Google Introduces Gemini as a Universal Work Agent Across Workspace

extract

Welcome to Gemini at Work 2026: Introducing the Gemini agent Thomas Kurian CEO, Google Cloud Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: - Gemini, a single, universal agent for work that answers your questions, handles your knowledge work, creates your images and media, and writes and runs code. - Inline in Workspace, Gemini works directly inside Gmail, Drive, Docs, Slides, Sheets, Chat, and Calendar, carrying the same memory, skills, and controls it has everywhere else. - New data and analytics skills that allow both technical teams and everyday business users to use plain-language questions to get to actionable operational insights in minutes. - Industry-specific specialization with tools, skills, connectors and knowledge specific for financial services and legal teams. - How we secure and govern agents through identity and policy management, authorization and permission controls, secure sandboxing, network gateways, and more. - Leading cost controls through multi-model orchestration, Smart Routing, real-time spend caps, and more. - Customer use cases that showcase the breadth and depth of our customers around the world. Bringing the best technology to all of you is what drives us at Google Cloud. In the last year, nearly 500 Google Cloud customers each processed more than one trillion tokens. Today, nearly 80% of all Google Cloud customers are using our AI products, and nearly 90% of the Fortune 100 use Gemini Enterprise. At that kind of scale, organizations have moved past experimentation and are running their business on it. Work now starts in the prompt window. To meet this moment, today we are excited to announce the Gemini agent: your new single, universal agent for work. It has all of your business context and can be used for everything from knowledge work to answering questions, and from content creation to coding, all from a single prompt box. It plans the work, uses skills and tools, connects to your systems, and brings back something finished — inside the documents, the inbox, and the developer environments you already work in. It chooses the best model for the job, has built-in cost controls, and most importantly, has the security, administration, and governance required by your company. The Gemini agent is your new single, universal agent for work. Introducing the Gemini agent Gemini answers your questions, handles your knowledge work, creates your images and media, and writes and runs code — all in a single agent and a single API. You give it objectives, not instructions. You delegate an outcome and come back to finished work. For an agent to do that, it has to be connected to your personal workflows, your systems of record, and your enterprise controls. Gemini can function as your personal assistant or as a team member, where it works on behalf of a group of people, like a project manager within a team, or on behalf of a specific role in an organization, like an analyst in your finance department. The agentic capabilities in Gemini are built around core architectural principles: - Unified agent: Gemini is an agent that can answer your questions when you chat with it, work autonomously to complete objectives you assign it, and generate code — all from a single interface. You can assign it work, schedule tasks that need to be completed, or have it respond to events. - Omnipresent access: Gemini can be accessed from any device including web, iOS and Android mobile devices, Windows and Mac desktops, and any channel (command line, Google Workspace, Microsoft 365, or Slack). It can also be integrated into third-party applications and surfaces and operates as a headless agent, meaning it does not need a dedicated user interface. - Persistent execution: It runs in the cloud, meaning it maintains a single set of memories, context, and one personalization graph no matter what device or channel you access it on. You never have to re-brief it or wonder which machine you told it to do something on. Work that takes hours or days keeps running after you close your laptop, and it is still there when you come back. - Multi-agent orchestration: Gemini doesn’t work alone. It can dynamically create a roster of sub-agents — temporary, job-specific agents, each with their own identity — to tackle multi-step tasks. Gemini can communicate with these sub-agents to coordinate workflows, including parallel and sequential steps that can run for hours or days. In addition, Gemini can act as a coworker agent — which is more like a team member, with a persistent, defined role and operational presence across days, sessions, and multiple changing responsibilities — and delegate and coordinate tasks. Coworker agents have dedicated identities including their own @agents.company.com emails, their own persistent storage, and only have access to the context that you or your team members provide. - Deeply contextual: Gemini arrives already knowing your tools, data, and work history. Whether you ask it a question, assign it an objective, or have it generate code, Gemini learns from every interaction with you. The longer you collaborate with it, the better it understands you and how you work. Teams can create dedicated projects to further optimize the context, skills, and tools Gemini uses when it works with you. - Model choice flexibility: Gemini is the agent, and the model underneath it is a separate choice. It runs each job on the model that fits best — orchestrating across our Gemini family of models and Claude models from Anthropic today, and other leading private and open models in the future — to deliver optimal quality and lower your costs. The best model for the task is not always the largest one. Matching the model to the work raises accuracy on the difficult jobs and lowers cost on the simple ones. And the leading model changes every few months, so keeping that choice open means your context, your skills, and your data stay put when it does. Top customers across industries were early testers and are already realizing its benefits: Premium sportswear brand On tested this new dynamic selection capability to accelerate its speed-to-market. This builds on the proven, large-scale multi-model strategies already used by leaders: Shopify blends frontier models for millions of merchants to unlock data and drive sales, and PayPal routes 10 million multi-model requests every week. Powering Gemini: Skills, tools, and context Gemini understands your business — everything from pricing to product portfolios to departmental norms — and all the institutional knowledge that makes your company unique. Three capabilities make that possible: tools that connect it to your systems, skills that teach it how your work gets done, and context that lets it remember. - Tools and tools registry: Gemini can securely connect to the software your company already runs, including collaboration tools like Confluence, Microsoft Office, Teams, Slack, and Workspace; development tools like Git and Jira; enterprise platforms like Salesforce and ServiceNow; databases like BigQuery, Databricks, Postgres, and Snowflake; and files on your own desktop. It can also connect and work securely with any Model Context Protocol (MCP) server inside or outside your company network. It also offers an enterprise tools registry, so teams can build and publish tools for the rest of the company. - Skills and skills registry: Skills are reusable sets of instructions, knowledge, or workflows stored as modular prompts that teach agents how to perform specific, multi-step tasks. Gemini ships with a robust global library of skills. Teams or departments can build and publish custom skills to a shared company registry, and you can build your own personal skills. Gemini chooses the right skills and tools to perform a task and continuously learns from each execution, improving its consistency, while saving token costs. - Context and memory: Gemini learns from each question you ask it, each objective you assign it, the people you work with, and uses your personal context and your organization's context to personalize and improve the quality of its responses. It keeps four kinds of memory: session memory for the task in front of it, even when it runs for days; semantic memory, a structured knowledge base it builds as it reads documents, talks to people, and works with other agents; procedural memory for how a job gets done, including skills it writes for itself; and episodic memory of everything it has done before. Gemini onboards itself the way a new hire would, learning you, your tools, and your team before it starts. Customers seeing significant benefits from Gemini Enterprise include: - BNP Paribas, a European leader in banking and financial services, is transforming Corporate & Institutional Banking by deploying Gemini Enterprise into LLM@CIB, its internal generative AI assistant available to more than 65,000 employees, to streamline workflows like preparing credit memos and boosting the productivity of customer advisers while maintaining strict enterprise-grade security and data governance. - Bradesco, one of Brazil’s largest banking and financial services conglomerates, is streamlining heavy operational workflows by deploying Gemini Enterprise for automated fiscal, accounting, and contractual analysis. The finance team has accelerated proposal reviews, service classification, and budgetary workflows, cutting document review time from 1 hour to 5 minutes while reducing risk inconsistencies by 60% and achieving over 10% in financial efficiencies. - Merck is exploring new frontiers in molecular research with the potential to significantly compress discovery timelines while maintaining complete data privacy and security. - Orange Spain, a leading telecommunications operator in Spain, is speeding up its digital transformation by deploying more than 1,000 custom Gemini Enterprise agents. Employees across HR, IT, sales, and customer service have built custom agents to automate incident triage, analyze network issues, and retrieve corporate knowledge, boosting operational agility and response times while helping non-technical staff automate daily workflows with zero IT bottlenecks. - Santee Cooper, South Carolina’s state-owned electric and water utility, is modernizing its financial planning and grid reliability by deploying a specialized AI model built on Gemini Enterprise. Financial planning teams and utility operators are automating complex financial scenario modeling and query execution using simple natural language and expect to boost modeling speed by up to 75% while mitigating market risk across a $10 billion grid expansion budget. - SOMPO, a leading Japanese insurance provider, built over 10,000 custom AI agents across its 34,000 employees to automate tasks like document search and summarization for employee efficiency. Their engineering team used Gemini Enterprise to cut the development time for new models from one week to a single day, freeing up engineers for more important work. - Ulta Beauty is helping guests shop 30,000 products by deploying the Ulta AI shopping assistant built with Gemini Enterprise. Online shoppers have translated conversational questions into personalized beauty recommendations, boosting digital sales conversion rates three-fold while skipping traditional search filters to buy the products they love instantly. - Wesfarmers, the parent company of Australian retail giants Bunnings, Kmart, and Officeworks, is deploying agents across its portfolio. An internal agent at Bunnings saved staff half a million hours of administrative work, while shopping agents — that help customers discover products and build their carts — have increased conversion rates up to three times higher for Kmart and Officeworks. Organizations worldwide are driving measurable impact. Gemini in Google Workspace Gemini not only answers your questions, handles your knowledge work, and writes your code — it works directly inside Gmail, Drive, Docs, Slides, Sheets, Chat, and Calendar, carrying the same memory, skills, and controls it has everywhere else. It works inline: in the email thread, in the document, and in the chat space. Inside Workspace, Gemini works three ways: - Personal assistance: Gemini works as your personal agent and arrives already knowing your calendar, your team, your projects, and how your documents relate to one another. It is briefed before you start. For example, you can ask Gemini to set up a meeting with the usual team of regional event leads next week, without supplying a single name or email address. Gemini determines who those people are from the membership of your chat space and the thread from your last event, checks their calendars, and starts an email thread to coordinate a time that works, even with external participants. It handles work that spans applications the same way: researching market trends, building a financial model in Sheets, then creating a deck that presents both, without you re-explaining the project at each step. - Proactive delegation: Gemini uses this same intelligence to proactively suggest tasks you can delegate to it. For example, if your manager emails you asking for the latest project update as a slide deck, Workspace Intelligence recognizes that as a delegatable task and gives you a single-click option to pass it to Gemini. It applies the same reasoning to your inbox, surfacing the message that matters most rather than the one that arrived last, and explaining why. - A member of your team: You can also use Gemini to create a coworker agent that works with your entire team. You simply describe the role you need, and Gemini creates it. The agent receives its own Workspace account, including an email address, calendar, Drive, and presence in your company directory. Your colleagues work with it the way they work with anyone else, by adding it to a Chat space or @mentioning it. For example, a marketing manager can ask an events coordinator agent in a chat group to draft a launch readiness document, which it posts back to the group when complete. The marketing manager could also tag the agent in a document comment, where it can suggest an edit in the Doc and reply in the comment thread, appearing under its own name in version history. A coworker agent acts under its own identity rather than yours, and it sees only what you share with it. Access follows the sharing and membership your team already uses, and no outside connector holds your data. Data analysis, data engineering and machine learning We are also giving Gemini skills built for specific domains, starting with data. Data and analytics represent a foundational domain where Gemini transforms business workflows, enabling organizations to move from plain-language questions to actionable operational insights in minutes. We are introducing purpose-built capabilities tailored to both technical teams and everyday business users: - For Data and ML engineers: We are extending Gemini with machine learning skills and tools that back every data scientist and data engineer with a team of agents. Engineers describe the outcome they want in plain language, and Gemini generates PySpark code, provides notebooks to edit and test it, trains models, and troubleshoots and fixes pipeline issues on its own. - For business users: Anyone in your organization can generate reliable, real-time operational reports simply by asking. Gemini uses operational reporting skills integrated with BigQuery and the Knowledge Catalog to construct and save the query. Once saved, teams can run reports on demand without incurring token costs, guaranteeing consistent, verified answers every time. Three Google Cloud capabilities keep those answers grounded: - Knowledge Catalog: Gemini integrates directly with your Knowledge Catalog to map business definitions once so all agents use them. This deep understanding of your organization’s schemas and business rules for terms like “net margin” and “addressable market” dramatically improves accuracy. Whether your metrics live in Databricks, dbt, LookML, or SAP, Gemini reads them directly where they sit to ensure factual responses. - Smart Storage: Ninety percent of enterprise data is unstructured — PDFs, images, scans, and audio recordings — which often remain "dark" and unreadable. Smart Storage changes this by enriching unstructured objects in place and writing context back directly onto the object itself. The intelligence stays where the bytes reside and inherits your existing security posture. - Borderless Lakehouse: Organizations should not be forced to move or duplicate their data to use AI. Our borderless Lakehouse allows Gemini to query Amazon S3 and Azure Data Lake with no variable egress fees, read directly from Salesforce Data 360, SAP, ServiceNow, and Workday without copying data, and federate open Apache Iceberg tables across Databricks Unity, Snowflake Polaris, and AWS Glue. You can start by registering data sets that you discover in your lakehouse with the Knowledge Catalog, and then assign Gemini simple or complex analysis to perform. It identifies the necessary data sets from the Knowledge Catalog, generates the necessary SQL, Spark or Python code to calculate the results, and runs the code on our Managed Spark Service with Lightning Engine or in BigQuery. It can also generate charts and build dashboards in the tools your analysts already use. By grounding its data agents in the Knowledge Catalog, Bloomberg Media lifted its SQL query accuracy by 63% during initial development. As William Anderson, Bloomberg Media’s CTO, noted: “...by grounding our AI in a trusted institutional context, we ensure confidence in the accuracy and quality of every insight generated.” Additional customers are seeing tremendous value from our data solutions: - Deutsche Telekom used BigQuery, Cloud Storage, and Knowledge Catalog to build a unified data lakehouse to overcome a fragmented and slow data infrastructure spread across 40+ legacy on-premise systems, allowing their teams to now move ten times faster while addressing European data sovereignty and security requirements. - Etsy migrated three petabytes of data to a unified lakehouse. By using BigQuery and open-source Apache Iceberg, they can now perform critical data joins up to 60% faster, allowing them to train models on much larger datasets and better connect buyers with the perfect items. - Snap connected its Prism agent directly to its storage archives, cutting technical diagnostic troubleshooting times down from 30 minutes to just 30 seconds. Industry-specific specializations Every industry runs on knowledge a general model does not have. We are specializing Gemini for individual industries, with the skills, tools, and knowledge specific to each one. It is now in preview for Financial Services and Legal, and coming soon to Government, Healthcare, and Retail. - Financial Services: Gemini for Financial Services automates what is usually pieced together across many workstreams: investment research, credit analysis, and risk modeling. It draws on trusted financial data from FactSet, LSEG, SEC filings, and your own proprietary repositories. Built with more than 50 foundational skills and designed to satisfy rigorous compliance, it shows its reasoning through confidence scores, explicit methodologies, full data lineage for easy auditing, and source citations you can check. Gemini for Financial Services is already being used by global financial institutions like CME Group and Deutsche Bank. - Legal: Gemini inherits matter-level permissions and ethical walls directly from document management platforms like NetDocuments and iManage. Partners like Harvey automate complex legal work while meeting the firm's confidentiality standards, while Onit streamlines contract lifecycle management without exposing privilege. Cooley is building a confidential information redaction agent on Gemini Enterprise for Legal that automates redactions, including personally identifiable information and confidential material, before legal filings go public. In high-stakes litigation, this can cut days of document review while maintaining the firm's rigorous standards for client confidentiality. In addition, we’ve seen our ecosystem and customers create new vertical applications as well. For example, Deloitte has created a multi-agentic solution to help organizations identify the highest-value opportunities for AI applications for their business. Their Agentic AI blueprint develops operational heat maps to pinpoint areas ready for agentic redesign, accelerating the deployment of custom agentic workflows and achieving up to a 3x faster path to measurable business impact. Securing and governing agents Two factors determine whether an enterprise agent program succeeds or stalls: whether you can govern it, and whether you can afford it. When deploying autonomous agents across an organization, governance comes down to answering four fundamental questions: - Who is the agent, and what identity does it have? - What is it allowed to do or what permissions is it granted? - What did it do and where can I see what it did? - What should it never touch? Identity, policy, and observability answer the first three. The fourth is Agent Gateway. - Identity: Every agent gets its own identity, cryptographically attested and governed like an employee, with least-privilege permissions. That identity is stamped into the logs that capture its work, and into any virtual machine spun up to run code on its behalf. - Authorization and permissions: You give each agent fine-grained, role-based access permissions, approved by your organization’s security administrators. When the Gemini agent connects to an external system, its identity is mapped and propagated through industry standards such as OAuth. - Auditing: In addition, every action Gemini takes is written to an audit trail and attributed to the agent rather than to a person. Since the identity travels into any virtual machine the agent spins up to run code, you can monitor those logs with our observability tools in real time and catch anomalous behavior before it matters. - Policy management and control: Gemini gives you identity, discovery, governance, and security by default. All Gemini agents execute tasks safely inside an Agent Sandbox with its own network boundary. All traffic — in, out, and between agents — passes through Agent Gateway, an AI network firewall enforcing your organization’s policies in real time. You write the policy once, such as: “agents may not open documents classified Need to Know.” Gemini applies it to every agent in your company instead of checking one agent at a time. Leading cost controls and spending options While per-token prices have dropped 98% since 2024, enterprise AI volume has exploded. Running every simple loop through a premium model quickly breaks corporate budgets. We announced new flexible spending options recently and are adding to those today: - Multi-model orchestration: As mentioned earlier, Gemini allows you to choose the right model for the job, and even combine different models for specific tasks in larger projects to deliver optimal quality and lower your cost. - Smart routing: Our routing tool automatically triages enterprise workloads so each one runs on the model that delivers maximum performance at the lowest possible cost. - Real-time spend caps: You can set a hard limit on a project's AI spend in the Cloud Billing Console, and Gemini enforces it. Gemini monitors token usage and sandbox costs, and if a spend cap is triggered, that project's agent pauses, and you can choose to resume work with a single click in the console. Because the tracking is per project, companies can charge AI costs back to specific departments. Infrastructure: 80% better price-performance All of this innovation — the agent, the data, the identity, and everything else — runs on our AI Infrastructure and our models. They are the reason the economics work. First, our AI infrastructure. We co-design the chips, the network, the data center, and the software that connects it all as one highly-optimized system — our AI Hypercomputer. This vertical integration delivers significantly better price-performance than the generic setups, and we are continuing to push the state of the art here. For example, our latest TPU 8i system delivers 80% better price-performance than the prior generation, making complex, high-value agent tasks both fast and highly affordable. On top of this silicon sit our models: Argon for frontier reasoning, Flash for speed and volume, Omni for generative media, and Gemma for lightweight, open-weights edge workloads. The edge capabilities are already real. NASA’s Jet Propulsion Laboratory is running Gemma directly on a satellite in orbit, a first for a vision-language model. JPL’s NAVI software analyzes Earth imagery on board the satellite and sends a summary with key information to ground operators. Supercharged by our ecosystem We remain committed to choice at every layer of the stack, ensuring you have the freedom to choose the best tech stack for your unique needs. Inside Gemini, you have a broad choice of third-party agents from leading SaaS providers as well as connectors that are ready to use. They are even easier to discover as collections in the new AI Solution Finder. Around Gemini, our services ecosystem continues to rapidly scale to meet enterprise demand. Together, in the last month alone, our global consulting partners have put more than a hundred thousand of their developers and consultants through Gemini hackathons. In addition, Accenture has made a significant investment by establishing a dedicated Gemini Enterprise Business Group to accelerate customer adoption and innovation. Several other partners have also expanded their commitments to support the growing demand for Gemini, including establishing specialized centers of excellence and training Gemini credentialed practitioners to help customers build and deploy production-grade agents faster. Gemini Enterprise in action: Global momentum Organizations worldwide are driving measurable impact across every major region: Europe and Middle East - Arden University, a UK provider of flexible online and blended learning, is preparing students for the global job market by rolling out Gemini Enterprise. Over 30,000 students and staff will now have access to advanced Al tools to personalize their studies and gain essential skills for the workplace. - Commerzbank, one of Germany’s largest private banks, is using Gemini Enterprise to automate document quality assurance, reducing manual work on document reviews from 20 hours to just one. They are expanding this with a multi-agent system for AI-driven QA. - Lloyds Banking Group is scaling agentic AI across the bank. Envoy, a secure, Gemini-powered pipeline, has already onboarded nearly a thousand engineers building production-ready AI use cases. From fraud detection to commercial client onboarding, Envoy gives teams a reusable agent marketplace, a "golden path" for building agents, and a CI/CD pipeline — all wrapped in the guardrails and security a highly regulated bank demands. - Nokia is tackling the complexity of modern telecom networks with an ecosystem of specialized agents built on Gemini Enterprise. This allows operators to fix issues before subscribers are impacted by automating troubleshooting and cutting issue resolution time by up to 80%. - On, a premium sportswear brand, is scaling workforce productivity and efficiencies by deploying Gemini Enterprise to every employee to drive personal productivity and foster an AI-ready culture. Team members have launched no code agents that help with efficient knowledge extraction, executive reporting, market research, scheduling, onboarding and more. - Ooredoo Qatar, the leading telecommunications provider in Qatar, is integrating Gemini Enterprise into their AI transformation strategy to drive advanced automation and intelligence. Its customer support, marketing, security, and field operations teams have deployed AI agents to optimize internal operations management, while accelerating rapid issue resolution and marketing campaigns to deliver around the clock, highly personalized, proactive customer experiences. - Qatar University, the nation's premier institution of higher education, is transforming higher education operations and academic research by deploying Gemini Enterprise campus-wide. Thousands of faculty and staff are deploying more than 2,000 custom AI agents to modernize institutional workflows, automate complex administrative operations, and enhance academic productivity. - Ryanair, Europe’s largest airline, is modernizing its collaborative operations and infrastructure by deploying Gemini Enterprise and Google Workspace to 35,000 employees. Flight crews, operations planners, and corporate staff will benefit from automated decision-making, optimized crew logistics, and enhanced corporate productivity, while a resilient dual-cloud strategy strengthens infrastructure resilience and supports the airline's target growth to 300 million passengers by 2034. - Starling, one of the UK's top-rated digital banks, built its Scam Intelligence tool on Gemini Enterprise. It analyzes online marketplace ads for suspicious content and has quadrupled the rate at which customers cancel potentially fraudulent payments. - Other major European customers include Berenberg in banking, Bouygues Telecom, the application building platform Lovable, and Siemens in automation. Asia Pacific - Airwallex, the global financial platform processing over $200 billion annually, has deployed Gemini Enterprise across its infrastructure to resolve customer issues 10x faster, automate dispute handling to cut case time by 40%, and accelerate software time-to-market by over 95% while building speci