"We had gathered our internal manuals and past meeting minutes in NotebookLM so new hires could look up how things are done on their own. But last week, when they opened the app, the name had changed to Gemini Notebook, and flustered employees started asking if NotebookLM was gone and their data lost." We heard this from an information management lead at a company with about twenty employees. The short answer is: no data was lost. Only the name changed and capabilities expanded. However, without a brief prior notice, changes like this manifest across frontline staff as confusing reports of things being broken or missing.
On July 16, 2026, Google announced that NotebookLM, the tool for querying uploaded internal information, was renamed to "Gemini Notebook." Bringing the tool under the Gemini brand family is significant: its positioning has shifted to make it an integrated asset across Google's entire AI ecosystem. In this article, we break down what changed, what stayed the same, and what businesses managing internal knowledge need to know.
What changed and what stayed the same
First, let's step back and look at the big picture. This change is about the name and expanded capabilities; existing notebooks and imported documents have not been lost.
| Details | |
|---|---|
| What hasn't changed | Existing notebooks and imported documents remain intact. Shared links are preserved via automatic redirection. Administrator intervention is generally unnecessary. |
| What changed (Name) | NotebookLM → Gemini Notebook. Positioned for use across Google products, including the Gemini app and Google Search. |
| What changed (Features) | Execute code in a secure cloud environment per notebook to perform data analysis and generate tables or slides. Bidirectional sync with the Gemini app. |
A vital detail is that shared notebook links continue to work through automatic redirection. If you have NotebookLM URLs posted in internal portals or procedure documents, you generally don't need to replace them. That said, employees unaware of the rename will inevitably get confused, so a simple internal heads-up stating "NotebookLM was just renamed to Gemini Notebook; all contents remain unchanged" will head off needless inquiries.
New capabilities: Moving from "read and answer" to "calculate and format"
The addition with the greatest practical impact is that each notebook is allocated a secure cloud computing environment, allowing you to write and run code against ingested materials. While Gemini Notebook previously functioned as a tool that answered questions within the scope of uploaded files, it now adds processing capabilities like aggregating imported numerical data into charts, or exporting structured spreadsheets and slides.
For example, if you upload monthly sales breakdowns and ask it to "create a table showing trends by store and month," it will return an aggregated table based on the source data. Portions of work previously spent copying numbers into Excel by hand can now be handed off while keeping the documents in context. However, advanced features like code execution roll out first to higher-tier plans (such as Google AI Ultra and eligible Workspace plans), with Pro tiers gaining access shortly after. To avoid surprises, verify what your organization's plan covers before building these features into workflows.
Additionally, two-way sync with the Gemini app has been introduced. Notebook name changes, document additions, and custom instructions reflect in real time on the Gemini app side. This makes it seamless to access company knowledge from the mobile Gemini app and organize the rest on desktop. Having Gemini bridge data across multiple apps aligns with the themes explored in our Article on Cross-Service Search in Google Workspace.
Operational considerations: Limiting source material is the greatest benefit
When setting up an internal AI query system, the greatest risk is plausible-sounding falsehoods (hallucinations). Standard chat AI draws from massive training corpora, which can produce answers that contradict internal company facts. Gemini Notebook's core strength is that it restricts the basis of its answers strictly to the documents you upload. By uploading only verified internal sources—such as employee handbooks, product manuals, and historical FAQs—it answers grounded solely in those materials, complete with source citations.
Managing your information sources is the cornerstone of leveraging internal knowledge with AI. Deciding what to feed it, whom to share it with, and how to restrict permissions on notebooks containing sensitive data are essential steps. Distributing tools without this groundwork risks opening doors to data leaks in exchange for convenience. The architecture behind making internal knowledge retrievable via AI is explored in our Article on Structuring Company Knowledge for AI Retrieval. For insights on pairing NotebookLM with Workspace to establish an internal knowledge base, see our Article on Combining NotebookLM and Workspace.
What administrators and the IT team should verify
Even for companies without dedicated IT personnel, there are minimum checklist items to review. One is feature availability by plan. As with code execution, available features vary by subscription tier. Announcing company-wide that a feature is available, only to discover your plan doesn't support it, creates needless confusion. Another is the sensitivity of the data handled internally. When uploading documents containing customer records or HR data, strictly limit sharing scopes and access permissions.
| What to verify | What happens if omitted |
|---|---|
| Feature scope supported by your plan | Team confusion when announced features turn out to be unavailable |
| Sharing scope for notebooks containing sensitive materials | Internal information exposed to unauthorized personnel |
| Who manages which notebook | Notebooks created by departed employees left unattended or orphaned |
While Google notes that administrator action is generally unnecessary, that refers purely to technical migration; establishing internal usage rules remains the responsibility of each company. Setting a clear baseline—such as verifying sharing permissions before uploading sensitive information—will nip potential security incidents in the bud.
Case study: A company that centralized internal inquiries into a notebook
Here is a practical example. At a firm with around thirty employees (name withheld), the general affairs department received dozens of repetitive questions every month—such as expense reimbursement procedures and paid leave applications—consuming valuable staff time. To resolve this, they compiled the employee handbook, various application manuals, and historical FAQs into a single notebook, allowing employees to query the system directly and receive answers with citations.
The success factor was restricting the answer source strictly to internal materials. While general chat AI mixes in guesswork, anchoring responses exclusively to uploaded manuals preserved answer reliability. Operations succeeded thanks to two practices: appointing someone to keep materials up to date (outdated manuals produce outdated answers), and managing sensitive files like HR records separately so they were never uploaded to this notebook. Managing what to feed the AI and what to withhold matters far more than model cleverness when deploying internal knowledge systems.
Start with an internal announcement and clear boundaries on source materials
The transition to Gemini Notebook presents a great opportunity to advance your internal knowledge management. However, leaving the name change unannounced or uploading sensitive documents without controls can quickly turn convenience into confusion and risk. Before diving into complex technical settings, take two straightforward steps: send a company-wide announcement clarifying that NotebookLM was simply renamed to Gemini Notebook, and set clear boundaries on what materials may and may not be fed into the AI.
If you want to make internal manuals and FAQs retrievable via AI, combine them with Google Workspace to build an internal knowledge base, or establish secure operational guidelines for sensitive data, feel free to reach out for a free consultation on Google Workspace & Internal Knowledge Management with GleamHub. From designing source materials and access permissions to drafting intuitive operational rules, we will support you according to your business needs.
