use legacy app registrations until a future migration. When an agent is published, its Agent ID receives permissions representing the Power Platform connectors configured for that agent. Depending on configuration, a scope can correspond to an entire connector or to specific operations. See Microsoft’s documentation on app registration, agent identities, and authentication for the documented behavior.
Microsoft also states that connector runtime checks revalidate whether calls comply with tenant advanced connector policies and data policies. Its concise distinction is: “In short, the scopes describe what an agent is configured to do whereas advanced connector policies and data policies decide what it’s allowed to do at the moment of execution.” A scope therefore should not be treated as a final authorization decision.
There are important boundaries to that documentation. The described Conditional Access enforcement on the agent identity currently applies only when the agent runs in Teams. Other channels continue to call connectors through the existing Power Platform connector authentication flow. Custom connectors, MCP servers, and REST API tools do not add API permissions to the Entra Agent ID in the described way. Confirm the path used by your deployment instead of generalizing the Teams behavior.
Questions for every platform
- What permission is granted when the integration is configured, and is it connector-wide or operation-specific?
- Which source-system controls are checked again at execution time?
- Which platform policies can block a call after configuration?
- Does the answer change for a custom connector, MCP server, REST tool, or non-default channel?
- What happens to an already-published agent when a user, credential, connector, or source permission is removed?
Validate the exact channel and tool path
Do not assume that a permission model demonstrated in one channel applies everywhere. Test the same operation in each channel you intend to support. Teams, a web experience, an embedded application, an API invocation, and a workflow started by another system may use different authentication flows or policy checks.
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| Deployment path | Validation questions |
|---|---|
| Teams or another first-party channel | Is Conditional Access or equivalent runtime policy applied to the agent identity? Which user token reaches the connector? |
| Custom connector | Does it add permissions to the agent identity, use a separate connection, or rely on a service credential? How are policies applied? |
| MCP server | What identity is used for each tool call? Is the server limited to approved tools and operations? Are calls logged with the invoking user? |
| REST API tool | Where are tokens stored, what scopes do they carry, and how are rate limits, retries, and revocation handled? |
| Embedded or external application | How is the user mapped to a source identity, and can a session outlive a source-system permission change? |
Include a blocked case in every channel test. A useful result is not merely a successful call; it is a clear denial with an attributable log entry when the user lacks the required permission.
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Permissions are only one part of governance. Determine who can create an agent, add a connector, publish a change, share it with users, approve a sensitive action, disable it, and delete it. The platform should let administrators limit availability to intended populations rather than relying on informal sharing.
Creation and publishing
- Can connector additions and high-risk actions require administrator approval?
- Are development, test, and production agents separated?
- Can publishing be restricted to an approved group?
- Is there a record of who changed the instructions, tools, policies, or credentials?
Sharing and eligibility
- Can access be assigned to groups, roles, or individual users?
- Are guest and external users handled differently?
- Can an administrator block a connector or connection type for the whole tenant?
- Does removing a user from a group immediately prevent invocation?
Operations and revocation
- Can administrators see successful calls, denied calls, failures, latency, and usage by agent and user?
- Can credentials be rotated without rebuilding every agent?
- Can a connection, tool, or agent be disabled and deleted cleanly?
- Are logs retained long enough for incident investigation, and do they contain sensitive payloads?
Include data-access and telemetry costs in the operating estimate. A platform can be technically suitable yet expensive or difficult to maintain if every connector requires separate credentials, monitoring, and policy ownership.
Use cross-platform administration carefully
Microsoft’s Connected platforms documentation for Agent 365 describes a way to connect supported external agent platforms and synchronize supported agents into the Microsoft 365 agent registry. The page lists Amazon Bedrock and Google Vertex AI with synchronization and observability marked supported. Salesforce Agentforce is listed with synchronization supported and observability marked “Coming soon.” The same documentation explicitly says capabilities vary by platform; it should not be read as uniform management or observability.
The connection responsibilities are split. The Agent 365 administrator manages the connection, while the source-platform administrator creates credentials, grants source permissions, and enables platform telemetry when applicable. Microsoft warns that collecting telemetry may query provider logging or data services and may incur charges from that provider. Confirm the current status and pricing before enabling collection.
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| External platform listed by Microsoft | Synchronization | Observability status in the documentation | What to verify |
|---|---|---|---|
| Amazon Bedrock | Supported | Supported | Which events are collected, retention, and provider charges |
| Google Vertex AI | Supported | Supported | Identity mapping, log access, and regional restrictions |
| Salesforce Agentforce | Supported | Coming soon | Whether observability is available in your tenant and what remains in Salesforce logs |
Read the current Connected platforms documentation during procurement because preview labels and supported capabilities can change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the documented vendor examples show
Microsoft Copilot Studio
Copilot Studio is a useful example of why identity, connector scope, channel, and runtime policy must be reviewed together. Its Entra Agent ID can receive connector-related permissions when an agent is published, yet the documented Conditional Access behavior is currently Teams-only, and custom connectors, MCP servers, and REST tools follow different paths. The right question is not whether Copilot Studio has a connector for a system; it is which operation, token, channel, and policy combination your workflow will use.
Use the identity and authentication documentation to confirm the behavior for the agent type and channel you plan to deploy. Treat the May 2026 Agent ID timeline as a version and migration consideration, not as a general market benchmark.
Salesforce Agentforce
Salesforce states that its AI agents respect standard Salesforce access controls, including licenses, permissions, field-level security, and sharing settings. Its Help documentation says, “AI agents respect standard Salesforce access controls such as licenses, permissions, field-level security, and sharing settings, so an agent always acts securely.” That is a Salesforce product statement, not an independent security audit. The same material directs administrators to inspect the permissions of the underlying custom action.
For a custom action, access depends on the underlying Apex class, flow, or prompt template. Test those implementations directly, including field visibility and record sharing, rather than assuming the agent layer will correct an overly broad action.
Salesforce also documents Agentforce agents and Prompt Builder templates as MCP tools for external assistants. Execution runs in the authenticated user’s context, with sharing rules, field-level security, and Einstein Trust Layer policies applying. This MCP path requires explicit configuration and supports only agents created with the new Agent Script Builder; legacy agents must be upgraded. Read the Agentforce MCP tools documentation and the Trust and Agentforce documentation for the supported configuration.
Build an evidence-based scorecard
Score each candidate against the actual workflow. A simple pass, conditional pass, or fail is more useful than a large feature-count spreadsheet. Record the evidence link, tenant configuration, channel tested, and owner for each answer.
| Axis | Questions to answer | Evidence to retain |
|---|---|---|
| Workflow and integration fit | Does the platform connect to every required system? Are the exact read and write actions available, supported, and maintained? Who owns credentials and source permissions? | Action-level connector documentation, configuration export, and support statement |
| Identity and scope | Does the agent act as an end user, maker, or service identity? Can access be restricted to individual operations, or does a connector grant broad tool access? | Token or connection type, scope list, and a permission-denial test |
| Runtime enforcement | Which source controls and platform policies are rechecked when an action runs? Does enforcement vary by channel or connector type? | Successful and blocked logs from each intended channel |
| Governance lifecycle | Who can create, publish, share, approve, disable, and delete agents or connections? Can availability be limited to intended users? | Role matrix, approval workflow, and revocation procedure |
| Operations and observability | Can administrators see sync status, failures, activity, and usage? Can credentials be rotated or revoked? Are data-access or telemetry charges possible? | Admin screens, retention settings, incident process, and cost owner |
| Fit and operating effort | Does the platform fit systems already in use, and can the team safely maintain connectors, policies, and agents over time? | Named owners, maintenance schedule, skills assessment, and support model |
The final axis is a buyer-specific inference, not a vendor ranking established by the documentation. A platform that passes every technical test may still be a poor choice if your team cannot maintain its connections and policies.
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Run a practical validation before purchase
- Choose representative tasks. Write two or three workflows with the data read, the exact action, the people who may invoke it, and the intended channel.
- Map the implementation. Identify the connector, operation, identity type, source permissions, platform policies, and any custom connector, MCP server, or REST tool involved.
- Ask for scope details. Have the platform owner show whether the permission is operation-specific or connector-wide and explain what happens when a source permission changes.
- Create a low-risk test tenant or account. Use non-sensitive records and a test action that can be safely reversed. Include one account that should be denied access.
- Test both success and denial. Run the same request as an authorized user, a user with partial rights, and a denied user. Repeat it in every intended channel.
- Inspect logs. Confirm that successful and blocked operations identify the agent, invoking user or service identity, connector, operation, timestamp, and error reason. Check whether payloads contain data your retention policy forbids.
- Exercise administration. Publish a controlled change, share it with a test group, rotate or revoke a credential, disable the connection, remove a user, and delete the agent. Record propagation time and residual access.
- Check lifecycle and cost assumptions. Confirm preview or coming-soon features, current licensing, connector limits, telemetry charges, log-retention costs, and support responsibilities in writing.
Common failure modes and how to correct them
| Observed problem | Likely cause | Corrective action |
|---|---|---|
| The catalog lists the system, but the required write action is missing | Catalog entry describes a connector family rather than supported operations | Check the action list and test the exact operation; use a controlled custom interface only if its identity model is acceptable |
| A user can invoke an action that only the maker should perform | The connection runs with maker or service identity | Switch to user-context execution where supported, narrow the service identity, or add an explicit approval step |
| A denied source user still receives data | Cached results, broad connector scope, or a different authentication path | Disable caching for sensitive data where possible, inspect the token and logs, and repeat the denial test in the actual channel |
| Teams behavior does not match a web or embedded channel | Channel-specific authentication or Conditional Access enforcement | Document separate controls per channel and do not advertise the Teams result as universal |
| Administrators cannot explain a blocked call | Insufficient connector, platform, or source-system telemetry | Require correlated logs and define retention and escalation ownership before production |
| Revoking a credential does not stop all activity | Multiple connections, cached tokens, or an unmanaged custom tool | Inventory every connection and token, revoke at the source, disable the agent, and verify a fresh denial |
| Cross-platform inventory shows an agent but no usable telemetry | Provider capability is limited or marked preview | Keep source-platform logging as the authoritative record and verify availability in your tenant |
Licensing, pricing, and operating effort
No reliable cross-platform price or license comparison is established here. Licensing can depend on users, messages, actions, environments, connectors, data volume, or advanced governance features. Obtain a current quote for the exact editions, channels, and environments you will operate.
Estimate the ongoing work as well as subscription cost. Assign owners for connector updates, source permission changes, credential rotation, policy review, incident response, log retention, and user eligibility. If telemetry queries a provider’s logging or data services, include any provider charges. A low-cost pilot can become expensive when every integration requires a separate service account and monitoring pipeline.
Make the selection decision
Select the platform that passes the end-to-end tests for your highest-value workflow with the least ambiguous identity and runtime behavior. Require operation-level coverage, a documented authorization model, channel-specific evidence, usable audit logs, and a practical revocation procedure. Reject a candidate when the vendor cannot explain who the agent acts as, which permissions are checked at execution time, or how administrators can stop the integration.
Then document the approved connectors, operations, identities, channels, user groups, owners, and rollback steps. Re-test after major connector, agent, identity, or channel changes. This turns platform selection into a controlled operating decision rather than a one-time integration purchase.
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