Sep 25, 2025

Asana targets collaboration, not automation, as its AI teammates launch in beta SHARE Work management company Asana Inc. has spent over a year developing its long-awaited “AI Teammates” that promise to dramatically accelerate the productivity of enterprise workers, and they’re finally rolling out in beta test. In an announcement today, Asana said that its artificial intelligence-based teammates come with a deep contextual understanding of each employee’s work processes to enable a level of collaboration that was previously unattainable. Along with their contextual abilities, the teammates also boast reliable memories that enable them to adapt and continuously improve over time, the company said. The company sells a popular work management platform used by thousands of enterprises to organize work-related tasks within a centralized dashboard. The main benefit is that it improves coordination among teams, so users can collaborate more easily and prioritize their most important tasks. The AI teammates leverage generative AI to engage with employees in a conversational way, so they can collaborate on work in the same fashion as their human colleagues do. As an example, Asana said they can help by advising workers on their most urgent priorities and generate workflows so they can complete these tasks more efficiently. Alternatively, they can perform many tasks themselves, eliminating the “mundane drudgery” that’s associated with lots of enterprise work. Collaboration, not automation The company isn’t the first to try and accelerate productivity with AI agents, but it argues that most earlier efforts at agentic automation have failed to hit the mark. It cites a study by Carnegie Mellon University published this month, which found that 70% of AI agents in the wild today fail at basic tasks. Asana Chief Executive Dan Rogers says other AI agents fail because they’re trying to automate too much. Rather than automate, he believes that the goal should always be to collaborate. “Everyone is building autonomous agents, but autonomy is the wrong goal,” he argued. In order to help AI agents collaborate effectively, it’s necessary for them to have the proper context, checkpoints and controls in place. Asana says that’s essential so they know what they’re supposed to do, how to do it in line with the company’s standards, and learn from their interactions with human workers. That’s why Asana’s AI teammates are closely intertwined with the company’s Work Graph, which is a proprietary data model that captures historical relationships and context across all workflows and teams within organizations. By feeding this information to its AI Teammates, the Work Graph gives them a more holistic view of what each employee or team needs when it comes asking it for help. Asana says this approach differs from other AI agents, which can only try to obtain the necessary context by trawling through vast oceans of company data each time they’re assigned a task. Rogers explained that enterprise workflows span numerous teams, multiple data points and impact all levels of an organization. “Enterprise work is highly nuanced, and agents can only collaborate with humans if they have access to the company’s operational framework, which shows them who is doing what by when, how and why,” he said. “Our Work Graph model provides exactly that.” Another advantage of the Work Graph is that it can be used by administrators to control how the AI teammates access company data and consume resources, ensuring sensitive data remains secure and keeping costs predictable. Tailor-made for every task Asana said its AI teammates are extremely adaptable and can be geared towards very specific roles, such as product launches, strategic planning, resource planning, onboarding new hires, marketing and so on. Human workers can call up their AI teammates at any moment through a new chat interface that’s integrated with the Asana work management platform, and they will immediately have full context of what that person is working on. So, if a senior executive pulls up a teammate and ask “What do you think might impede this goal and put it at risk?” it will immediately understand what the question refers to, and generate an appropriate response. Offering some examples, Asana said an advertising worker can ask the AI teammate to triage incoming requests to identify missing assets and proactively gather them, and then intelligently assign work to specific designers based on skillsets and their current workload. Alternatively, it might assist with after-action reports on key metrics, reducing the manual paperwork for its human counterpart and providing rich insights into the impact of different ad campaigns. The AI teammates can also assist information technology support teams by handling IT tickets, categorizing them depending on their severity and the nature of the problem users have. In some cases it might be able to troubleshoot problems itself, while in others it will hand the ticket over to the human who’s best qualified to resolve it. It can also help identify patterns and trends relating to recurring problems and update the company’s knowledge base. Asana said the AI teammates build upon last year’s launch of the Asana AI studio , which is a conversational platform that anyone can use to create their own AI agents . It provides tools for embedding these agents into workflow anywhere within the Asana platform. Because everything can be done with natural language commands, it makes AI agent creation accessible to every worker. Teammates are trending Ultimately, Asana believes that every human employee should start working with AI teammates. “The organizations that master human and AI collaboration, rather than chasing autonomy, will be the ones that pull ahead,” Rogers said. “They’ll move faster, achieve more ambitious goals and create competitive advantages that are hard to replicate.” It remains to be seen if Asana will be at the forefront of this push, for the concept of AI teammates has caught on at dozens of software companies, many of which have different ideas of how AI and humans ought to collaborate. Examples include Atlassian Corp. Plc.’s Rovo , an AI assistant that adapts to each worker and allows them to create smart agents adapted to specific tasks, and Salesforce Inc.’s Einstein Copilot , a customizable AI assistant that works alongside employees using company data to complete complex workflows. There is also a host of startups focused specifically on AI teammates. Last month, a company called InstaLILY Inc. raised $25 million in funding to build “industry vertical-specific AI teammates” that can be integrated with third-party legacy software. Meanwhile, Pipedrive Inc. is developing AI teammates for sales teams that focus on “grunt work” such as research, summarizing long-winded reports, writing emails and examining schedules. Images: Asana A message from John Furrier, co-founder of SiliconANGLE: Support our mission to keep content open and free by engaging with theCUBE community. 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