Asana CEO uses AI agents to manage workflow and monitor operations

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Asana CEO uses AI agents

Highlights

Asana CEO Dustin Rogers deploys multiple internal AI agents for inbox triage, calendar review, meeting transcript analysis, and operational decision support throughout his workflow.
Custom AI agents analyze sales questions, customer signals, renewal delays, and engineering capacity, automating key business reporting and identifying accounts or tasks requiring executive intervention.
A competitor-monitoring AI agent tracks rival product releases and social media, sharing actionable intelligence with product leadership and contributing to resource allocation and product development planning.

How Asana deploys agents in executive workflows

As reported by Business Insider, Rogers uses a group of AI agents throughout his workday to handle priorities ranging from inbox triage and calendar review to sales questions, customer signals and engineering planning.

Three of the tools act as what he calls personal productivity teammates. One reviews his Gmail inbox for messages needing immediate action, another checks whether his calendar matches his stated priorities, and a third scans meeting transcripts for new commitments and task updates. Rogers says that setup helps him spend time according to strategic priorities rather than reacting to whatever arrives first.

Other agents support broader operating decisions. A customer-focused tool reviews Asana's database for renewal delays, complaints and online requests, helping Rogers decide which accounts may need attention before issues escalate. A sales-support agent, built by Asana's sales team, draws on internal documentation and training materials to answer staff questions, while also showing management where employees are struggling to understand topics such as new pricing models.

The company also uses an internal business-analysis agent that pulls information from internal systems into reports and dashboards covering sales performance and new-customer progress. Rogers says that reduces the need to request the same information from finance or business intelligence teams, although access and actions are limited because the data is sensitive.

Implications for software operations and competition

Rogers describes work-focused agents as different from consumer AI assistants because they are built to understand institutional knowledge, coordinate across systems and handle confidential information more safely. He also says the tools are not plug-and-play, noting that a competitor-monitoring agent only became useful after he refined its instructions to filter out irrelevant alerts.

That competitive-intelligence tool now tracks rival software companies, including product announcements and social media discussion, and prepares daily briefings that Rogers reviews every few days. It also exchanges information with another agent used by Asana's chief product officer so the company can compare competitors' new features with Asana's existing and planned products, and flag changes that could affect the product road map.

Rogers also relies on an engineering-capacity agent to help decide how development talent is assigned across products and features. The tool can identify smaller tasks for engineers between releases and help estimate when customer-requested features may be built, showing how AI agents are moving from administrative assistance into resource allocation and operating oversight inside enterprise software companies.

In our earlier article on the KPMG U.S. CEO survey on AI agents, we reported that many large companies are seeing efficiency and growth gains, but only a small share of executives view agents as transformational so far. The survey also highlighted that adoption typically requires process redesign, better data readiness, and continued investment in AI infrastructure and talent—often alongside hiring and retraining rather than headcount cuts.

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