UpTrajectory Review

Google Drive's new Projects feature addresses a practical pain point for businesses using Gemini AI: the slowdown that occurs when the AI assistant scans your entire Drive library to answer questions. Instead of having Gemini search through every file you've accumulated—documents, spreadsheets, presentations, and media—you can now create a Project, attach only the relevant files and Workspace content (Gmail threads, Calendar events, Chat conversations, Keep notes, Tasks), and prompt Gemini to work within that focused context. The premise is straightforward: less noise in, faster and more relevant answers out. For businesses that have been using Workspace for years and have sprawling Drive libraries, this is a meaningful quality-of-life improvement.

For a small-business operator, this matters because time spent waiting on AI—or worse, getting generic answers because the AI is pulling from irrelevant files—is time not spent on actual work. If you're asking Gemini to summarize your Q3 budget, you don't want it factoring in a co-worker's vacation photos or last year's marketing deck. Projects lets you curate the context, which means the AI's output should be more actionable and less prone to hallucination from tangential data. It also makes Gemini more useful for recurring workflows: create a Project for your monthly financial review, attach the relevant spreadsheets and email threads, and you've got a repeatable process instead of starting from scratch each time.

What's genuinely new here is the shift from AI as a generalist to AI as a specialist within your own data. Google is essentially acknowledging that 'analyze everything' is a flawed approach for business users, and that curation beats volume when it comes to AI accuracy. The comparison to NotebookLM is apt—both tools let you define the corpus before asking questions—but Projects integrates that logic directly into Drive, where your files already live. We're skeptical of one thing: the feature's reliance on users to manually attach files and keep Projects updated. If you're not disciplined about adding new documents to the right Project, you risk missing recent data in your analysis.

Second-order effects: this could change how teams organize their Drive libraries. If Projects becomes the primary way people interact with AI, there may be pressure to structure folders and files with AI-readiness in mind, not just human navigation. That could benefit businesses that are already organized, but penalize those with chaotic file structures. There's also a cost consideration: Gemini access requires a Workspace plan that includes it, which may not be the tier your business is on. And while Projects speeds up AI analysis, it doesn't solve the underlying storage bloat problem—if your Drive is full, you're still paying for space, AI or not.

What to watch: whether Google expands Projects to support automated file suggestions (e.g., 'these three new documents look relevant to your Budget Project—add them?') or integrates it more deeply with Gemini's agentic capabilities. For now, if your Workspace plan includes Gemini, the actionable step is to identify one recurring analysis task—monthly reporting, client onboarding, project retrospectives—and build a Project around it. Test whether the focused context actually improves speed and relevance compared to a general Drive-wide query. If it does, that's your proof of concept for rolling it out to other workflows.

“When you chat with Gemini within this Project, it will analyze only the materials attached to the Project.” — Computerworld

Takeaway: Use Drive Projects to give Gemini a focused file set for recurring analysis tasks—curated context beats full-library scans for speed and relevance.