Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
Table of Contents
- What do you need before you add AI to HubSpot Service Hub?
- What are the three ways to add AI to HubSpot Service Hub?
- How do you add a third-party AI agent to HubSpot Service Hub, step by step?
- Step 1: Get the install approved, and know what the app will ask for
- Step 2: Install the agent, then connect it in the tool
- Step 3: Point it at your knowledge
- Step 4: Scope what it's allowed to see and answer
- Step 5: Run it in draft-note mode first
- Step 6: Set the human handoff, then turn on direct replies for one ticket type
- What changes if you build it yourself (Route C)?
- How do you test the AI agent before it replies to customers?
- What breaks when you add AI to HubSpot Service Hub, and how do you tell?
- What should you do next?
- FAQs
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By the end of this, a third-party AI agent is answering real HubSpot conversations, in the afternoon we'd set aside for it. Service Hub stays the system of record, and your ticket pipelines never move.
If HubSpot's own customer agent needs a plan you don't hold, or it went live and still won't answer from what you've written, a third-party AI agent can work the same Conversations inbox instead. Three routes are open: an App Marketplace install, a copilot test in draft-note mode that no customer ever sees, and a custom Conversations API build. The Marketplace install is the one most teams take, a point-and-click job wired up in an afternoon that leaves your pipelines, snippets and workflows exactly where they are.
You own the Help Desk. Over a year or two you've built ticket pipelines and statuses, saved views, a snippet library and a stack of workflows that hold the queue together.
Running a different helpdesk? We wrote this same walkthrough for Zendesk, Gorgias, Freshdesk and Intercom.
Sort one thing out today, well before step 6: getting the install approved needs a Super Admin, and in a HubSpot shop that person often sits in RevOps. An afternoon gets it wired up, then a quiet week follows before it talks to a customer.
What do you need before you add AI to HubSpot Service Hub?
TL;DR: A Super Admin to approve the install, published knowledge base articles (or historic-ticket training if you don't have them), and about an afternoon. The route most teams take is a Marketplace install, and it runs on any HubSpot plan.
- Permissions: HubSpot's rule is "Super Admin or App Marketplace access permissions are required to install apps." A Super Admin "can do virtually anything in the account", which is why nobody hands it out lightly. If yours won't, ask for the narrower switch. App Marketplace access is a per-user toggle on the Account tab of a user's permission editor, under Settings access, and it lets someone install apps without the keys to everything else (uninstalling is a separate toggle again). Both live in HubSpot's user permissions guide, and the install path is in its App Marketplace article.
- What the app actually gets: our HubSpot channel docs have the answer. "You must be a Super Admin to install an app in a HubSpot account, however the AI agent app doesn't get Super Admin rights." The only two scopes we hold are
conversations.readandconversations.write. HubSpot's own scopes reference describes those as "View details about threads in the conversations inbox." and "Send messages in conversations. Create and update message threads."
- Plan tier: HubSpot's customer agent sits behind a real gate. It needs Professional or Enterprise on one of seven HubSpot subscriptions (Marketing, Sales, Service, Data, Content or Revenue Hub, or Smart CRM), plus HubSpot Credits, plus an assigned seat, all listed on HubSpot's set-up article. A third-party route like ours runs on the Conversations API scopes, which are listed as open to any HubSpot account (yes, even a free one).
- Data prep: published knowledge base articles, which live at
Service > Knowledge Base, or historic-ticket training if you don't have those yet. None of this touches your pipelines, views, snippets, teams or workflows.
- Custom Help Desk views need their own permission: HubSpot's guide to organizing teams and views in the help desk adds a requirement: creating a custom Help Desk view needs "A Service Seat and Custom views permissions". Check it now, before you're mid-scope.
- What you can skip: rewriting the knowledge base, and auditing every workflow first. Test on what you have. If almost nothing is written down, training on historic tickets drafts your starter knowledge: ours reads 5,000+ historic tickets and generates around 20 grouped help articles, usually within six hours.
- Time: an afternoon to install and scope, then a week of watching it draft notes.
What are the three ways to add AI to HubSpot Service Hub?
TL;DR: HubSpot's own agent is the option you already have. If it sits behind a plan tier you're not on, or you ran it and it didn't land, three routes are open: an App Marketplace install, a copilot test no customer ever sees, and a custom API build.
HubSpot's own AI layer now goes by Agent Hub. HubSpot's own words: "Agent Hub (BETA) brings together HubSpot pre-built agents, custom agents, and agentic workflows in one place."
The customer-facing one you deploy to support channels is the customer agent. Breeze Assistant is the separate half that sits with your reps. Our complete guide to HubSpot's Breeze AI agent covers what it does in depth.
Route | Best for | Time to allow | Needs a developer? | Trade-off |
A. HubSpot App Marketplace install | Most teams | Give it an afternoon | No | You work inside the app's model of routing |
B. Copilot / draft-note test | Proving it before anyone sees it | Give it an hour | No | It drafts for a rep to send, so handle time drops while ticket volume holds |
C. Custom Conversations API and webhook build | Non-standard routing, or an in-house model | Give it days to weeks | Yes | You own it forever, including the 401s |
Route A is a HubSpot App Marketplace install. You pick the app, a Super Admin approves it, and the connection reads and writes your Conversations inbox. Nothing else in the account changes.
Route B is the same app, running in draft-note mode (my usual starting point). It writes a note on the conversation that your team can send, edit or bin. HubSpot's Note tab is explicit that a note "will not be visible to the contact."
Route C is a webhook into your own service, replying through the Conversations API with a private app for auth. The edges are token scopes, retries, and workflows re-firing on your AI's own reply.
If you're not sure, I'd install A, run it in draft-note mode for a week, then widen. Note mode is our default at connect time.
How do you add a third-party AI agent to HubSpot Service Hub, step by step?
TL;DR: Six steps. Get the install approved, connect the agent, feed it your knowledge, scope what it's allowed to answer, run it in draft-note mode for a week, then set the handoff and let it reply to one ticket type.
Two questions decide which agent you pick, both answerable before you install anything. Does it connect to HubSpot natively, reading and writing the Conversations inbox directly? And can it read the knowledge you already have: published knowledge base articles, snippets, and your ticket history?
Step 1: Get the install approved, and know what the app will ask for
Start this one first. Someone with Super Admin has to approve the install, so the support lead usually has to go and ask for it.
The ask itself carries the scopes we need: two of them,
conversations.read and conversations.write, and the app's rights in the account end there. If full Super Admin is a bridge too far, the App Marketplace access toggle on the Account tab of a user's permission editor is the narrower ask.You're done when you can see the Marketplace icon in your top navigation bar, or you have a named person who'll click Install for you.
Step 2: Install the agent, then connect it in the tool
Whichever third-party agent you pick, the job runs the same way. Install it from the App Marketplace, authorise the connection, and land back in the tool, which is where the real work happens.
The HubSpot half is the short half: click the Marketplace icon in the top navigation bar, select HubSpot Marketplace, find the app, then click Install. A grayed-out Install button just means it's already there.
On our side the connect flow is four clicks: Dashboard > Channels, then Add to helpdesk, then the HubSpot icon, then Connect your HubSpot account. Pick the account, confirm, and you land back in My AskAI, where every remaining setting lives.
Worth knowing before you authorise: replies go out under whichever HubSpot user made the connection. If you want the agent to carry its own name and picture, make that account first and connect with it.
Our integration works with the HubSpot Service Hub Help Desk, where your Conversations inbox already lives. You're finished here when our docs' end state is true: "Your My AskAI is now connected to HubSpot and will be providing 'note' responses, that only agents can see."
Step 3: Point it at your knowledge
Any agent is only as good as what you feed it. Order matters here. Published help articles first, then your canned responses turned into standalone answers, then your historic tickets.
Get the sequence wrong and you spend a week debugging answers that were never going to land (we've watched teams do exactly this).
Articles first, because they're already written for a customer to read. Load your published knowledge base articles into the agent, and only published ones count, so hit Publish or Update on anything still sitting in draft.
Snippets need a conversion step before they go anywhere near the AI. A snippet is a fragment written for a human to top and tail, so an AI reading one verbatim answers half a question.
Where you want the wording used word for word, load it as one of our Custom Answers. For everything else, copy the snippets out of
CRM > Snippets by hand, because HubSpot has no automated export. Then run them through an AI writing tool such as ChatGPT, using the prompt in our snippets and canned responses guide, which turns each fragment into a standalone answer.You can start with a thin knowledge base. Historic ticket training reads your past conversations and drafts the starter articles you never got round to writing. They land in Improve > Self-learning for you to edit before anything goes live.
If HubSpot's own agent is already answering, pause it on the surfaces you're handing over before your new one goes live. Two agents on one channel is the mess I see most often. This is also the only part of the walkthrough you settle inside HubSpot.
Open Service > Customer Agent, then Deploy > Channels in the left sidebar. Read the workspace column, because it splits Inbox from Help Desk. Turning one surface off is a per-row job: "To remove the agent from a channel, hover over the channel and click Remove."
The global switch sits under your account name in the top right, at Account & Billing > Usage & Limits > Credit Agent usage. I've been on calls where nobody thought to look there, though HubSpot documents it.
Know what "off" does before you flip it. HubSpot's wording: "If you turn the customer agent off, it'll continue to handle existing threads until the conversation is resolved, but won't be assigned to any new threads." Visitors also stop seeing "Powered by AI" in the live chat header, which your marketing team may notice before you do.
Pausing is the whole of your rollback, in HubSpot's set-up article: "while you can edit or pause the agent at any time, once a customer agent is created, it can't be deleted."
Step 4: Scope what it's allowed to see and answer
Every agent arrives wide open. Narrow it on day one (before habits set in). Two decisions do the job: which channels it may read, and which topics it must hand straight to a person.
Both are settings inside the agent. Ours starts on everything, as our HubSpot channel docs put it: "By default your AI agent in HubSpot will reply to messages sent to all channels in your HubSpot."
Narrow the channels at Dashboard > Channels > Add to helpdesk > HubSpot, under Configure, where live chat, email, Facebook Messenger, WhatsApp, SMS and the customer portal thread are separate picks. Running several support addresses and only want one of them answered? Name that address in AI Agent Setup and the others carry on untouched.
One HubSpot switch does need your attention here (an easy one to miss). Turning off Knowledge base search inside any chatflows at
Service > Chatflows comes before anything else, so HubSpot's own article search isn't answering over the top of your agent. Leaving it on costs you a confusing week of the wrong articles landing.
Topics are the other half, and we write those as Guidance rules. They're plain sentences, like "If the customer asks about a billing dispute, hand over to a person". Each one runs before the model answers, so a blocked category never reaches its judgment at all.
What you're scoping against is furniture you already own: ticket pipelines and statuses, saved Help Desk views, and teams. Name them in your rules, then leave them where they are. Your workflows stay as they are too.
Step 5: Run it in draft-note mode first
A new agent should draft before it sends. That's Route B: a week of real answers goes by with no customer on the other end. Ours ships that way, and our channel docs say "By default when you connect My AskAI, both will be set to note replies."
Your rep clicks the Note tab in the Reply editor (the tab they already use for each other), reads the drafted answer, and sends, edits or bins it. Nothing reaches a customer for a full week.
It's the copilot pattern.
You change it later at
Dashboard > Helpdesk & Channels > HubSpot, under Type of Replies, where chat and email are separate toggles. Leave both on notes for the week.
Step 6: Set the human handoff, then turn on direct replies for one ticket type
Before any agent replies to a customer, reaching a person has to be easy, so set the handoff before touching the reply mode. Four moments need it: the customer asks for one, the AI can't answer, the customer sounds frustrated, or the topic is one you've said a human owns.
Our escalation carries context. The AI summarizes the conversation so your rep picks up where the customer left off, and those summaries can't be switched off. It also unassigns itself and stops replying.
In HubSpot the handover is one-way. Once our agent hands a conversation over it stays with your team, and ordinary Help Desk routing takes it from there (tickets arrive unassigned, and you assign from the Ticket owner dropdown).
Then turn on direct replies for one pipeline, one view, one team, on your highest-volume lowest-risk queue. The Direct reply toggle sits at Dashboard > Channels > Add to helpdesk > HubSpot. On direct reply our agent assigns the conversation to itself, so your team's Unassigned views stay clean and nobody's stepping on anyone.
What changes if you build it yourself (Route C)?
A webhook fires into your service, and you reply with a POST to
/conversations/v3/conversations/threads/{threadId}/messages, authenticated with a private app bearer token.Three things bite. The 401 is usually a scope problem, with a second cause behind it: remove the user who created the private app and calls start failing with
USER_DOES_NOT_HAVE_PERMISSIONS.Retries are generous enough to hide a slow service from you. HubSpot retries up to 10 times over 24 hours, triggered by a connection failure, a response slower than five seconds, or any 4xx or 5xx (five seconds is a tight budget under load). And workflow re-enrollment will re-fire a rule on your own AI's reply if you let it.
WhatsApp messages can't be sent through the Conversations API at all, and HubSpot now files these pages under legacy private apps.
How do you test the AI agent before it replies to customers?
TL;DR: Replay closed tickets in draft-note mode, force a handoff, check it can't invent a policy, confirm HubSpot's agent and yours aren't both answering, and write down your first response time and CSAT before you widen it.
- Replay recently closed tickets in draft-note mode and compare each draft to what your rep sent. Pass: every material difference has a named cause. When an answer is wrong it's almost always the knowledge at fault: a source that was out of date, ambiguous, incorrect or conflicting, or a scoping gap that let a ticket through. If you can't name the cause, you haven't finished the check. Your team can trace it: open the conversation and ask our Echo why the agent gave that answer and which source it used.
- Force a handoff by asking it something your knowledge base doesn't cover. Pass: it hands over cleanly, the conversation arrives summarized, control passes to a human in the same Help Desk, and the AI doesn't reply again. Do this one on a throwaway conversation, since the handover is one-way.
- Check it can't invent a policy. Ask a question with no article behind it. Pass: it hands over or stays quiet, and never produces a policy sentence. Block the categories you can't afford to get wrong with one of our Guidance rules at the routing layer, ahead of the model's judgment.
- Check for double answers, on every surface. Raise a conversation that matches both scopes, once per row of Deploy > Channels. Pass: exactly one replies. It should be the one you chose in Step 2. A customer agent you turned off still finishes threads it already owns (HubSpot's own behavior, working as designed), so an in-flight thread is a pass. And a chat channel set up through the chatflow "Assign to Customer Agent if no users are available" beta option can't be configured from customer agent settings at all, so check that one in chatflow settings.
- Baseline first response time and CSAT before direct replies go on. Pass: the baseline exists, it's dated, and it covers a full week.
Before a customer sees an AI-written reply, all of this needs to be true. Checks 2, 3 and 4 pass on the live account, and a full week of draft notes has run with a named cause behind every binned draft. Your first response time and CSAT baselines are recorded and dated, and direct replies are on for exactly one pipeline or view.
For a sense of where this lands, our own AI resolution rate benchmark study puts the field median at 70% across 195 rated deployments spanning 38 vendors, measured through May 2026. It's an aggregate: every vendor counts its own metric differently, and the teams who publish numbers are the ones happy with them. That median comes from settled deployments, months past their launch week.
What breaks when you add AI to HubSpot Service Hub, and how do you tell?
TL;DR: Most failures trace to the scoping or the knowledge, and on HubSpot the common one is its own agent still answering on a surface nobody re-checked.
Symptom | What's actually happening | Fix |
HubSpot's agent answers first on one channel; your new agent never sees the conversation | Deploy > Channels is a per-row table, and each row is its own decision | Remove the agent from that row. If it's a chat channel set up through the chatflow beta option, it can't be configured there at all, so fix it in chatflow settings |
It answers with the wrong article on live chat, even though your knowledge is right | HubSpot's chatflow Knowledge base search is still running alongside your agent | Turn Knowledge base search off inside the chatflow at Service > Chatflows |
The install never appears | Nobody in the account has Super Admin or the App Marketplace access toggle | Get Super Admin granted under Users & Teams, or the App Marketplace access toggle granted on the Account tab of a user's permission editor |
It replies on a channel nobody meant to scope in | The connection defaults to every channel in your HubSpot | Scope it in Step 4 |
A workflow and the AI collide on the same ticket | Workflow re-enrollment re-fires the rule on the AI's own reply | Check the re-enrollment toggle on that workflow's triggers and turn it off |
A Route C build returns 401 | Token scope, or the person who created the private app has left the account | Re-check conversations.read and conversations.write, then re-create the token under a current user |
It answers from an article that's out of date | The model is quoting your published article as written | Fix the article. Ask Echo why the agent gave that answer and which source it used |
HubSpot's AI permissions are coarse. One admin on r/hubspot put it this way in May 2026:
"Because Hubspot's permissioning around AI is so non-granular, I've still got it disabled in our portal altogether due to these concerns."
What should you do next?
TL;DR: Once one ticket type holds, widen by pipeline and then by team, and fix what it couldn't answer as you go.
Widen by pipeline first, then by team. Changing one thing at a time is how you know which change moved the numbers (the only way to trust the read).
Every week, read what the AI couldn't answer and write the articles that were missing. Historic-ticket training keeps surfacing those gaps as grouped articles.
If you'd rather not wire this by hand, our HubSpot AI agent integration page is the same setup with the steps already done. That's the App Marketplace install, the knowledge sync, the note-reply default, and the handoff.
FAQs
Can I set up AI customer support without any coding?
Yes, if you take Route A. The whole job is an App Marketplace install, a knowledge sync and some scoping. Route C is the coded path, for teams with non-standard routing or an in-house model.
Do I need admin access to do this?
Someone with Super Admin has to approve the install: HubSpot's own permissions guide says Super Admin or App Marketplace access permissions are required to install apps. You don't have to be that person yourself, and the narrower App Marketplace access toggle, on the Account tab of a user's permission editor, is enough day to day. Our app takes only
conversations.read and conversations.write.Will this break my existing workflows and ticket pipelines?
No. Pipelines, statuses, views, teams and workflows carry on as they are, and the connection reads and writes conversations. Workflow re-enrollment can re-fire a rule on the AI's own reply, and once direct replies are on our agent assigns the conversation to itself, which changes what your Unassigned views show.
Do I have to turn Breeze off?
No. You decide who takes what on every surface, because Deploy > Channels is a table with one row per channel, so removing the agent from live chat leaves it live on email unless you remove that row too. Step 2 carries both paths: the per-row Remove, and the global switch that stops it everywhere at once.
A chat channel set up through the chatflow beta option is the exception, because customer agent settings can't reach it. Fix that one in chatflow settings.
Switching every channel off means existing threads finish while new ones stop. The Conversation coverage field splits the work between them, at whatever percentage you set for the customer agent.
Can I roll it back?
Our app uninstalls at
Integrations > Connected Apps, then Actions, then Uninstall, which needs the App Marketplace Uninstall access permission.HubSpot's customer agent cannot be removed once it exists. HubSpot's wording: "while you can edit or pause the agent at any time, once a customer agent is created, it can't be deleted." A custom agent built in the agent builder is a different object, and that one can be deleted permanently.
Does this cost anything on my current plan?
HubSpot's own customer agent needs Professional or Enterprise on one of seven HubSpot subscriptions (Marketing, Sales, Service, Data, Content or Revenue Hub, or Smart CRM), plus HubSpot Credits, plus an assigned seat, so check that gate before you plan around it. The third-party route runs on the Conversations API scopes, which are listed as open to any HubSpot account, so the App Marketplace install works regardless of your HubSpot tier. For the numbers on either route, our HubSpot Breeze AI pricing guide has them.
