You create Asana tasks with AI by describing the task in chat instead of filling in a form. A connected AI agent can create the task, put it on the right board, assign a teammate, attach a link, set a due date and add a comment. Each instruction is a sentence, and the agent confirms what it did and gives you a link back to the board.

Project management is one of those areas where the tool is fine and the friction is everything around it. Opening the board, finding the right project, remembering which section, picking the assignee, pasting the link, setting the date, writing the comment. None of it is hard. All of it is enough to make you say you will do it later.

Below is a real example of that whole sequence done in chat, what the agent got right, the one moment it pushed back, and where I would be careful before letting an agent write to a board that other people depend on.

What Is AI Project Management?

AI project management is the practice of creating and updating work items in a project tool through natural language rather than through the tool's own interface. An agent with a connection to the project tool reads the request, maps it onto the right fields, performs the actions and reports back.

Dubb Agent does this for Asana. Because it is also the place your recorded video lives, the same request that creates a task can point an editor at the footage they need, which is the part that matters if your team's work product is content rather than tickets. This is a different job from the existing Chrome extension route for putting a video into Asana, where you are in Asana doing the clicking. Here you never open the board until the work is already on it.

What One Request Actually Created

Here is the request, close to how it was typed. Nothing formal about it:

The agent created the task, put it on the social board rather than marketing or ads, assigned Caleb, carried the Drive link across and kept the notes as written. Then it did something I did not ask for, which I will come back to.

Clicking the link it returned opened the task in Asana with the title at the top, Caleb on it, the due date set, the notes in the description, the Drive link in place and the comment underneath. Everything that would have taken a couple of minutes of clicking was already there.

Writing a Request That Produces a Usable Task

The quality of the task is decided entirely by the quality of the sentence. A vague request produces a vague task that somebody has to fix, which costs more than making it yourself. Six elements, and you can say them in any order.

My shortcut: say it the way you would say it to the person if they were standing there, then add the board name. That covers five of the six without thinking about it.

Follow-Up Edits: Move It, Date It, Comment on It

The part that surprised me the first time is that the conversation stays live. You do not have to get the request perfect, because you can keep amending in plain sentences and each one is another action on the same task.

In this example that was three follow-ups, each one line:

• "Move that to the To Do section." The task shifts columns.
• "Add a due date." Now it has an end point, which is the difference between a task and a note.
• "Add a comment: let me know if you need any custom b-roll footage." The comment posts on the task, so the assignee gets it in their notifications rather than in a separate message somewhere else.

That last one is worth dwelling on. The reason team communication fragments is that the context and the conversation live in different places: the task in Asana, the question in Slack, the files in Drive. Putting the offer of extra footage on the task itself means the editor reads it at the moment they are doing the work, not three days earlier when they were doing something else.

You can also edit tasks, move them between sections and perform other Asana actions the same way. It is the same mechanism each time: describe the change, the agent makes it, you get a confirmation.

Why the Agent Correcting You Is the Useful Part

Here is the moment from this example I would actually keep.

The task got created and the agent came back with a heads up: it had landed in the ideas section of the board, and did I want it moved to To Do instead? I had not mentioned a section. It noticed the gap between where the task went and where a task with an assignee, a brief and files attached obviously belongs.

That is a small thing and it is the whole difference between an agent that is useful and an agent that is a liability. An agent that silently does something approximately right creates work you discover later. An agent that tells you what it did, flags the bit it was unsure about and offers the fix is one you can actually delegate to.

The practical advice: read the confirmations. It is tempting to skim them because the task got made. The value is in the sentence after that.

Attaching Video, and What Captions Change

Because Dubb Studio is the recording side of the same platform, a Dubb video can go into the task as well, which is the natural move when the instruction is easier to show than to type. Twenty seconds of "here is what I mean by tighten it up, watch this bit" saves a paragraph and a round of revisions.

There is a second use for this that is less obvious. With closed captions, which are available on Dubb's paid plans, the agent can read the captions on the video. That means the task can be built from what you said in the recording rather than from what you typed afterwards. You talk through the brief once, and the written task comes from the talking.

I would treat that as the advanced move rather than the starting point. Get comfortable with typed requests first, then try describing a task out loud and see how close the result lands.

Dubb Agent, Asana AI and Zapier Compared

Three honest options here, and they are not really competing for the same job.

Most teams end up with two of these. Zapier for the tasks that are always the same, and a conversational agent for the ones that are never the same. Asana AI on top if you live in the board all day.

Common Mistakes and How to Avoid Them

Not naming the board. If you run several boards, the board name is the most important word in the request. Everything else the agent can infer or ask about.

Using a nickname for a teammate. Assign by the name in the workspace. "Tag the editor" works only if the agent can work out who that is, and on a team with three editors it cannot.

Writing a title instead of a brief. "Edit the clips" is a title. "Tighten these clips up if needed and add b-roll if needed" is a brief. The second one tells the editor where their judgment is allowed, which is what they actually need to know.

Skipping the link. A task pointing at nothing gets a reply asking where the files are. Paste the link in the same sentence as the request.

Not reading the confirmation. The confirmation is where the agent tells you the section it chose, the person it matched and anything ambiguous. That is the review step, and it takes four seconds.

Assuming it is a scheduled job. This is conversational and it happens when you ask. It is not the same thing as a routine that runs on its own each morning, which is a separate setup.

Before You Let an Agent Write to a Live Board

This is the part I would not skip, because a board is shared infrastructure and the failure mode is social rather than technical.

Assigning someone notifies them. Every task the agent creates with a name on it pings a real person. Test on a board only you use, or on a scratch project, before you point it at the board your team works from. Ten test tasks assigned to your editor is a bad first impression of the tool.

The agent inherits your access. It acts as you, with your permissions, which means it can reach any project you can reach. That is convenient, and it also means a misnamed board in a request could put an internal note somewhere a client guest can see it. Know which of your projects have external members in them.

Links carry their own permissions. Pasting a Drive link into a task does not grant anybody access to it. Check the sharing settings on the folder, or the assignee opens the task and hits a permission wall.

Deleting is not conversational. Creating and editing through chat is low risk because both are visible and reversible. I would still do deletions and bulk changes in Asana itself, where you can see exactly what you are about to remove.

Proof: Why This Actually Works

Based on anonymized usage patterns across Dubb accounts that connect a project tool to the agent, meaning small marketing teams, agencies and content operations rather than large engineering organizations, observed over the past year, two patterns stand out.

The first is that the tasks created conversationally are more complete than the ones those same teams create by hand. Not better written, more complete: an assignee, a brief and a link, rather than a title someone meant to fill in later. The reason appears to be that speaking a request naturally includes the context, while filling in a form invites you to skip the optional fields.

The second is where the adoption actually comes from. It is not the people who live in the project tool all day, who are already fast in it. It is the people who avoid it: the founder who briefs by voice note, the salesperson who never opens the board. For them the choice was never chat versus Asana. It was a task existing versus not existing.

Frequently Asked Questions

Can AI create tasks in Asana for me?

Yes. With an AI agent connected to your Asana workspace, you describe the task in a sentence and the agent creates it, places it on the board you named, assigns the person you named and carries across any links or notes you included. It then confirms what it did and gives you a link straight to the task, so you can check the result without hunting for it.

How do I connect Asana to an AI agent?

You authorize the connection once from the agent side, signing in to Asana and approving what the connection is allowed to do. After that the agent can act on your workspace in conversation. Read the permission screen rather than clicking through it, because the agent will be acting with your access, and your access probably covers more projects than the one you have in mind.

Can an AI agent assign a task and set a due date?

Yes, and both can be done after the fact. Assigning happens in the original request if you name the person, and a due date can be added in a follow-up message. The conversation stays attached to the task you just made, so short amendments like moving it to another section or adding a comment each work as their own one-line instruction.

What is the difference between this and Asana AI?

Asana AI works inside Asana and knows that workspace deeply, which makes it strong at summaries, smart fields and structuring projects. A connected agent works from outside and is strong at the moment before the task exists, when the work is still a thought in your head or a video you just recorded. One is for managing what is on the board, the other is for getting it onto the board.

Can I create an Asana task from a video?

You can attach a recorded video to a task, and if closed captions are enabled on a paid plan the agent can read those captions, which means a task can be built from what you said in the recording rather than typed separately. Record the brief once, then ask for the task based on it. Treat this as a step to try after you are comfortable with typed requests.

Is this safe to use on a shared team board?

It is, with two precautions. Test on a project only you can see first, because assigning a task notifies a real person and nobody wants ten test notifications. And remember the agent acts with your permissions, so it can reach every project you can reach, including any with external guests in them. Create and edit through chat freely, and do deletions in Asana where you can see what you are removing.

Try It on One Task First

I would not reorganize how your team works on the strength of a demo. What I would do is take the next task you were going to create by hand, and describe it in chat instead. One task, on a board that matters, with a real person on it. You will know inside a minute whether the sentence you wrote produced something your teammate can act on.

If it did, the second one takes ten seconds and you have quietly removed one of the small frictions that keeps work in your head instead of on the board. Dubb Agent handles the Asana side and holds your video library in the same place, which is the combination that matters if your team's output is content. There is a seven-day free trial with 25,000 AI credits and no credit card, so the cost of finding out is one task.