Google Cloud Next 2025: Ushering in the AI-Powered Cloud Era

Google Cloud Next 2025 marked a clear shift toward embedding artificial intelligence into every layer of the cloud, from infrastructure and tools to the everyday work experience. With an array of major announcements, Google Cloud laid out its vision to make advanced AI more accessible, useful, and impactful for businesses and developers alike.

This year’s event wasn’t just about showcasing new products. It was a clear statement of intent. Google’s leaders like Sundar Pichai and Thomas Kurian emphasized that AI is no longer a futuristic idea - it’s becoming a practical tool driving real change across industries. And, t`he numbers back that up;Vertex AI usage has grown twentyfold in the past year. Case studies and customer stories presented at the event highlighted how organizations are already using these tools to solve real-world problems. This kind of momentum shows that AI is entering a more mature phase, where it’s not just about innovation but about impact.

Building a Smarter Backbone: AI Hypercomputer and Ironwood TPU

One of the biggest highlights was the introduction of the AI Hypercomputer, a high-performance computing system purpose-built for AI workloads. It’s a combination of new hardware and software designed to run AI models faster and more cost-effectively.

Leading this effort is the Ironwood TPU, Google’s seventh-generation Tensor Processing Unit. Ironwood offers more than 10 times the performance of the previous generation and a jaw-dropping 3,600 times more than Google’s first TPU. Each Ironwood pod packs over 9,000 chips, together delivering 42.5 exaflops of compute power. This means developers can train and run much more complex models, helping businesses stay ahead in a fast-moving AI landscape.

On top of that, Google Cloud is expanding its GPU offerings. It’s the first cloud provider to support both NVIDIA’s powerful B200 and GB200 Blackwell GPUs, and it’s preparing to launch the upcoming Vera Rubin GPUs too. This range gives users the freedom to choose between Google's TPUs or industry-leading GPUs based on their specific needs.

Smarter Storage to Match the Speed

AI models need to access data quickly to perform well, and Google Cloud addressed this with several storage innovations. These include Hyperdisk Exapools for massive performance and capacity, Anywhere Cache for faster data access, and Rapid Object Storage designed for low-latency reads and writes. These features are key to reducing training time and improving how responsive AI-powered applications can be.

The Power of Gemini: Next-Gen AI Models

Google also expanded its family of Gemini models. Gemini 2.5 Pro has claimed the top spot on the Chatbot Arena leaderboard and even scored the highest ever on Humanity’s Last Exam, a test designed to measure advanced reasoning. Meanwhile, Gemini 2.5 Flash is optimized for low-latency and affordability, making it ideal for high-volume use cases.

Both models now support “thought chaining,” a feature that allows them to perform multi-step reasoning. By offering both a high-performance version and a budget-friendly one, Google Cloud is making sure that enterprises can access advanced AI models no matter their needs or resources.

Generative AI for Every Creative Medium

In the creative space, Google Cloud showed off significant upgrades to its multimodal generative AI tools. Imagen 3 improves image quality and adds the ability to repair missing or damaged parts of an image. Chirp 3 can generate realistic voice samples from just 10 seconds of audio and offers better transcription accuracy. Lyria, a text-to-music model, converts short text prompts into 30-second musical compositions, while Veo 2 now supports advanced video creation and editing features like cinematic effects and inpainting.

Even more notable is their integration with tools like Adobe Express, making these models readily available to creative professionals and streamlining workflows across industries like marketing and entertainment.

AI in Science and Research

Google Cloud is also putting its AI tools to work in scientific research. AlphaFold 3, developed with DeepMind and Isomorphic Labs, can now predict how molecules interact—something that could be game-changing for drug discovery and biotech. A new high-throughput version of AlphaFold 3 is available via the Google Cloud Cluster Toolkit.

In addition, WeatherNext models, created with Google Research and DeepMind, are now available through Vertex AI Model Garden. These models offer fast, accurate weather predictions, showing how AI can help tackle some of the most complex challenges in science and the environment.

Vertex AI: The Command Center for AI Innovation

At the heart of all this progress is Vertex AI, Google Cloud’s unified platform for training, deploying, and managing AI models. Usage has exploded—twenty times more overall and forty times more for Gemini models. The Model Garden now features over 200 models, including Google’s own, open-source options, and third-party offerings.

Vertex AI has also added tools that make AI integration easier, like grounding features that improve factual accuracy by connecting models to trusted sources, and Vertex AI Dashboards for monitoring and performance tracking. The platform even supports real-time streaming into Gemini and cost-effective execution of PyTorch workloads using TPUs. These improvements make Vertex AI an even more critical piece of the puzzle for companies building production-ready AI solutions.

The Agentic Era: Multi-Agent AI Comes to Life

A major theme at Google Cloud Next 2025 was the emergence of multi-agent AI systems, networks of AI agents working together to complete complex tasks. This new era is being powered by two key launches: the AI Agent Development Kit (ADK) and the Agent2Agent (A2A) protocol.

ADK, an open-source framework, allows developers to build smart AI agents with fewer than 100 lines of code. It includes Agent Garden, a library of over 100 prebuilt connectors for tools, APIs, and cloud databases like BigQuery and AlloyDB. Developers can even build agents that work directly on their NetApp data without copying it elsewhere.

The A2A protocol is an open communication standard that allows AI agents, regardless of their underlying technology, to talk to one another. Over 50 partners have already joined the effort, paving the way for a more open and interoperable AI ecosystem.

Google Agentspace: AI for Everyone in the Enterprise

In terms to bring these agent capabilities to every employee, Google introduced Google Agentspace. Integrated with Chrome Enterprise, Agentspace lets workers interact with AI agents directly through their browser’s search bar. Features include an Agent Gallery showing all available agents and an Agent Designer that lets users build their own AI helpers without writing code.

Built-in agents like the Idea Generation agent and Deep Research agent help employees brainstorm, prioritize, and explore complex topics more effectively. This move is part of Google’s broader strategy to embed AI directly into everyday tools, boosting productivity and decision-making across entire organizations.

A Unified Approach to Security

AI is also playing a big role in security. Google introduced Google Unified Security (GUS), a single platform combining threat intelligence, AI-driven agents, and cloud services to improve detection and response.

Security-specific AI agents now assist with alert triage and malware analysis, even writing scripts to identify obfuscated threats. Additional tools include Audit Manager, enterprise browsing protections on Android, and Mandiant Retainer for emergency response. Google also announced advancements in Confidential Computing and Sensitive Data Protection, making it clear that securing AI and cloud environments is a top priority.

Cloud WAN: Google’s Private Network, Now for Everyone

To support global connectivity needs, Google launched Cloud WAN, making its massive private fiber network, which spans over 200 countries available to enterprises. The result? Over 40% better performance and up to 40% lower total costs. Early adopters like Nestlé and Citadel Securities are already seeing the benefits. This could signal a shift in how enterprises build and manage their networks, favoring cloud-based models for speed and efficient           .

Final Thoughts

Google Cloud Next 2025 made it clear that Google is all-in on AI, and it’s not just talk. From foundational hardware like the Ironwood TPU to practical tools like Agentspace, Google is offering a full stack of solutions designed to make AI real, useful, and scalable.

What sets Google Cloud apart is its commitment to openness and interoperability, as seen in efforts like the A2A protocol and broad model support in Vertex AI. Add to that a focus on industry-specific solutions and real customer success, and it’s easy to see why Google Cloud is positioning itself as a leader in the AI-powered future of cloud computing.

For businesses and developers alike, the tools unveiled this year offer new ways to build, innovate, and grow. And as AI continues to evolve, platforms like Google Cloud will be key to turning potential into progress.