Asana is developing an AI “teammate” feature that embeds generative AI (genAI) into the flow of work for users of its work management app. The teammates — created using “trigger and action” format in Asana’s existing workflow automation tools — can perform tasks such as carrying out research and interact with co-workers to help coordinate work.
The new feature accesses information on the Asana work graph — data on the work a team does, and the people doing the work — and relies on large language models [LLMs] from the likes of Anthropic and OpenAI.
“When people think about working with AI like working with the teammate, they get better value out of it, because they’re better able to give it instructions, give it feedback, and effectively partner with it,” said Paige Costello, head of AI at Asana.
There are a variety of ways to customize a teammate, said Costello. One example (from a customer testing the feature) involves the work request process for a design team. Here, a “request triage” assistant can check an incoming work request form to determine whether it contains sufficient detail about the scope of the request. If not, the AI assistant sends a message back offering suggestions for more information to include.
That process can save back-and-forth messages between coworkers trying to get the correct information, Paige said.
Another customer — a marketing firm — set up an AI teammate to conduct research around clients. In that case, the teammate can generate a first draft brief with information on clients’ previous brand campaigns and what they’re known for.
The Asana app already has workflow automation tools, but the addition of LLMs allows for more powerful automations. “What’s really exciting about embedding LLMs into work management is that there’s judgement, there’s nuance,” said Costello. “Instead of it being a black and white rule — ‘if these things are missing, ask this’ — it’s directional, like, ‘here’s what we typically look for; use your judgment.’”
That said, given the unreliability of LLMs, there’s potential for the teammates to introduce errors into the work management process.
Costello said it’s important to have a “human in the loop,” when the AI assistant takes action. “We want to make sure that humans are the ultimate deciders,” she said. “They’re the ones that are accountable, they’re the ones completing the work: AI is just helping. AI shouldn’t be moving work forward in a way that is not permissioned effectively by the team or the person driving that work.”
The AI teammate feature could potentially be accessed by a broad range of Asana users, said Chris Marsh, research director at 451 Research, part of S&P Global Market Intelligence.
“I believe the AI teammate is designed to appeal in a general sense, in that the aim is to have the teammate enhance general team workflows,” he said, noting it could improve withaccess to more data in Asana’s work graph over time.
“It’ll inevitably be a work in progress in terms of how helpful it is from the launch, but what it does represent is AI being applied to the next tranche of use cases in work management,” Marsh said.
He expects “market interest” in the capabilities of a tool such as Asana’s AI teammate.
A recent 451 Research survey indicated that 44% of employees see “low or no impact” of AI on their workforce tools. Only 24% said AI has had a moderate impact. But when survey participants were asked about the types of technologies that could enhance how they work, the popular response was an “an AI assistant that can help with automating basic tasks and more strategic kinds of work design,” said Marsh.
“So, few are seeing AI’s impact so far, but a lot want to see it and want to see it in the form of an AI assistant to do the kinds of things Asana’s AI teammate is focused on doing,” he said.
The AI teammate feature is currently in beta trial with select customers. Asana is evaluating different pricing models with more specifics available closer to a general availability launch.
No launch date has yet been set.
Asana is developing an AI “teammate” feature that embeds generative AI (genAI) into the flow of work for users of its work management app. The teammates — created using “trigger and action” format in Asana’s existing workflow automation tools — can perform tasks such as carrying out research and interact with co-workers to help coordinate work.
The new feature accesses information on the Asana work graph — data on the work a team does, and the people doing the work — and relies on large language models [LLMs] from the likes of Anthropic and OpenAI.
“When people think about working with AI like working with the teammate, they get better value out of it, because they’re better able to give it instructions, give it feedback, and effectively partner with it,” said Paige Costello, head of AI at Asana.
There are a variety of ways to customize a teammate, said Costello. One example (from a customer testing the feature) involves the work request process for a design team. Here, a “request triage” assistant can check an incoming work request form to determine whether it contains sufficient detail about the scope of the request. If not, the AI assistant sends a message back offering suggestions for more information to include.
That process can save back-and-forth messages between coworkers trying to get the correct information, Paige said.
Another customer — a marketing firm — set up an AI teammate to conduct research around clients. In that case, the teammate can generate a first draft brief with information on clients’ previous brand campaigns and what they’re known for.
The Asana app already has workflow automation tools, but the addition of LLMs allows for more powerful automations. “What’s really exciting about embedding LLMs into work management is that there’s judgement, there’s nuance,” said Costello. “Instead of it being a black and white rule — ‘if these things are missing, ask this’ — it’s directional, like, ‘here’s what we typically look for; use your judgment.’”
That said, given the unreliability of LLMs, there’s potential for the teammates to introduce errors into the work management process.
Costello said it’s important to have a “human in the loop,” when the AI assistant takes action. “We want to make sure that humans are the ultimate deciders,” she said. “They’re the ones that are accountable, they’re the ones completing the work: AI is just helping. AI shouldn’t be moving work forward in a way that is not permissioned effectively by the team or the person driving that work.”
The AI teammate feature could potentially be accessed by a broad range of Asana users, said Chris Marsh, research director at 451 Research, part of S&P Global Market Intelligence.
“I believe the AI teammate is designed to appeal in a general sense, in that the aim is to have the teammate enhance general team workflows,” he said, noting it could improve withaccess to more data in Asana’s work graph over time.
“It’ll inevitably be a work in progress in terms of how helpful it is from the launch, but what it does represent is AI being applied to the next tranche of use cases in work management,” Marsh said.
He expects “market interest” in the capabilities of a tool such as Asana’s AI teammate.
A recent 451 Research survey indicated that 44% of employees see “low or no impact” of AI on their workforce tools. Only 24% said AI has had a moderate impact. But when survey participants were asked about the types of technologies that could enhance how they work, the popular response was an “an AI assistant that can help with automating basic tasks and more strategic kinds of work design,” said Marsh.
“So, few are seeing AI’s impact so far, but a lot want to see it and want to see it in the form of an AI assistant to do the kinds of things Asana’s AI teammate is focused on doing,” he said.
The AI teammate feature is currently in beta trial with select customers. Asana is evaluating different pricing models with more specifics available closer to a general availability launch.
No launch date has yet been set. Read More
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