Company Context

Asana is a leading work management platform used by teams to plan, coordinate, and track work across projects, tasks, goals, and workflows. The company is expanding AI capabilities across surfaces like the Asana Inbox, project views, task creation flows, and Asana Intelligence to improve productivity while defending premium pricing in a competitive collaboration market.

Problem

Asana recently launched a new AI capability inside Asana Intelligence that automatically drafts project updates and recommends next steps based on task activity, blockers, and recent comments. Early data looks promising on the surface: 38% of exposed users tried the feature in their first two weeks, and AI-generated update views are high. However, only 11% of those users reused it in week 4, and PMs are debating whether the feature is creating durable workflow value or just short-term curiosity.

Leadership wants a clear recommendation on whether to invest further, reposition the feature, limit rollout, or pivot the experience to a narrower use case. Assume the feature is currently available to a subset of paid customers across mid-market and enterprise workspaces.

Deliverables

1. Define how you would distinguish real user value from novelty engagement for this Asana AI feature.
2. Identify the most important user segments and jobs-to-be-done to evaluate first.
3. Propose the qualitative and quantitative signals you would use to assess product-market fit and workflow impact.
4. Recommend what Asana should do next: scale, iterate, narrow scope, or stop investing.
5. Explain the key trade-offs in your recommendation.

Constraints

• You have one quarter to make a go/no-go recommendation for broader rollout.
• Engineering capacity is limited to one product squad; you cannot rebuild the feature from scratch.
• AI inference cost is materially higher than standard Asana actions, so sustained usage must justify margin impact.
• Enterprise customers are sensitive to trust, accuracy, and admin control over AI-generated content.