Overview:
Google Cloud's Agentspace helps businesses build AI agents that search company data, plan tasks, and automate workflows.
Companies like Telus, Suzano, and Danfoss report faster operations and major time savings through AI automation.
Google Cloud is investing heavily in AI infrastructure and shared protocols to help agents work across different platforms.
Artificial intelligence used to mean a chatbot that answered questions. That era is fading fast. Companies today want software that plans a task, carries it out, and reports back without constant supervision. Google Cloud has built its entire strategy around this change, and the shift is visible in nearly every product it ships.
The company's push covers custom chips, language models, cloud infrastructure, and office software. Sundar Pichai called this period a fundamental rewiring of technology at Google Cloud Next 2026. Those words sound bold, but the products behind them are already running inside banks, logistics firms, and manufacturing plants. Agentic AI is no longer a side project at Google Cloud. It sits at the center of the company's growth plan.
A Platform Built for the Agentic Era
Agentspace is Google Cloud's main offering for businesses that want AI agents at work. It launched in preview at Google Cloud Next last year and reached general availability soon after. The platform gives employees one place to search, plan, and get tasks done.
It pulls data from Google Drive, SharePoint, Jira, Confluence, Salesforce, and Box. Staff can search text, images, video, and audio files at once. Nobody has to jump between ten different apps to find one document anymore.
What Agentspace Offers Teams
A search tool that works across every connected company system
Agent Designer, a no-code builder for custom AI agents
Results and permissions tailored to each employee's role
Ready-made connectors for HR, sales, engineering, and marketing work
Smaller firms without big engineering teams can still build working agents. This matters because AI automation was once limited to companies with deep technical budgets. Google Cloud is trying to close that gap.
Real Results from Early Adopters
Google Cloud shared customer numbers in its 2026 business trends report, and a few stand out. These figures come from the company itself, so they deserve a careful read rather than blind trust.
Telus now has over 57,000 employees using AI tools regularly, saving about 40 minutes per task.
Suzano built an agent that turns plain questions into SQL code, cutting query time by 95% for 50,000 workers.
Danfoss automates 80% of order-processing decisions, dropping customer response time from 42 hours to near-instant.
Macquarie Bank sent 38% more customers to self-service while cutting false security alerts by 40%.
Each case points to the same pattern. Repetitive, rules-based work is moving away from human hands and into agent workflows. The time saved is being redirected toward judgment calls that still need a person.
Also Read: Claude Comes to Google Workspace: What it Can do in Docs, Sheets and Slides
Why Agentic AI is Growing So Fast
The scale behind these results is hard to ignore. The Gemini app reached 750 million monthly users by the end of 2025, up 100 million in just one quarter. Developers are building on top of this growth too, with the Gemini API handling 85 billion requests in January 2026 alone.
Paid adoption looks strong as well. Google Cloud counts 8 million paid Gemini Enterprise seats spread across 2,800 companies. Cloud revenue crossed USD 70 billion for the year, up 48% from the year before, with a booked backlog of USD 240 billion.
Pichai has talked about Google Search turning into something closer to an agent manager. Instead of returning links, it would dispatch an AI agent to finish the task directly. Many searches people run today are really requests to get something done.
Google Cloud is also working with Salesforce on a shared standard called the Agent2Agent protocol. It lets agents built on different platforms talk to each other and share a task. A related effort, the Universal Commerce Protocol, brings in Shopify, Target, and Walmart to let agents complete purchases on their own.
Business Functions Seeing the Quickest Change
Customer support, where scripted bots are giving way to personalized service
Security teams, where agents handle alert triage so analysts can hunt real threats
Finance departments, automating approvals and order processing at scale
Training programs, shifting from single courses to ongoing, adaptive learning
What this Means Going Forward
Google Cloud still trails the market leaders in raw share. It holds about 11% of cloud infrastructure, behind Amazon Web Services at 31% and Microsoft Azure at 25%. Thomas Kurian, who leads Google Cloud, has argued that competitors sell scattered tools while his company offers a connected platform.
Spending plans back up that confidence. Google expects to invest between USD 175 billion and USD 185 billion in 2026, nearly double what it spent the year before. That kind of commitment signals a company betting its future on agents becoming a permanent fixture of office work.
Final Words
Google Cloud has turned AI agents from a research idea into something companies use every day. Agentspace, Vertex AI, and shared protocols like Agent2Agent work together rather than standing apart. The customer numbers, while self-reported, still point to real time and cost savings across several industries.
What stands out most is the direction of travel. Tasks that once needed a full team now run through a single agent with light oversight. As more platforms adopt shared standards, this approach may well become the normal way large businesses operate within the next few years.
Also Read: Cloud Layoffs Hit Google as Tech Giants Redirect Billions Toward AI
FAQs
1. What is Google Agentspace used for?
Agentspace is a workplace tool that combines search and AI agents in one place. It connects to apps like Drive and Salesforce, helping employees find information and automate routine daily tasks securely.
2. How does Vertex AI support Google's agent strategy?
Vertex AI gives businesses the infrastructure to run agents at full scale after testing them in Agentspace. It handles the heavier technical work needed once an agent moves from pilot to production use.
3. What does the Agent2Agent protocol actually do?
It is a shared standard built with Salesforce that lets agents from different companies work together. This allows one business process to pass smoothly between agents built on separate platforms.
4. Which industries have adopted AI agents the fastest?
Banking, logistics, customer support, and security operations show the quickest uptake. Companies like Danfoss and Macquarie Bank report faster response times and fewer manual tasks after rolling out agents.
5. Can smaller companies use Google Cloud's AI agent tools too?
Yes. Agent Designer offers a no-code option, so companies without large engineering teams can still build working agents. This lowers the entry barrier that once limited agentic AI to bigger firms.