Google’s AI note-taking app now allows you to interact with books
Google’s AI note-taking app, Gemini Notebook, has quietly crossed a significant threshold: it can now read the books you own. With the rollout of its "Expert Intelligence" feature, the tool allows users to import titles purchased through Google Play Books directly into their notebooks. Once imported, those texts become active knowledge bases—queryable, summable, and remixable into new formats like study guides, project plans, infographics, and even AI-generated podcasts.
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For professionals drowning in unread PDFs and half-finished business books, the shift is practical. It moves AI from a general-purpose chatbot toward a personalized research assistant grounded in the specific library a user has already curated and paid for.
Background
Gemini Notebook—formerly known as NotebookLM—has positioned itself since launch as a "source-grounded" AI. Unlike standard chat models that hallucinate or drift into generic advice, it restricts its answers to the documents, links, and text a user uploads. Until now, those sources were largely manual uploads: PDFs, Google Docs, pasted text, or YouTube transcripts.
The Play Books integration removes a major friction point. Users no longer need to locate, download, and upload DRM-free files—a process that is often legally murky or technically blocked for commercial ebooks. Instead, the connection is native. If a title sits in a user’s Play Books library, it appears as an available source inside Gemini Notebook.
During a briefing with *The Verge*, Google Labs editorial director Steven Johnson demonstrated the workflow. He imported Michael Pollan’s *Food Rules* and asked the tool to generate a recipe book based on the author’s principles. In another example, the system applied concepts from Kim Scott’s *Radical Candor* to a specific management scenario, producing a tailored action plan. The feature also supports multimodal outputs: users can request an "Audio Overview" podcast where two AI hosts discuss the book’s key arguments, or generate visual summaries like mind maps and timelines.
Why It Matters
The business implication is straightforward: knowledge locked inside purchased books is now operational.
Most organizations buy books for leadership teams, assign them for onboarding, or stock them in digital libraries. That investment typically yields passive consumption—someone reads a chapter, takes sparse notes, and moves on. Expert Intelligence turns those static assets into active tools. A product manager can import *Inspired* by Marty Cagan and ask, "How would Cagan evaluate this feature spec?" A founder can load *The Hard Thing About Hard Things* and generate a crisis communication checklist grounded in Ben Horowitz’s framework.
Because the grounding is explicit, the risk of hallucination drops. The model cites specific pages and passages. Users can verify every claim against the original text. For regulated industries or high-stakes decision-making, that audit trail matters.
There is also a workflow advantage. The outputs—podcasts, infographics, structured plans—are shareable artifacts. A team lead can produce a 10-minute audio briefing on a new strategy book and drop it into Slack. A consultant can build a client workshop deck sourced directly from a methodology text the client already owns. The tool becomes a force multiplier for the "read and apply" loop that knowledge work demands.
The constraint is the ecosystem. The feature only works for books purchased through Google Play Books. Kindle libraries, Apple Books, and DRM-free EPUBs from other vendors are not supported. For businesses standardized on Amazon’s ecosystem, the utility is zero unless they repurchase titles. Google has not announced plans to expand import sources.
What’s Next
Google frames Expert Intelligence as a step toward "personalized AI expertise." The roadmap signals deeper integration between the Gemini model family and the user’s private data corpus—emails, Drive files, Calendar, and now commercial media libraries.
For AI adopters, the pattern is clear: the competitive advantage shifts from model access to data curation. The organizations that build clean, authorized, high-signal knowledge bases—whether from books, internal wikis, or customer transcripts—will extract more value from the same underlying models than those feeding them generic prompts.
Watch for two developments. First, whether Google opens the import API to third-party ebook platforms or enterprise content repositories. Second, how copyright holders respond. The feature relies on the user’s existing license to "read" the book; transforming that text into derivative works (podcasts, infographics, plans) via AI sits in a gray zone that publishers have not fully tested in court.
Takeaway for Business Owners
If your team already buys professional books through Google Play, enable Expert Intelligence immediately. It turns a sunk cost into a queryable asset. If you’re on Kindle or another platform, factor this capability into your next procurement decision: the platform that lets your AI actually *use* the books you buy will win the productivity argument. Start small—pick one high-impact title, import it, and task the tool with producing a deliverable your team needs this week. Measure the time saved. That’s your ROI.
Source: Original Article