Microsoft Copilot vs. Google Gemini for Workspace: Full Report and Comparison of Features, Performance, Pricing and more

Microsoft’s Copilot and Google’s Gemini (formerly known via Duet AI in Workspace) represent two leading AI copilots embedded in productivity suites. Copilot is woven throughout Microsoft 365 (Office apps, Teams, Windows, etc.), while Google’s Gemini brings generative AI assistance across Google Workspace apps (Gmail, Docs, Sheets, Meet, and more). Both aim to boost productivity by understanding context from your work data and assisting with content creation, analysis, and automation. This comprehensive comparison examines their core AI models, features in documents/spreadsheets/email, calendar and meeting smarts, voice and mobile capabilities, pricing models for businesses vs. individuals, enterprise integration, handling of files and plugins, and privacy practices – all as of late 2025. The goal is an informative, neutral look at how Microsoft Copilot and Google’s Gemini stack up in the modern workplace.

The core AI models powering Copilot and Gemini.

Microsoft 365 Copilot does not rely on a single large language model – it orchestrates multiple AI models behind the scenes. In practice, Copilot primarily uses OpenAI’s GPT-4 class models (such as GPT-4 Turbo), and Microsoft has indicated it will leverage newer models like GPT-4.1 and GPT-5 as they become available. In fact, by late 2025 Microsoft added support for GPT-4 Turbo as a default model for Copilot, offering faster performance. Copilot’s architecture can even tap into other providers’ models for specific tasks – for example, Anthropic’s Claude 4 for advanced reasoning, or even Google’s Gemini for certain coding contexts. This multi-model strategy means Copilot can choose the best AI “brain” per task, all while grounding queries in the user’s data via the Microsoft Graph.

Google’s Workspace AI is powered by its own cutting-edge model family called Gemini. As of 2025, the flagship is Gemini 2.5 Pro, which Google touts as its “most intelligent AI model” with robust reasoning, coding, and multimodal capabilities. Gemini 2.5 is a “thinking” model designed for complex problem-solving; it leads many benchmarks and excels at tasks from math and science Q&A to code generation. A key advantage of Gemini 2.5 Pro is its enormous context window – it can handle up to 1 million tokens of context (with plans for 2 million), allowing it to ingest and analyze very large documents or datasets in a single session. This far exceeds the context length of typical GPT-4 implementations (which max out at ~32k tokens), highlighting Google’s focus on enabling long-context reasoning. In summary, Copilot’s intelligence comes from OpenAI’s GPT models (augmented by others in an orchestration), whereas Google has built Gemini as a formidable rival model specifically for Workspace AI assistance. Both companies continue to update these core models (e.g. OpenAI’s GPT-5 and Google’s future Gemini versions) to improve accuracy and capabilities.

·····

Both Copilot and Gemini offer AI assistance for documents, spreadsheets, and emails.

One of the most impactful use cases of these AI copilots is helping users draft, edit, and analyze content in documents, spreadsheets, and email. Microsoft Copilot and Google Gemini (via Duet AI features in Workspace) both integrate deeply into their respective productivity apps to assist with writing and data tasks.

In word processing, Copilot lives in Microsoft Word’s toolbar and can generate content or modify your text on command. It can produce a first draft based on a prompt, help brainstorm or outline, rewrite selected text for clarity, or summarize a long document into key points. For example, a user can ask Copilot to “Draft a two-page project proposal based on the outline in my OneNote”, and it will pull context from your notes to create a draft in Word. It can also transform text to a different format (turn a paragraph into a table or a list) and suggest additional details or evidence by finding relevant info in your other files. Google’s Gemini provides similar aid in Google Docs. With the “Help me write” feature, users can ask Gemini to draft or refine text within a Doc. It can adjust the tone or style of writing, fix grammar and spelling, and generate summaries of the document on the fly. Unique to Google is the use of smart chips – Gemini can pull in context like referenced Drive files or tagged people. For instance, typing @Gemini help me write@ in Docs enables the AI to suggest completions or even insert relevant Drive content. Both AI assistants thus act as intelligent writing partners: Copilot leverages your Microsoft 365 content (Word files, OneNote, etc.) for context, while Gemini uses your Google Workspace data (Drive, Docs) to keep suggestions relevant.

......|

......

Feature	Microsoft Copilot (Microsoft 365)	Google Gemini (Workspace)
Document assistance	Generates and revises content in Word. Offers “Rewrite” suggestions, can transform text into tables or bullets, and summarizes documents. Leverages context from OneDrive/SharePoint to enrich the draft.	“Help me write” in Docs drafts text or refinements. Checks grammar and style, inserts summaries, and even creates images for illustrations within the document. Uses smart chips to pull info from Drive and other Docs.
Spreadsheet help	Copilot in Excel creates formulas and analyzes data. It can suggest charts or identify trends/outliers from a selection. Users can ask in plain language (“What are the top 5 sales regions?”) and get answers with pivot tables or charts. It also helps clean data and import external data via Microsoft Graph.	Gemini in Sheets offers an =AI function to generate insights. It can autofill tables, predict values to complete a column, and categorize or summarize data sets. It can also generate template layouts and classifications based on the sheet’s content.
Email assistance	Integrated into Outlook as a side-panel assistant. Copilot can summarize long email threads, highlight key points and action items, and draft replies in the correct tone. It can also suggest meetings, generate agendas, and help triage inbox priority.	Built into Gmail’s “Help me write”. Gemini drafts new emails or refines your draft. It summarizes long threads and suggests reply options. It supports multiple languages for drafting and tone tuning.

. |......

As seen above, both Copilot and Gemini significantly streamline working with text and data. In practice, Copilot’s strength lies in its deeper actions within Office apps – e.g. creating an Outlook meeting agenda from an email thread or pulling data from Excel into a Word report – thanks to Microsoft Graph’s unified view of your work data. Gemini’s strengths include seamless multimodal aid (it can generate images in Google Slides or graphics in Docs) and context-aware suggestions using your Google Drive content. For example, in Google Slides, Gemini can not only rewrite text but also create speaker notes and even generate custom slide images on demand. Overall, for everyday document creation, data analysis, and email drafting, both assistants serve as capable AI helpers – reducing drudgery by handling first drafts and providing insights so users can focus on refining and decision-making.

·····

Both assistants offer AI help with calendars and can summarize meetings.

Managing meetings and schedules is another area where Copilot and Gemini compete. Microsoft Copilot ties into Outlook and Teams to facilitate meeting prep and follow-up. For instance, within Outlook email, Copilot can proactively schedule a meeting – if an email thread suggests a discussion, Copilot will draft an invite with date/time suggestions and even generate an agenda based on the email context. Once in a meeting (especially Microsoft Teams), Copilot acts like a smart note-taker and analyst. It can summarize the key discussion points of a Teams meeting in real time or afterward. It identifies action items and decisions, and can answer questions about the meeting – e.g. “What decisions were made regarding Project X?” – by referencing the transcript and chat. Users who join a meeting late can ask Copilot to catch them up, and those who miss a meeting entirely can receive a Copilot-generated recap. This recap includes attendees, major topics, and any tasks assigned, saving time on meeting minutes. In short, Copilot helps ensure no one misses critical information from meetings, by providing concise summaries and extracting follow-up tasks.

Google’s Gemini (Duet AI) similarly boosts productivity around meetings, especially in Google Meet and Calendar. In Google Calendar, the AI can suggest optimal meeting times or automatically schedule meetings by coordinating attendees’ availability (leveraging Google’s scheduling features, which Duet can access). During Google Meet calls, Gemini’s presence is notable through the “take notes for me” feature: the AI will generate live meeting notes and turn them into a Google Doc that can be shared. It captures the discussion and action items in a structured document without human effort. Moreover, if you’re unable to attend a Google Meet, Duet AI can attend on your behalf in a limited capacity – it won’t participate actively, but it will record the meeting and produce a summary for you. Google has demonstrated an “attend for me” concept where the AI can even deliver a brief statement in the meeting on your behalf and then take notes. After the meeting, Gemini can email a summary to all attendees or to those who missed it. In Meet, Gemini also provides real-time translated captions (e.g. translating a speaker’s speech into your preferred language live), which is invaluable for global teams. It even suggests custom backgrounds and optimizes audio/lighting for video calls – these latter features are more about convenience, but they show Gemini’s integration in enhancing meeting quality.

In terms of meeting summarization quality, both AI assistants are evolving rapidly. Copilot benefits from its integration with Microsoft Teams and the Microsoft Graph – it can pull in related documents or emails during a meeting to answer context questions (for example, “What did we decide about Budget in last week’s meeting?” might prompt Copilot to fetch notes from that meeting). Google’s Gemini leverages Google’s speech-to-text and translation prowess, making Meet summaries and captions very accurate and multilingual. Both can generate follow-up emails or tasks: Copilot can draft an email summary of a Teams meeting to send to stakeholders, while Gemini can add action items to Google Tasks or Calendar reminders based on the meeting discussion. For scheduling, Microsoft’s Copilot being embedded in Outlook gives it an edge for those in Microsoft’s ecosystem, whereas Google’s assistant shines for Google Calendar users. Overall, each assistant ensures you spend less time in meetings or catching up on them – by automating note-taking, summarizing long discussions, and helping with the scheduling logistics so you can focus on the meeting content itself.

·····

Both Copilot and Gemini extend their AI assistance to voice and mobile platforms.

As AI copilots become part of daily workflows, both Microsoft and Google have introduced voice and mobile capabilities to make their assistants accessible anywhere. Microsoft’s Copilot is accessible not just on desktop apps but also via mobile and voice-enabled interfaces. In 2024, Microsoft launched a Microsoft 365 Copilot mobile app for iOS/Android, which acts as a pocket productivity assistant. This mobile Copilot lets users use voice or text to ask for help on the go – for example, “Summarize the last email from my boss” or “Update the Excel sales report with the latest figures” – and it will perform the task, leveraging cloud connectivity to your Microsoft 365 data. Windows 11 also now features Windows Copilot, a sidebar AI that can be summoned with a click or voice command. It’s essentially Bing Chat (GPT-4) with knowledge of your PC context, allowing you to control settings or summarize on-screen content by voice. Microsoft has enabled voice input for Copilot chats on many platforms, recognizing that speaking a request can be more convenient than typing. For instance, in the Copilot mobile app or in Teams on your phone, you can tap the microphone and ask, “Copilot, what are my priorities for today?” – and it will speak back a brief summary of your top meetings and tasks. Copilot is also beginning to integrate with Microsoft’s Cortana voice assistant heritage (though Cortana as a standalone is deprecated, its functionality is merging into Copilot). Moreover, Copilot can generate audio output for certain content: one new feature is turning document summaries into audio (the “podcasts” feature), effectively letting Copilot read out information in a natural-sounding voice. This is useful for listening to reports or emails while commuting. In short, Microsoft is making Copilot a multimodal assistant – accessible via voice commands, able to respond with text or speech, and present on PCs, the web, and mobile devices for continuous support.

Google’s approach similarly blends Gemini into voice and mobile experiences. In late 2025, Google began upgrading the Google Assistant on mobile to Gemini. This means that on Android phones (and eventually other devices), saying “Hey Google” now invokes the more advanced Gemini AI instead of the older assistant engine. The result is a more conversational and capable assistant: you can speak naturally to it to draft messages, create content, or answer complex questions, and Gemini will leverage its powerful model to comply. For example, you might ask via voice, “Compose a thank-you email to the team and summarize our project highlights,” and Gemini will draft a proper email for you in Gmail, all through voice interaction. The Gemini mobile app (essentially the evolution of the Bard app) is available on Android and iOS, giving users a chat interface on the go for brainstorming, researching, or getting help with Workspace files. This app accepts voice input as well – you can talk to Gemini as you would to a personal assistant. Because Gemini is natively multimodal, it can understand images or screenshots you might upload on mobile and respond accordingly. Google is effectively replacing its prior Google Assistant with Gemini Assistant, unifying the experience. Users can opt-in to have Google Assistant use Gemini for a more powerful AI experience. This brings features like having the assistant read and draft messages in any app, summarize articles you’re viewing on your phone, or even control phone settings with smarter understanding. Additionally, Google’s devices (Pixel phones, etc.) often integrate these AI features at the OS level – for instance, a feature called “Call Assist” can summarize lengthy customer service calls in real time or help you draft replies during a call, using Gemini’s language prowess.

Both Copilot and Gemini thus aim to be ubiquitous digital assistants. Copilot leverages Microsoft’s ecosystem (PC, Office, Teams, Cortana legacy) to be available wherever work gets done, with increasing emphasis on voice and even vision (e.g., the new “Copilot Vision” can analyze images in OneNote). Gemini leverages the billions of Android devices and Google services to reach users, effectively turning the familiar “Google Assistant” into a next-gen AI aide. For users, this means the line between “desktop work assistant” and “mobile voice assistant” is blurring – you can ask either AI to do things like send a summary, find a file, or give you a briefing, whether you’re at your desk or in the car using voice. This hands-free, cross-device capability greatly enhances productivity and accessibility for both individual and enterprise users.

·····

Business and individual pricing structures differ significantly between Copilot and Gemini.

Microsoft and Google have taken contrasting approaches to pricing their AI copilots for organizations and end users. For businesses, Microsoft 365 Copilot is generally an add-on license on top of existing Microsoft 365 plans, whereas Google’s Gemini features are included by default in many Workspace subscriptions.

• Microsoft (Business) – Microsoft 365 Copilot is offered as a paid add-on for commercial customers at roughly $30 per user per month. This fee is in addition to the base Microsoft 365 subscription cost. For example, a company paying for Microsoft 365 Business Standard ($12.50/user/month annually) would pay an extra $30 for Copilot, totaling ~$42.5 per user monthly. Microsoft initially targeted enterprise customers with this $30 Copilot licensing (e.g. Microsoft 365 E3/E5 plans + Copilot). In late 2025, Microsoft extended Copilot availability to small and medium businesses as well, at the same add-on rate. The add-on grants access to Copilot across all the user’s Microsoft 365 apps and services, plus admin tools to manage Copilot usage.

• Google (Business) – Google took a more inclusive approach: since early 2025, generative AI capabilities (Duet AI, now “Workspace with Gemini”) have been built into Business and Enterprise tiers of Google Workspace at no extra charge. In other words, if your organization subscribes to Google Workspace Business Standard ($12/user/month) or Business Plus (~$18), you automatically get the Gemini AI features in Gmail, Docs, Sheets, Meet, etc. at those plan prices. There isn’t a separate “Duet AI license” fee for core features – Google’s strategy has been to make AI a value-add to retain Workspace customers. (Notably, Google did experiment with a paid Duet AI add-on in 2023, but reversed course to bundle it in plans by 2025.) However, Google has introduced Gemini Enterprise – a separate advanced AI subscription (launched in Oct 2025) priced at $30 per user/month for organizations that want to build custom AI agents and integrations beyond Workspace. This is optional and geared towards large enterprises needing an “AI platform” (akin to a more powerful AI sandbox with connectors to Salesforce, SAP, etc.), whereas typical Workspace businesses get the built-in AI with no extra fee.

......

......

Customer	Microsoft Copilot Pricing	Google Gemini (Duet AI) Pricing
Enterprise/Business	Add-on license required: +$30 per user per month for Copilot (on top of Microsoft 365 plan cost). Example: M365 Business Standard ~$12.50 + Copilot $30 ≈ ~$42.5 per user/month. The add-on unlocks Copilot across Word, Excel, Outlook, PowerPoint, Teams.	Included in base subscription: $0 extra for core Gemini features in many Workspace Business / Enterprise editions. You pay the normal Workspace plan (e.g. Business Standard, Business Plus) and get AI built in. Optional: Gemini Enterprise at ~$30/user/month for advanced/custom AI agents.
Individual (Consumer)	Free basic: Windows Copilot / Bing Chat with limits. Premium: Microsoft 365 Premium at $19.99/month, which bundles Copilot + Office apps + expanded OneDrive for individuals/families. Lower Microsoft 365 Personal/Family plans get limited Copilot features with usage caps.	Free tier: basic Gemini access (Gemini 2.5 Flash) with limits. AI Plus: around $5/mo for boosted usage. AI Pro: ~$19.99/month (or ~$199/year) with Gemini 2.5 Pro access + 2 TB storage. AI Ultra: ~$249.99/month for power users, including Deep Think / high-end generation credits.

......

For individual users, the landscape is also evolving. Microsoft initially did not offer Copilot to consumers outside of Bing Chat, but by late 2025 it launched Microsoft 365 Premium for $19.99/month which gives consumers Copilot access in Word, Excel, Outlook, etc., alongside the Office apps and cloud storage. This essentially brings Copilot to tech-savvy families and individuals willing to pay for a higher-tier Microsoft 365 subscription. Meanwhile, standard Microsoft 365 Family/Personal subscribers (who pay ~$6.99–9.99/month for Office and 1TB OneDrive) get limited Copilot features at no extra cost – Microsoft increased the usage caps and is allowing these users to sample Copilot’s image generation, visual analysis (“Copilot Vision”), and other features in a controlled way. Microsoft’s strategy seems to be encouraging upgrades to the Premium plan for full AI access, while not alienating existing subscribers by giving them a taste of AI. On the other side, Google’s approach to consumers is tied to its Google One subscription tiers. Gemini AI Pro at $19.99/mo is equivalent to Google’s 2 TB storage plan; subscribers get the top-tier Gemini model and features like Deep Research and NotebookLM for document analysis. There’s also a free tier for casual use – anyone can use the Gemini app or Bard (which Gemini supersedes) in a limited capacity for free. And Google introduced an “AI Plus” $5 plan in some regions to bridge the gap. In summary, Google provides a more gradated pricing ladder for individuals (free, $5, $20, $250) depending on needs, whereas Microsoft has essentially a free/basic offering (via Bing/Windows) and then a big jump to a $20 Premium plan for full capabilities, aligning with their paid Office model.

From a business perspective, Google’s inclusion of AI in standard Workspace plans can be a cost advantage if you were comparing suite-to-suite. A company that already uses Google Workspace can enable powerful Gemini features without a procurement or security review for a new add-on – it’s simply part of the service. Microsoft customers, however, must budget that additional $30/user, which is significant – often nearly doubling the per-user cost of the Office suite for many licenses. Microsoft argues the productivity gains justify the cost, and indeed demand for Copilot has been strong, but it is a point of differentiation. It’s noted that Microsoft started bundling some domain-specific Copilots (for Dynamics 365, etc.) at lower costs or in bundles by late 2025, hinting at possible price adjustments. But as of Oct 2025, the headline remains: Copilot typically costs extra for businesses, while Gemini’s core features do not. Organizations will weigh this against the capabilities and ecosystem preference when choosing between Microsoft 365 and Google Workspace for AI-powered productivity.

·····

Copilot and Gemini offer distinct enterprise integrations within Microsoft 365 and Google Workspace.

When it comes to enterprise integration and extensibility, each assistant leverages its parent ecosystem’s strengths. Microsoft Copilot is deeply intertwined with the Microsoft 365 ecosystem and Microsoft Graph, which gives it access to a rich context about the user’s work – emails, meetings, contacts, documents, Teams chats, and more. This means Copilot can retrieve and reason over organizational content seamlessly. For example, in Word you could ask, “Insert the latest sales figures,” and Copilot (through Graph) can fetch the relevant Excel data from OneDrive or a Power BI report. Microsoft’s Copilot uses an orchestrator (often referred to as the “Prometheus” layer) that first grounds user queries in enterprise data via Graph, then calls the LLM, and finally formats the response with references to that data. The result is that Copilot’s answers in enterprise settings tend to be highly context-specific and actionable (e.g., pulling client data from Dynamics 365 CRM if you ask a sales question).

Furthermore, Microsoft has rolled out Copilot Studio, an environment for organizations to build custom AI copilots and integrations. In 2025, Copilot Studio started allowing enterprises to choose different underlying models (OpenAI GPT-4.1, Anthropic Claude 4, etc.) for their custom assistants and even bring their own internal models (via Azure AI). This flexibility means a company could fine-tune a smaller model on proprietary data and have Copilot use it for domain-specific queries, all within Microsoft’s managed interface. Copilot Studio also supports developing plugins (called “API plugins”) that let Copilot interact with third-party applications. These plugins use the same OpenAPI standard as OpenAI’s ChatGPT plugins, enabling Copilot to perform actions like querying an internal database or creating a ticket in ServiceNow via natural language. For example, a developer can register a CRM’s API with Copilot; then a manager could ask, “Copilot, update the status of Project X to completed in Salesforce,” and Copilot will call that API to perform the update. Microsoft has a growing catalog of these extensions, and it has aligned them with its Teams and Power Platform as well – meaning Copilot can trigger workflows, Power Automate flows, or retrieve Power BI analytics as part of an answer. Overall, Copilot is becoming an AI orchestration layer across Microsoft 365 and beyond, aiming to integrate all the tools a business uses.

Google’s Gemini, integrated via Google Workspace with Gemini and Gemini Enterprise, focuses on connecting various Google and non-Google applications through a unified AI front-end. Out-of-the-box, Gemini in Workspace ties together Gmail, Calendar, Drive, Docs, Sheets, and Meet, so it can move fluidly between them (e.g., if you’re in Gmail drafting a reply, Gemini can pull info from a Docs file you have in Drive to include, all within the prompt). For larger organizations, Google introduced Gemini Enterprise, which is described as “the new front door for AI in the workplace”. Gemini Enterprise provides a chat-based interface where employees can interact with AI agents that have access to corporate systems. Critically, it “securely connects to your company’s data wherever it lives — from Google Workspace and Microsoft 365 to business applications like Salesforce and SAP.”. This highlights Google’s acknowledgment that many enterprises use a mix of systems; Gemini aims to bridge them. Through Gemini’s no-code AI orchestration tools, companies can build custom agents that perform multi-step workflows (for example, an agent that collates data from an internal database, generates a slide deck draft in Google Slides, and emails a summary to the team – all triggered by a single prompt). Google provides pre-built “taskforce” agents for common needs like “Deep Research” (an agent that can research across your Google Drive and external sources to answer a question) and “Data Insights” (for analyzing data sets), and these can be extended with a partner ecosystem of connectors. Notably, Gemini Enterprise can integrate with Microsoft 365 data too – for instance, connecting to SharePoint or Outlook – under an open approach. Google’s vision is an open AI fabric where their AI can work with a company’s existing tools, not just Google’s apps.

In terms of enterprise workflow, both AI platforms are adding multimodal and specialized capabilities. Microsoft’s Copilot in the enterprise can be used within developer IDEs (GitHub Copilot X), in Power Platform (to generate formulas or apps), and even in security (as Security Copilot for cybersecurity analysts). Google, at its end, is leveraging its Cloud AI strengths – e.g., using Vertex AI for custom model deployment and then surfacing those via Gemini Enterprise. Google Cloud Blog announced multi-modal Gemini agents in Workspace that handle text, image, video, and speech – for example, a “Google Vids” agent that turns a Google Slides deck into a video with AI-generated script and voiceover, and voice agents that do real-time language translation in Google Meet. These show how Gemini is expanding into creative and communication tasks within enterprises. Another example: Google’s AI can summarize data from BigQuery or spreadsheets and create a narrative, similar to how Microsoft’s Copilot can generate a SWOT analysis from SharePoint files.

In summary, Microsoft Copilot’s enterprise integration revolves around harnessing the Microsoft 365 stack and extending it with plugins and custom AI (especially via Azure OpenAI Service for those who want custom models). Google’s Gemini integration emphasizes cross-platform connectivity and workflow automation, trying to unify not only Google’s suite but also external systems under a single AI assistant interface. Both offer admin controls and compliance: Microsoft has a Copilot control panel for IT to manage access and monitor usage, and Google’s admin console similarly lets admins enable/disable specific AI features and retains audit logs. As enterprises evaluate these, they will consider how well the AI can mesh with their data silos and processes. In many cases, companies may even use both – for example, a firm might use Microsoft 365 but also adopt Gemini Enterprise to build certain AI workflows, or vice versa, since Google is positioning Gemini to work in Microsoft environments too. The race is on to be the AI hub for enterprise knowledge and operations.

·····

Copilot and Gemini differ in file support, memory limits, tool integrations, and output formats.

Beyond core apps, it’s important to compare file handling, memory, tools, and structured output capabilities of Microsoft Copilot vs Google Gemini:

• File support and uploads: Both assistants can work with a variety of file types, but how they do so differs. Microsoft Copilot typically works in-context of Office files – e.g., you open a Word document and ask Copilot to summarize it, or you have an Excel file and ask Copilot to analyze the data. Copilot leverages the fact that your files are stored in OneDrive/SharePoint; it has read access (with your permission) to those files to answer questions. For instance, you can query in Copilot Chat, “What are the key takeaways from the PDF in my OneDrive named Q3_Financials.pdf?” and it will fetch and summarize that PDF. Copilot’s context window is effectively the model’s context (GPT-4’s limit) plus any retrieval from Graph. Currently GPT-4 Turbo in Copilot supports an 16k to 32k token window, which can handle moderately long documents or multiple files at once. Google’s Gemini offers more direct file upload in its interface: in the Gemini app or in NotebookLM (a Google Labs tool now integrated with Gemini Pro), users can upload PDFs, images, or Google Docs/Sheets for analysis. Gemini being multimodal means it can even parse images (for example, you could snap a photo of a chart and ask Gemini to interpret it). With its massive context window (up to 1M tokens in 2.5 Pro), Gemini can ingest extremely large files or even multiple documents and maintain all that information during conversation. Google’s NotebookLM integration (available to Pro users) is specifically aimed at analyzing long documents or sets of documents, allowing Gemini to generate summaries with source citations from those files. In practical terms, if you have a 200-page contract, Gemini can handle it in one go, whereas Copilot might need to summarize it section by section due to token limits. That said, Microsoft is exploring long-context models too (e.g., research into GPT-4 with 100k tokens via Azure). Both systems support common business file types (DOCX, PPTX, PDF, CSV). Copilot in PowerPoint, for example, can insert images and design slides for you, but it doesn’t “upload” files per se – it works with what’s in your 365 cloud. Google’s Gemini can fetch files from Google Drive when prompted (e.g., “Summarize the document Proposal.docx from my Drive”), similar to Copilot with OneDrive.

• Memory and context behavior: In interactive use, both AI assistants maintain conversational context within a session, but length and persistence vary. Microsoft Copilot’s memory is typically scoped to the current document or chat session. For instance, Copilot Chat in Teams or Outlook will remember what’s been discussed in that chat thread to a certain extent, but it might not recall a detail from a different document you referenced 2 hours ago unless re-provided. Microsoft has removed limits on turns per conversation for Copilot in 2024, allowing longer back-and-forth with the assistant. Still, if the conversation gets very lengthy, Copilot may summarize or forget older parts beyond the model’s token limit (~8k or 16k tokens historically for GPT-4, possibly more with GPT-4 Turbo). Google’s Gemini, especially in Advanced/Pro modes, was built with “thinking” and long-context use in mind. It can handle extended dialogues and even multi-document discussions without losing track easily. In the standalone Gemini chat app, users can have very long threads (the Ultra tier extends this further). However, neither system has indefinite memory across sessions – once you close a session or explicitly reset, the models don’t retain your data (for privacy reasons). One difference: Google’s Workspace has an approach where certain context can persist in a controlled way; for example, if you pin a particular context (like a specific Google Doc) in a NotebookLM session, Gemini “remembers” that document for follow-up questions until you unpin it. Microsoft’s Copilot doesn’t have an exact analog yet, though in Copilot Studio, developers can pre-load certain organizational content for an agent.

• Tools and plugins: Microsoft Copilot now supports a plugin ecosystem allowing it to use external tools/APIs. This is akin to giving Copilot “skills” – for instance, a weather plugin to fetch weather, a CRM plugin to log a case, or even internal tools. These API plugins function as described earlier, where Copilot can decide to invoke them based on the user’s request. Microsoft has aligned this with OpenAI’s model, meaning many ChatGPT plugins are or will be compatible with Copilot (via Bing Chat and Teams). An example scenario: You ask Copilot, “Book a flight to London next Monday”, and if a Skyscanner plugin is installed, Copilot can query it and present options, rather than just saying “I cannot book flights.” All such actions are done with user permission, and Microsoft 365 admins can govern which plugins are allowed. Google’s Gemini approach to tools is a bit more behind-the-scenes. While Google hasn’t launched a public “plugin store” for Gemini as of Oct 2025, it has integrated Gemini with Google’s own suite of tools (Maps, Search, etc.) and some partner applications via the extensive partner ecosystem in Gemini Enterprise. Google’s AI can use something called App Actions in Workspace – for example, within Gmail, you might see a suggestion “Draft calendar invite” and clicking it triggers the Calendar integration through Duet AI. In code, Google’s PaLM API (the predecessor to Gemini) had a tool use-case where you could give the model access to Google’s APIs (for Maps, etc.); it’s likely Gemini can do the same under the hood (e.g., if you ask Gemini in Chat “Where is the upcoming company offsite?”, it could call a Maps API to get location info if integrated). For developers, Google’s emphasis is on Vertex AI and AppSheet for custom extensions – i.e., you can build a chat app that uses Gemini and hooks into various APIs, but not as freely end-user-configurable as Copilot’s plugins yet. In summary, Microsoft currently provides more user-facing plugin infrastructure for Copilot, whereas Google offers integration through its enterprise agent platform and built-in connectors.

• Structured output and formatting: Both Copilot and Gemini can produce structured outputs like tables, JSON, bullet lists, or even diagrams, but with some differences in how reliably they format information. In Microsoft 365 apps, Copilot can not only generate text but also directly modify Office documents in structured ways. For instance, in Excel you can say “Create a table of the top 5 products by sales” and Copilot will insert that as an actual Excel table, not just formatted text. In Word, if you ask for an outline, Copilot might use the proper heading styles and bullet points, leveraging Word’s formatting. This is possible because Copilot has some awareness of the host application’s object model (for example, Copilot in Word can apply styles, add comments, etc.). Google’s Gemini, when used in Docs or Sheets, will also insert content as native elements (it will create a bulleted list in Docs if asked, or put a formula in a Sheets cell if requested). However, in free-form chat (like the Gemini web app), getting a perfectly formatted table or JSON is hit-or-miss – the model tries its best, and Gemini 2.5 is quite good at following format instructions. Notably, Gemini’s large context helps it produce long structured outputs without losing consistency. If you ask for a detailed HTML or JSON output, it can comply, but Google has guardrails in the consumer app that sometimes prevent very large outputs. Copilot (using GPT-4/5) is also strong at structured output, but in certain Microsoft contexts it may refuse to produce executables or certain formats for security. Both systems allow code generation (for instance, Copilot in GitHub or VS Code is famous for suggesting code; Gemini has a Codey model variant and will also output code in responses). For a business user, structured output often means tables of analysis or step-by-step plans. Both AI will happily produce those. One unique feature: Google’s NotebookLM (Gemini Pro) will output answers with footnote citations linking back to your source documents – useful for analysts who need to verify the summary. Microsoft Copilot, when answering based on, say, corporate SharePoint files, doesn’t currently insert footnotes, but it may list the files it drew from or suggest where the info came from (“as per the Q3_Financials.xlsx in OneDrive”). In Bing Chat (the consumer web version of Copilot tech), sources are cited, but in Microsoft 365 Copilot, the assumption is it’s your own content.

• Multimodal and “visual” tools: Both AIs are expanding beyond text. Microsoft Copilot integrates DALL·E 3 for image generation within Designer and Bing, meaning a user in Word can ask Copilot to “Create an image of a growth chart” and get an AI-generated graphic. Copilot in PowerPoint can generate new slide designs and even place images or icons appropriate to the content. Google’s Gemini has the “Flash” image model and can generate images in Slides or the AI app (though Google often keeps image generation somewhat separate, e.g., through its Imagen model). Still, Duet AI in Slides explicitly allows “create custom images for my slide about robotics” and it will produce options. Both also do voice-to-text and text-to-voice: Copilot can read aloud content (handy for accessibility or listening to reports) and take voice input; Gemini in the new Assistant can respond with voice output if using Google’s TTS.

In summary, Copilot offers tight integration with Microsoft file formats and a burgeoning plugin system for tool use, while Gemini offers unparalleled context length and deep integration with Google’s cloud (and an emphasis on cross-platform agent orchestration). If your work involves handling very large documents or datasets in a single analysis, Gemini’s 2.5 Pro model has an edge with its million-token memory. If you need your AI assistant to execute actions across various enterprise apps (send emails, update records, trigger workflows) with fine control, Copilot’s plugin and Microsoft Graph integration provide a robust framework for that. Both systems are rapidly closing each other’s gaps – we can expect Microsoft to increase Copilot’s context limit and Google to open up more third-party plugins. The end goal for both: an AI that not only converses, but acts on the user’s intent across all their tools, and outputs results in the exact format needed.

·····

Both Microsoft and Google emphasize privacy and have policies for user data handling.

In deploying AI assistants that work with personal and company data, privacy and data handling are paramount. Both Microsoft and Google have made clear commitments that Copilot and Gemini will not use your private workspace content to train broad foundation models.

Microsoft’s privacy stance: Microsoft has stated unequivocally that it does not use customer data from Microsoft 365 to train the underlying AI models that power Copilot. Your documents, emails, chats, etc., stay within your tenant and are not fed back into, say, OpenAI’s training corpus. This was reiterated in response to some misinformation in 2024; Microsoft clarified that features labeled “Connected Experiences” in Office (which involve cloud processing of content for things like Designer or Editor) are about providing functionality to you, not about harvesting data for AI training. Unless a customer explicitly opts in for a scenario (for example, a customer might choose to fine-tune a model on their data, which is a specific contract), Microsoft’s default is no human or outsider sees your content and it’s not used to improve the base AI. Additionally, Microsoft built Copilot with a “commercial data protection” layer. In Copilot’s web context (when it answers using Bing search plus work data), Microsoft says it “doesn’t retain your prompts or responses” and “doesn’t use your chat data to train the underlying models”, treating it with the same confidentiality as any enterprise cloud service. Essentially, Copilot operates within the Microsoft 365 service boundary, inheriting all the compliance and security that comes with it. For enterprise customers, Copilot adheres to industry standards like GDPR, SOC 2, HIPAA, etc., and Microsoft provides documentation (Data Processing Addendums) to that effect. Admins also have controls to prevent sensitive content flow – e.g., they can disable Copilot’s web search capability in regulated industries to ensure no data ever leaves the tenant (indeed, Microsoft 365 Copilot’s July 2025 update disabled web search by default for enterprise users to enhance privacy).

Google’s privacy stance: Google similarly promises that your Workspace data is yours and isn’t used to train Google’s models without permission. In an August 2023 announcement, Google explicitly said: “Your data stays in Workspace. We do not use your Workspace data to train or improve the underlying generative AI and large language models that power Bard, Search, and other systems outside of Workspace without permission.”. Google’s Duet AI (now Gemini) interactions are kept private to your account. No other user can see your content through the AI, and Google doesn’t use, for example, your company’s Gmail or Docs content to make Gemini “smarter” for the general public. For business and public-sector customers, Google adds extra safeguards: Duet AI’s outputs and prompts are stored within your domain’s collaboration data (so if you generate a Doc summary, that summary is saved like any other user data in your Drive) and are not seen by Google employees or other orgs. They also automatically apply enterprise security controls – for instance, if an admin has set Data Loss Prevention (DLP) rules (like “don’t allow credit card numbers in Chat”), those rules will also govern Duet AI’s functioning. Google underwent independent audits and has detailed privacy documentation, reassuring that using Workspace’s AI features does not weaken the privacy of Workspace. In plain terms: your prompts and AI-generated text are not used to train Gemini’s next version; they remain confined to your account. Google also doesn’t use that data for ads, a point they specifically highlight (Workspace data is not scanned for ad targeting, and that continues with AI).

Both companies also give users and admins control and transparency. Microsoft 365 admins can turn Copilot on or off per app or tenant, and users can always choose whether to share a piece of content with Copilot (for example, if you have a sensitive document, you’re not forced to let Copilot read it). Microsoft provides audit logs of Copilot usage in the Compliance Center, so admin can see things like “User X asked Copilot a question involving File Y.” Google, through the Workspace admin console, similarly logs AI activities and lets admins enable Duet AI features selectively (some education customers, for example, might disable AI-generated content in Gmail but allow it in Docs). Both systems ensure that if data is sent to the cloud for AI processing, it’s encrypted in transit and at rest. Microsoft leverages Azure’s security, and Google uses its Cloud infrastructure security – both are state-of-the-art in terms of certifications and encryption.

Another aspect of data handling is responses and accuracy: Both companies warn that AI might produce inaccurate or biased content, so they encourage users to verify critical outputs. Microsoft has built a feedback mechanism in Copilot (a user can flag an inappropriate response, which is then reviewed under their standard privacy-preserving processes – similar to how Microsoft handles data in, say, Office crash reports). Google does the same; if you “Report an issue” with a Gemini response, that feedback may be used to improve the model, but Google clarifies that such feedback is usually scrubbed of personal info and aggregated. By default, though, the content of your documents or emails themselves are not collected into training sets.

It’s also worth noting that neither Copilot nor Gemini will expose one user’s data to another. If two users at the same company both ask a question, each will only get results from content they have permission to access. Copilot respects Microsoft 365’s document permissions (so if you can’t open a file normally, Copilot won’t retrieve info from it for you). Google’s Duet respects Drive sharing settings and so on. They are essentially permission-bound agents.

In conclusion, both Microsoft and Google have aligned their AI offerings with the principle that your organizational data remains confidential and is only used to serve you, not to train AI models for others. They’ve built on their long-standing privacy and security frameworks (Microsoft leveraging enterprise-grade Azure security, Google leveraging its zero-trust Google Cloud security model) to ensure that adopting Copilot or Gemini doesn’t mean giving up control of your information. Enterprises evaluating these solutions often conduct their own compliance assessments, and so far both Copilot and Workspace AI have been cleared for use in sectors like finance and healthcare under strict agreements. The bottom line: Microsoft and Google are effectively on the same page about user data handling – no content harvesting, no sharing, and transparency/controls for the customer – because any lapse in this area would break the trust needed for AI to be widely adopted at work.

FOLLOW US FOR MORE

DATA STUDIOS

[datastudios.org]