Asana AI Studio Explained: Features, Use Cases, and Setup
If youâve used Asana rules before, you know theyâre great for automation but not really for decision-making.
Asana AI Studio changes that. You can now build workflows that rename tasks based on their content, flag missing details, summarize long updates, or even decide who a task should go to, all with simple, natural-language instructions.
Weâve been using AI Studio at Cirface since its beta, and have compiled all what we learned about this new addition in this quick guide.Â
What is Asana AI Studio?
AI Studio is a no-code feature inside Asana that lets you build smarter workflows that go beyond simple automation. Instead of just moving a task or assigning it to someone, you can now add an AI step that actually thinks based on the context of the work.
Weâve been using AI Study to streamline a lot of the messy and repetitive work such as naming tasks when a form is submitted and checking for missing information. You write a short prompt, like you would in ChatGPT, but it runs automatically as part of a rule inside your project.
âAI Studio is like rules on steroids. It lets you take the kind of logic you already use in Asana and layer intelligence on top without needing to code anything.â
What I like about it is this: itâs not some separate AI tool. Itâs built right into the Asana workflows youâre already using. You donât need to code anything. And you can design it around how your team actually works.
Itâs a simple way to take the manual tasks off your plate so your team can stay focused and keep things moving.
How AI Studio Works
AI Studio builds on the same rule system youâre already using in Asana, but adds one smart layer in the middle.
You still start with a trigger such as âWhen a new task is added to this project.â But now, before jumping straight to the action, you can insert an AI step. Thatâs where intelligence comes in.
Letâs say youâre using the prebuilt Check for Duplicates rule. When someone submits a task, AI scans your project for anything that looks similar, like maybe itâs the same request phrased a little differently. If it finds a match, it drops a comment with a link to the duplicate.Â
Whatâs happening behind the scenes is this:
Trigger fires: A task is created, updated, or moved (whatever event youâve set.)
AI runs your instructions: The AI reads the taskâs details, any comments or fields youâve scoped in, and follows the instructions youâve written like âIf this task looks similar to anything else in the project, drop a comment with links.â
Action happens: The AI output then drives the next step. That could be renaming the task, filling a field, posting a comment, or moving it to another section just like a normal rule, but smarter.
Activity gets logged: Youâll see exactly what happened in the taskâs activity feed to learn when the rule ran and what the AI did.
Optional human review: We always advocate for human oversight when it comes to working with AI so we recommend you build in approval steps for a person to check the AIâs output before it moves forward.
AI Studio Pricing Explained
Asana AI Studio is available in three pricing tiers to match the level of complexity and scale your team needs. Here's how each one works:
Basic (included with Starter+ plans)
Basic is best for teams just starting to explore AI-powered automation. Itâs included with all non-legacy Starter+ plans and gives you a limited number of credits to experiment with simple, routine workflows like auto-naming tasks or flagging missing fields. This tier is ideal if you want to validate a specific use case before investing more heavily in AI automation. It's suitable for teams of any size working within low monthly usage limits.
Ideal for teams just exploring AI in their workflows
Includes a pre-set credit limit per user
Access to core AI Studio features like web search and compliance
No additional cost
Plus (includes 100K monthly credits)
The Plus tier is designed for individuals and small teams who are ready to adopt production-ready workflows. It supports more advanced use cases and provides a metered approach to scale up automation over time. With 100,000 credits per month and a cost of $1.35 per 1,000 credits, it's a solid option for teams under 1,000 employees who expect moderate AI Studio usage, typically under 1M credits per month.
Best for small teams looking to scale productivity
Includes 100,000 credits per month
$1.35 per 1,000 credits
Access to web search, link previews, and onboarding support through Asana-certified service partners (FSPs)
Pro (includes 5M quarterly credits)
Pro is built for large teams running high-volume or complex workflows across departments. This tier is optimized for enterprise-scale operations and includes advanced billing controls, onboarding services, and access to usage monitoring. Youâll get 5 million credits per quarter (plus the option to purchase 2.5M more for $499), making it ideal for companies with 1,000+ employees or those automating across multiple teams and systems. Itâs the best fit if your team regularly consumes over 1 million credits per month and needs robust governance.
Designed for large, complex workflows across organizations
Includes 5 million credits per quarter
$1.00 per 1,000 credits
Additional 2.5 million credits available for $499
Includes advanced billing controls and full onboarding services through FSPs
We recommend choosing your plan based on how your team actually works, not just company size. Consider the volume of inputs, frequency of rule runs, and level of AI support youâll need before selecting a tier.
How Asana AI Studio Credits Work (and How Not to Burn Through Them)
When we first started testing AI Studio, one of the biggest questions we had was how much will this actually cost us to run?
The short answer: it depends on how complex your prompts are, how often your rules run, and which model you use.
Each time an AI-powered rule runs, it consumes credits. And while the system handles most of the backend complexity, hereâs what actually affects your usage:
Model size: GPT-4o and Claude Sonnet are more powerful, but also more âexpensiveâ than lighter options like GPT-4o Mini or Claude Haiku.
Input volume: The more fields, comments, or linked tasks you feed into the rule, the more tokens it needs to process.
Output size: Â Asking it to generate a 2-sentence status update will cost less than drafting a full creative brief.
Frequency: A rule that runs 5x a week costs far less than one that triggers every time a task is created.
âThink of AI models like cars. Credits are your fuel, and the more powerful the model, the more fuel it burns. Claude 3.5 Sonnet for example, thatâs your luxury Maserati. Itâs fast, high-performing, but not always necessary. Most of the time, a compact model like Claude Haiku or GPT-4o Mini gets the job done just fine and uses a lot less fuel. â
Real Credit Usage Examples
AI Intake Rule (e.g. rename task, check missing fields): ~1,200â2,200 credits
Brief Drafting Rule: ~300â500 credits
So if you're using 38â40 AI-powered rules a day, every day, for a quarter youâll just start to hit the 5 million credit cap that comes with the Pro tier.
Most teams we work with donât even come close.
Tips to Use Credit Efficiently
Start with Mini or Haiku models before upgrading because often than not theyâre good enough.
Keep prompts tight. The UI flags you when your instructions are too long.
Limit the scope by using task description + key fields only.
Pilot new rules in a sandbox project to monitor usage first.
Bottom line: You donât need to worry about hitting limits if your rules are well-designed. AI Studio gives you flexibility but being intentional is what makes it scalable.
The âUse AIâ Variable
One of the most powerful things about AI Studio (and what makes it feel like a real assistant) is something called the âUse AâI variable.
Now, this isnât your typical variable like {Task Name} or {Assignee}. Those only pull existing data from the task. âUse AIâ, on the other hand, actually generates new content or makes a decision based on your instructions. Itâs as if you telling Asana to âfigure it out.â
What does âUse AIâ do?
Letâs say youâre building a rule that posts a comment when a task is submitted. Normally, youâd just drop in a canned response or pull a field. But with Use AI, you can say:
âSummarize the task description in two bullet points and highlight any deadlines mentioned.â
Now instead of a static comment, you get a dynamic summary written by the AI based on the real content of the task.Â
Where to use âUse AIâ
Youâll find Use AI anywhere youâre setting a value:
Task description
Comments
Assignees
Custom fields (like Priority or Approval Status)
Section moves
Due dates
Even when creating subtasks or approvals
Just select âUse AIâ as the value and youâll see a box open up where you can write the instructions.
Standard variable vs. Use AI (and how to mix them)
Hereâs the difference:
Standard variable â only pulls info
Use AI variable â reads context and generates a new response
And yes, you can combine both. Example:
âUsing the taskâs {Custom Field: Request Type} and the description, classify this as Urgent or Normal and give a one-line reason.â
The field is pulled in, but the reasoning comes from the AI. Thatâs how AI-powered rules work in a nutshell.Â
Use cases that work really well
Here are a few ways weâve seen teams use the Use AI variable effectively:
Smart routing: AI reads the request and assigns it to Legal if it mentions âcontract,â or to IT if it says âbug.â
Auto-commenting: When a task is marked âDone,â AI drops a note summarizing what was completed.
Content drafting: Use AI to generate a first draft of an email or a project brief based on form inputs.
Quality checks: When a task moves to âIn Review,â AI checks if the description is complete and pings the assignee if somethingâs missing.
3 AI Studio Rules to Build First
If youâre just getting started with Asana AI Studio, donât overthink it. Start small, start useful, and start with things your team touches daily.Â
 When you click into âRulesâ under the Customize menu in any Asana project, youâll now see a growing list of preconfigured AI rules including smart task naming, form validation, and status summaries. These templates make it easy to get started without writing your own prompts from zero.
1. Smart Task Naming on Form Intake
This AI-powered rule renames tasks when a form is submitted using key form fields (like campaign name + due date). While this doesnât seem too important, itâs much needed to avoid âUntitled creative requestâ cluttering your project. It enforces naming standards without needing to train your team.
Bonus: Add a second AI step to set priority or request type based on form responses.
Credit impact: ~1,200â2,200 credits per run
Great for: Marketing or creative request queues, IT support desks, intake-heavy teams
2. Missing Info Checker (with Comment Reply)
This rule checks new tasks for missing or vague information, like empty fields or unclear descriptions, and automatically posts a clarifying comment. It saves project managers from chasing people down and keeps work from stalling at the intake stage.
Credit impact: ~1,500â2,000 credits per run
Great for: Teams struggling with incomplete briefs, project managers tired of chasing details
3. Check for Duplicated Tasks
AI Studio automatically and without prompting finds duplicate tasks in your project and notifies you. AI leaves a comment in the task with links to its duplicate so that you can easily merge the tasks. Itâs a simple concept, but one that could save your team hours of rework and miscommunication, especially in fast-moving projects where requests pile up quickly.
Credit impact: ~300â600 credits per run
Great for: Cross-functional projects, intake boards, teams managing high volumes of requests
Donât build 10 rules at once. Start with one, test it in a duplicate project, and share results with your team. Once they see the time savings, adoption becomes easy.
Get Started With AI Studio Today
1. Make sure AI Studio is enabled
If youâre on Advanced (annual), Enterprise, or Enterprise+, an admin needs to enable AI Studio from the admin console. Itâs just a toggle. Once itâs on, members in your org will be able to access AI actions inside the rule builder.
2. Pick a project to test
Open the project where you want to add your rule. This could be a real workflow (like your creative requests board) or just a scratch project to play around.
Either way, you need to have edit access to the project to create rules.
3. Open the rule builder
Click Customize and then scroll down to Rules, and hit + Add Rule.
In the gallery, youâll see the option âCreate with AI Studio.â Click that to start building your first Smart Workflow. If you want to use one of Asanaâs pre-built rules instead (like Smart Task Naming or Missing Info Checker), scroll to the đź icons and choose one of those. You can always customize the prompt later.
4. Set the trigger
This is the âwhenâ that kicks off your rule.
Some examples:
Task added to project â great for intake rules
Status field changes to X â good for summaries or routing
Task moves to a section â helpful for quality checks or approvals
Pick whatever fits the moment you want AI to step in.
5. Add an action with Use AI
Choose what you want the rule to do like adding a comment or renaming a task, and then select Use AI as the value. Once you do that, an instruction box will appear where youâll write what the AI should do.
6. Write your prompt
Keep it simple and clear. Youâre just telling the AI what you want it to output.
Some examples:
Smart Task Naming:
âUse the task description to create a clear, concise title. Include the request type and subject. Avoid using âForm response.ââMissing Info Checker:
âCheck if the task has a description, due date, and dependencies. If anythingâs missing, post a comment listing whatâs missing.â
The clearer you are, the better your results.
8. Test it
Trigger the rule! Add a test task and see what happens.
Did the AI rename the task? Add a smart comment? If not, check the taskâs activity feed to confirm the rule ran. If it didnât work how you expected, no problem. Go back, tweak the prompt, and try again.
And thatâs it.
Youâve just shipped your first smart workflow and saved your team from another repetitive task.