Cloud Computing

We are now seeing the Agentic Enterprise become reality for customers, and this week at Next ‘26 we are announcing exciting, new innovations to help customers accelerate agentic AI even further. Our partners play a critical role in enabling the Agentic Enterprise, and today we are also announcing new resources, technologies, and deep technical partnerships […]

Small businesses are the backbone of the global economy. With 400 million SMBs worldwide and 36 million in the U.S. alone, they provide 50% of global employment. Now, with Google Cloud AI, they’re scaling faster, operating more efficiently, and delivering better results for their customers.  For years SMBs have been working with cutting edge products

The future is taking shape in Las Vegas this week, where the world’s leading startups are showcasing their groundbreaking AI work at Google Cloud Next. Whether they need the top AI models, infrastructure purpose-built for the most demanding workloads, intelligent multi-model databases, or security and sovereignty solutions to grow with confidence — or all of

The agentic web — where autonomous AI agents reason, plan, and execute complex transactions using the open web and industry standard protocols — aims to create an autonomous customer experience. While these agents can significantly enhance online interactions, they also introduce new abuse and fraud vectors, creating unique challenges for security platforms.  This rise in

At Google Cloud Next, we are announcing innovations across every layer of our storage stacks — performance, intelligence, and management — to ensure your data is as fast and as useful as the AI models, apps and agents you are building. Why it matters: Storage is no longer just a place to keep data. When

At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matters: IT leaders and builders are faced with balancing compute investments and resources between agentic AI and the general purpose use cases, including

Traditional lakehouses were engineered for the era of reporting, not the high-velocity, multimodal demands of AI agents. To bridge this gap, architecture must evolve into an AI-native foundation — one that replaces batch processing with continuous feedback loops and live data streams. This shift gives agents the reliable context they need to transform raw data

Editor’s note: This is an adapted transcript of Thomas’ keynote remarks for Next ‘26 where we are announcing a number of new innovations including: Gemini Enterprise Agent Platform, a comprehensive platform to build, scale, govern, and optimize agents.  Gemini Enterprise app includes a new Agent Designer, Inbox for managing agent activity, long-running agents, Skills, Projects

The first wave of AI changed how we find information; the next wave is changing how we get work done. Today, we’re enhancing our most powerful AI tools and bringing them together under one roof.  Gemini Enterprise is now an end-to-end system for the agentic era, built for agents that can execute complex, multi-step work

Companies are shifting from gen AI that simply answers questions to autonomous agents that perceive, reason, and act on their behalf. Attempting to scale these agents on legacy stacks exposes structural failures that can lead to fractured governance, a persistent trust gap, and broken reasoning loops, all while causing costs to spiral. To solve this,