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aside_block ), ('btn_text', ''), ('href', ''), ('image', None)])]> The AI era demands a new security era. Organizations are facing the dual challenge of harnessing the potential of AI while defending against its malicious use, and Google Cloud can help you adapt and thrive. The latest research from
Significant contributors to this article include Megan O'Keefe, Senior Staff Developer Advocate, and Karl Weinmeister, Director of Developer Relations. Whether you are joining us in person in Las Vegas or tuning in virtually from around the world, Google Cloud Next '26 offers a deep look into the pr
As AI models improve, technical practitioners are increasingly turning to agentic AI tools to build with Google Cloud products, from Firebase and the Gemini API, to BigQuery and GKE. But how can you ensure that the model is equipped with accurate, up-to-date information about these technologies? One
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 year
The AI era requires a fundamental rethink of physical cloud architecture — networking, in particular. With foundational model parameters growing exponentially, traditional general-purpose networks are reaching their breaking points. To fuel the next decade of machine learning, Google designed Virgo
Today, we announced the preview of Spanner Omni, a downloadable version of Spanner, that expands its industry-leading distributed database capabilities beyond Google Cloud. This enables enterprises to run Spanner in their own data centers, across clouds, or on a laptop — bringing its virtually unlim
The era of agentic AI is accelerating from human- to machine-speed operations, while also creating profound stress on legacy technology infrastructure. This new reality pushes foundational systems to their limits: agents generate thousands of internal messages and complex queries, spawning more agen
At Google, our TPU design philosophy has always been centered on three pillars: scalability, reliability, and efficiency. As AI models evolve from dense large language models (LLMs) to massive Mixture-of-Experts (MoEs) and reasoning-heavy architectures, the hardware must do more than just add floati
By combining the analytical depth of Looker with Google’s Agentic Data Cloud, the potential to transform how we model, interact with, and act on our data appears limitless. This week at Google Cloud Next, we are thrilled to share how we are reimagining the business intelligence (BI) stack with Looke
Security teams are frequently burdened with manually stitching together telemetry, alerts, and response playbooks. This fragmentation can limit visibility, increase alert fatigue, and slow down investigations. Defending the modern enterprise requires tools that work together. Today at Google Cloud N
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 comp
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 ne
As we have deployed Gemini Enterprise across various industries over the last few months — including the world's most complex and heavily regulated organizations — a clear shift has emerged. Enterprises don't just need AI to answer questions or complete isolated tasks. They also need autonomous agen
In the agentic era, the role of enterprise data is shifting from a passive resource to a dynamic System of Action. That’s why we announced the Agentic Data Cloud — a unified architecture that integrates models, analytics, and operational databases into a single, AI-native system. This allows organiz
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 a
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 Desi
For decades, many of the world’s most critical enterprise datasets have relied on the performance of Oracle databases. Today, we are bringing that reliability even closer to the cutting edge. By enabling customers to run Oracle AI Database services natively within Google Cloud, we’ve bridged the gap
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
From vibe-coded and large-scale apps to AI models and agents, Cloud Run delivers on-demand compute with zero overhead and pay-per-use pricing for all of your workloads. Last year, the number of external active developers and applications on Cloud Run doubled, with more new customers and apps coming
This week at Google Cloud Next ‘26, we are sharing the evolution of Google Kubernetes Engine (GKE), delivering leading performance, efficiency, security, and scale for your most demanding and complex workloads, and the next generation of AI and agentic applications. Why it matters: Kubernetes has ra
