How our Slack integration and AI Studio automate product support intake

If you work at Asana, you probably live in Slack. Our customers do, too. That’s why the Slack integration is one of the most popular ways teams connect to Asana - both inside our own walls and across our customer base.

Over the past year, we’ve been dogfooding a new intake workflow that brings together Slack, Asana, and Asana AI Studio. The goal: help our field teams (sales, success, services, and support) get fast, reliable answers to questions about our AI Studio product without overwhelming R&D, and give product teams a clear view of what customers are asking for.

In this article, we’ll walk through how the workflow works, why it matters for Asana, and how the same pattern can help customers get more value from the Slack + Asana integration.

The challenge: Questions in Slack, answers everywhere

Before this workflow, our AI Studio team saw a familiar pattern:

• Field teams would ask questions in Slack about AI Studio, pricing and packaging, limits, and edge cases.

• Those questions would spark rich discussions, but they were hard to track. There was no guaranteed owner, no easy way to see what had already been answered, and no clear signal when a question was entirely resolved.

• The same questions kept popping up because there was no single system of record where answers could live, evolve, and be measured.

This created friction on both sides:

• Field teams had to chase down answers or re-ask questions, especially as product updates were released quickly.

• R&D and SMEs were spending too much time answering ad hoc, often repeated questions instead of focusing on roadmap progress or deals.

We needed a way to respond to urgent questions like this quickly, without overwhelming R&D, and to make accountability and triage more transparent and measurable in Asana. 

The solution: A two-way Slack–Asana intake and research workflow powered by AI Studio

To solve this, our AI Studio and Solutions teams built a primary workflow that connects a dedicated Slack channel to an Asana routing project, then layers in AI-powered triage.

Here’s how it works today:

1. A seller or CSM posts a question in Slack.

2. The question creates a task in Asana that syncs the message thread.

   • Asana automation automatically creates an Asana task in the central routing project for each new Slack message.

   • The whole Slack thread stays synced with the Asana task’s comments, so there’s always one shared conversation - no matter where people reply.

   • Under the hood, we’re using the latest rules capabilities, such as dynamic variables and the Use AI option, to keep Slack messages rich and contextual. For example, Slack messages can include key task fields (such as request type, priority, assignee, and links) plus a short AI-generated summary, so sellers scanning a channel can quickly understand what changed and whether they need to act.

3. The task enters an AI-powered triage flow in Asana.

   • The task is multi-homed into the AI Studio Inbox project, where it first lands in a Resource Check section.

   • AI Studio rules scans resources - docs, slides, internal FAQs, a project with previously answered questions, and in some cases, recent call notes - to see if there’s already a good answer.

4. If an answer exists, AI responds, and the task is tracked as “answered by AI.”

   • When AI Studio finds a match, it posts an answer as a comment on the Asana task.

   • That answer is synced back to the original Slack thread, so the requester sees a clear reply to the question.

   • The task moves to an Answered by AI section, where the requester can still choose to escalate to an SME if needed.

5. If an answer doesn’t exist, the task routes to the right SME.

   • Rules use context, such as request type, customer region, and submitting team, to route the task to the right project or SME inbox (for example, trust & security, deal desk, or specialized AI Studio support).

   • Owners and SLAs are explicit in Asana, so we can see where work sits and how quickly we’re responding.

6. The workflow listens for follow-ups and satisfaction.

   • If someone adds a new comment with more detail or a related but distinct question, AI Studio can decide to re-run the resource check or escalate to an SME.

   • Ideally, “satisfaction” means the task is marked complete based on an AI rule that reads the latest comments and determines when the question is resolved.

Why this matters for Asana’s field teams

This workflow isn’t just about showing off new features; it’s about making life meaningfully easier for the people on the front lines with customers.

For sales, success, services, and support teams, it means:

• Faster, more consistent answers. Questions asked in Slack get structured, trackable tasks in Asana. AI Studio handles the first pass by reviewing docs, FAQs, and prior SME answers, so many questions can be resolved in minutes rather than days.

• Less busywork, more selling and supporting. Reps don’t have to hunt through channels or remember who answered a similar question last month. They ask once in Slack and know there’s a workflow behind the scenes that will either answer or escalate.

• Clear ownership and expectations. Because routing and status live in Asana, it’s obvious who owns a request, what’s in progress, and what’s been answered - without trying to manage this inside Slack threads alone.

Sales leaders are already impressed at how much faster AEs can get the answers they need. They’re already hearing from AEs across regions about how impressed they are with this new workflow that delivers fast, reliable answers and clear escalation paths when needed. 

Value for R&D: Focus where humans add the most value

On the R&D side, this Slack + Asana workflow is just as important.

• Deflecting repeat questions. When AI Studio can confidently answer from existing resources, engineers and product managers don’t need to step in. Instead, they can focus on edge cases and new scenarios.

• Clear signal on what needs human attention. Only questions that truly require a human response are escalated to SMEs, and they appear in the right Asana projects with the right owners.

• A tighter feedback loop into the roadmap. Because every question and answer is stored in Asana, product teams get a searchable record of what’s confusing customers, where docs might need improvement, and which gaps could be better addressed with new product capabilities.

In other words, the workflow doesn’t just answer questions - it becomes a live voice-of-customer channel that product managers can use to prioritize what to build next.

What we’re learning as we use this workflow

Like any advanced AI-powered workflow, this setup is powerful—and a little demanding.

A few learnings from running it in our own instance:

• The Asana-side routing logic matters as much as the Slack sync. Setting up a two-way sync between Slack and Asana is straightforward. The hard part is building and maintaining the “noise filter” in Asana: defining request types, routing rules, and escalation paths so that AI and humans are working on the right things.

• AI needs good guardrails and healthy infrastructure. Minor changes to things like retrieval frameworks, document sets, or token limits can disrupt the flow. When an AI rule fails, it doesn’t just break a single task - it can slow down the entire intake queue. We’ve seen this firsthand and now monitor these workflows closely.

• AI gets you a strong first pass - humans still close the loop. In most cases, AI Studio does a great job handling the initial answer or summarizing what we know so far. But follow-ups still need a bit of “babysitting” from SMEs to confirm edge cases, refine guidance, or capture new learnings in our docs.

Dogfooding this setup means we feel those friction points ourselves, long before our customers do—and can steadily improve the underlying workflows, content, and product experience.

How this pattern helps customers get more from Slack + Asana

While this particular workflow is built around our internal AI Studio inbox, the pattern applies broadly:

• A dedicated Slack channel where questions or requests come in

• A synced Asana project that becomes the system of record

• Rules and AI that check existing resources first, then route to the right experts

• Clear signals for when work is answered, escalated, or complete

Customers can start small by turning important Slack messages into Asana tasks, using rules with dynamic variables and AI to keep stakeholders updated in Slack, and gradually layering in richer routing and AI triage.

For us at Asana, this isn’t just an experiment. It’s a way to demonstrate, in our own workflows, how powerful it can be when Slack and Asana work together with AI to keep questions accountable, keep answers fresh, and keep product teams closely connected to customer needs.