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You can build an AI-assisted email workflow in two broad ways. You can write code against a mailbox API, such as the Gmail API or the Outlook mail API in Microsoft Graph, or you can configure a managed tool that already exposes mailbox actions, such as Microsoft Copilot Workflows. In both cases AI is one processing step inside the workflow. It does not replace mailbox authorization, and it does not decide who is accountable for what gets sent. The right route depends on your mail platform, the permissions you can obtain, your governance requirements, and the actions the workflow must perform. The evidence behind this guide is strongest for Gmail and Microsoft Outlook with Microsoft 365, and other email platforms may support similar patterns through their own APIs or connectors.
What mailbox APIs give you
A mailbox API gives a program a documented way to read, organize, draft, and send mail, and in the two platforms covered here, to learn when something has changed. Those three capabilities are the foundation for any automated workflow. Everything else, including AI classification and summarization, sits on top of them.
Gmail API
Google’s Gmail API overview describes access to a Gmail mailbox after the user or administrator authorizes the application. Programs can send and organize mail programmatically. For change tracking, the overview describes push notifications delivered through Google Cloud Pub/Sub, which means your application can react to new mail without polling the mailbox on a timer. Google’s overview was last updated 2026-09-18 UTC, so check it before you design around any specific behavior.
Microsoft Graph Outlook mail API
Microsoft’s “Use the Outlook mail REST API” page, part of Microsoft Graph v1.0 documentation, covers both primary and shared mailboxes that your app is authorized to access. The documented operations include creating drafts, reading, replying, forwarding, sending, updating, and deleting messages, plus filtering and searching. Graph also supports message change notifications and incremental synchronization, so an application can process only what has changed since its last run.
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Two details matter for production code. First, Microsoft cautions that message and folder IDs can change after operations such as copy or move. Where the documented constraints fit your application, use immutable IDs so stored references remain valid. Second, build against v1.0 endpoints. Beta endpoints may change, and the documentation does not support treating them as stable for production.
Where AI fits in the pipeline
A workflow that uses AI well usually follows the same sequence whether it is coded or configured. Each stage has a clear owner and a clear failure mode.
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- Trigger. A new message arrives, a change notification fires, or a user starts the workflow manually. Notifications keep this stage event-driven rather than polling.
- Retrieve. Fetch the message, or a filtered set of messages, using the mailbox’s own search and read operations. Keep retrieval narrow. Large or broad pulls are where incomplete or slow results tend to appear.
- Process with AI. Classify, summarize, extract a request, or propose a reply. This is the only stage that uses a model. Its output is a suggestion that later stages can check.
- Decide. Apply rules you control. For example, route a billing question to a folder, or send only messages from a known sender list to automatic handling.
- Act. Create a draft, reply, send, label, or move the message. Which action you take is the most consequential design decision in the whole workflow.
- Record. Log what was processed, what the model returned, and what action was taken. Without this stage you cannot audit or debug the workflow.
Sending through the Gmail API
Google’s “Create and send email messages” documentation describes a fixed sequence for sending. It is worth knowing even if you later choose a managed tool, because it explains what any Gmail-based automation is doing underneath.
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- Construct the message as a MIME message, including headers and body content.
- Encode the complete MIME message as base64URL.
- Place the encoded string in the
rawproperty of a message resource. - Call
messages.sendto send the message immediately, or calldrafts.sendto send a draft you created earlier.
Choosing drafts.send over messages.send is a practical way to insert a human checkpoint, because the draft exists in the mailbox before anything leaves it.
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Three ways to build the workflow
Custom API workflow
A custom build is code your team owns. It can react to mailbox change notifications, retrieve or search messages, call any model you choose, and then create a draft or send a response. You control the prompts, the routing rules, the logging, and the error handling. The cost is that you also own authorization setup, token handling, notification subscriptions, retries, and monitoring. The reviewed Google and Microsoft documentation describes the mailbox capabilities but does not describe a built-in run history for code you write, so plan for your own logs from the start.
Managed workflow: Microsoft Copilot Workflows
Microsoft’s “Get started with Workflows in Microsoft Copilot” documentation describes Outlook actions for getting emails, sending an email, saving a draft email, and replying. It also documents built-in AI actions and a Copilot prompt action. A received email is the example trigger, and the page describes testing, run history, error reporting, and tenant-level access controls. For advanced scenarios or non-Microsoft services, the page points to Power Automate or partner connectors. Availability and controls depend on your Microsoft 365 settings and may change, so confirm them in your tenant before you commit to a design.
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Connected assistant: ChatGPT Outlook and Gmail connectors
OpenAI’s connector documentation lists Gmail search and read tools, and Outlook tools for listing, searching, and fetching messages, along with the scopes each connector needs. This route suits people who want an assistant to look through mail and answer questions, rather than a process that runs on its own. The ChatGPT Outlook help article, updated 2026-09-20, states that available actions depend on Microsoft permissions, workspace configuration, and the connected account. It also warns that broad searches or summaries can return incomplete results, and that attachments from shared or delegated mailboxes cannot currently be retrieved by the listed attachment actions. Treat these capabilities as product-specific and verify the current configuration before relying on them in a workflow.
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| Factor | Custom API workflow | Managed workflow (Microsoft Copilot Workflows) | Connected assistant (ChatGPT Outlook and Gmail connectors) |
|---|---|---|---|
| Who builds it | Developers, in code | Configured in Microsoft 365 | Configured by the user or admin inside ChatGPT |
| Mail platforms covered in the reviewed sources | Gmail API; Microsoft Graph Outlook mail API | Outlook within Microsoft 365 | Gmail; Outlook |
| Event triggers | Gmail push notifications via Pub/Sub; Graph message change notifications | Received email is the documented example trigger | Not stated; documented tools are search, list, read, and fetch |
| Send, draft, reply | Gmail: messages.send and drafts.send; Graph: draft, send, reply, forward |
Send an email, save a draft email, reply | Not stated in the reviewed connector documentation |
| Where AI runs | Any model you call from your code | Built-in AI actions and a Copilot prompt action | The assistant itself, during a conversation |
| Monitoring | Depends on what you build | Testing, run history, errors | Not stated |
| Governance controls | OAuth and API scopes, admin consent | Tenant-level access controls | Entra consent, workspace settings, account connection state |
Permissions and governance
Access is the first constraint, and it is set outside your workflow logic. Microsoft Graph requires the appropriate mail permissions for each operation, so confirm the exact permission names for every endpoint you call on Microsoft Learn before you request consent. The permission model also determines whether the application acts as the signed-in user (delegated) or with broader application-level access, and that choice affects who must approve it and how much mailbox scope the workflow receives. Google’s Gmail API likewise works through authorized access and documented scopes, which you should review for each feature you enable.
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For connected assistants, the chain has more links. The ChatGPT Outlook app depends on Microsoft Entra consent, the workspace configuration an administrator has set, and the state of the individual user’s account connection. A workflow can work for one user and fail for another if any link in that chain differs. Document who connected the account, which actions are enabled, and who has administrative authority over the workspace.
Shared and delegated mailboxes need separate planning. Graph supports shared mailbox access where it is authorized, but the ChatGPT Outlook documentation specifically notes that attachments from shared or delegated mailboxes cannot currently be retrieved by its listed attachment actions. If your process depends on those attachments, a custom API route or a managed workflow is the better test case.
Draft for review or send automatically
Whether a workflow should send without a person in the loop is an editorial design choice, not a technical default. The reviewed sources document both draft and send capabilities, but they do not establish that one policy is universally safer. A common pattern is to have the workflow create a draft, notify a person, and let that person send it. This keeps the model’s output reviewable and keeps accountability with a human. Automatic sending suits narrow, low-risk, well-tested categories, such as acknowledgment replies to a fixed set of request types. Choose per category rather than for the whole mailbox, and record which path each message took so that you can later review the results.
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- Choose a custom API workflow if you need Gmail or Graph behavior that is not covered by a managed tool, if you must control every prompt and routing rule, or if you can staff the authorization, notification, and monitoring work.
- Choose Microsoft Copilot Workflows if your mail is in Outlook within Microsoft 365, your needs fit the documented Outlook actions and AI actions, and your administrators want tenant-level controls and run history without building infrastructure.
- Choose a connected assistant if the goal is interactive search, reading, and summarizing for a person, rather than an automated process that runs without them.
- Check your mail platform first. The evidence reviewed here is strongest for Gmail and Outlook. Other platforms may be viable, but you would need to verify their APIs, triggers, and permission models independently.
- Check permissions before design. If you cannot obtain the scopes or consent for the actions you need, no route will work as planned.
- Decide draft or send per category, and log every run.
Limits to verify before you build
- The sources describe features, not performance. None of the reviewed documentation provides a benchmark for speed, reliability, or accuracy of AI classification, so test with your own mail volume and content.
- Cost comparisons are not established by the reviewed sources. Pricing and licensing for Microsoft 365 features, Google Cloud Pub/Sub, and AI usage should be checked directly with each provider.
- Copilot Workflows availability, tenant controls, and actions depend on Microsoft 365 configuration and may change. Confirm them in your tenant.
- Connector behavior in ChatGPT is product-specific and was last updated 2026-09-20 in OpenAI’s help article. Confirm the enabled actions and scopes before relying on them.
- Gmail and Graph documentation changes over time. Re-check the Google “Gmail API overview” (last updated 2026-09-18 UTC) and the Microsoft Learn “Use the Outlook mail REST API” page before you finalize scopes and endpoints.
Once the mailbox, permissions, and action set are settled, the rest of the design follows: a narrow trigger, a single AI step with a clear output, rules you control, and a record of every action. Start with one workflow category and expand only after the logs show it behaving as intended.
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