Google Docs AI Roadmap: What to Build First So Remote Teams Get More Done

You are a product manager on Google Docs, the collaborative document editor in Google Workspace. Remote teams, whose members often work from different locations and time zones, rely on shared documents to write, review and reach decisions. Decide which AI-driven features Docs should prioritize to make these teams more productive: explain how you would choose, which features you would build first, and how you would measure the result. ```hint Start from the remote workflow, not the model List the places where distributed teams lose time around a document, such as waiting on a colleague in another time zone or reading back through a long comment history. Judge each AI idea by which of those losses it removes and how much harm it does when it gets something wrong. ``` ### Clarifying Questions - Which remote-team workflows should the answer focus on: drafting documents, reviewing and commenting, or turning meetings and discussions into written decisions? - Is the target a business customer whose administrators control which AI features are switched on, or individual users as well? - Should the plan build on the AI writing and summarizing help Docs already offers, or treat the AI feature set as starting from scratch? - How should productivity be judged: time saved per person, faster decisions for the team, or fewer meetings? ### What a Strong Answer Covers - A clear definition of productivity for a distributed team, with a chosen segment and workflow to focus on - Pain points specific to remote, asynchronous document work rather than generic writing help - A set of AI feature candidates ranked with explicit criteria, including the cost of an AI mistake and whether Docs has an advantage over a general-purpose chatbot - Success metrics measured at the team level, with guardrails for accuracy, document permissions, privacy and cost - Enterprise concerns such as administrator controls and data governance ### Follow-up Questions - How would you run an experiment when a feature's benefit depends on everyone in a team having it? - What would you do if people trusted AI summaries so much that they stopped reading the documents they approve? - How would your priorities change for a team that collaborates across several languages?