Google Cloud Next 2025, held in Las Vegas from April 9th to 11th, showcased a surge of advancements, primarily focusing on AI agents and significant performance improvements across its cloud infrastructure. The event underscored Google's commitment to making AI more accessible, efficient, and integral to business operations. CEO Thomas Kurian emphasized that AI is no longer just a vision but a tangible reality, with Google Cloud dedicated to providing the tools and infrastructure necessary for organizations to thrive in this new era.

A major theme of the conference was the unveiling of new AI agents and tools designed to simplify complex tasks and enhance productivity. Google introduced the AI Agent Development Kit (ADK), an open-source framework intended to streamline the creation of sophisticated multi-agent systems. This kit empowers developers to build Gemini-powered agents capable of reasoning, utilizing tools, and performing multi-step tasks. Moreover, the ADK supports the Model Context Protocol (MCP), enabling seamless interaction between AI models and diverse data sources, eliminating the need for custom integrations. Google also announced an Agent2Agent (A2A) protocol to facilitate communication between agents, regardless of their underlying model or framework, fostering a multi-agent ecosystem. Key partners like Atlassian, Salesforce, and ServiceNow are supporting this initiative.

Google's AgentSpace platform received considerable attention, with new features aimed at scaling the adoption of enterprise search and AI agents. AgentSpace combines Google's search capabilities, conversational AI, and Gemini models, providing employees with tools to access and synthesize information, converse with AI agents, and automate tasks within their enterprise applications. New additions include an Agent Gallery, a no-code Agent Designer, and specialized agents for idea generation and deep research. Workspace also benefits from AI, with features like "Help Me Analyze" in Sheets and Workspace Flows for task automation.

The Customer Engagement Suite saw significant upgrades, featuring human-like voices, emotion recognition, streaming video support, and a no-code interface for building AI agents. The goal is to enable more personalized and efficient customer interactions across various channels. The next generation of Conversational Agents will leverage the latest Gemini models and Agent Development Kit, along with enterprise-grade features such as privacy controls and AI observability. These power a no-code console that enables even non-technical employees to build complex conversational AI agents.

Performance improvements were another key highlight of Google Cloud Next 2025. Google announced its seventh-generation Tensor Processing Unit (TPU), named Ironwood, designed to accelerate machine learning workloads. Ironwood boasts a 10x performance increase compared to previous TPUs and is significantly more energy-efficient. For AI inference, Google introduced new capabilities in Google Kubernetes Engine (GKE), including Gen AI-aware scaling and load balancing, which can reduce serving costs, decrease tail latency, and increase throughput. Pathways, Google's distributed ML runtime, is now available for cloud customers, enabling state-of-the-art multi-host inferencing for dynamic scaling. Google is also bringing vLLM to TPUs, allowing customers to run PyTorch workloads on TPUs cost-effectively.

Google's AI Hypercomputer architecture has been upgraded for better performance, efficiency, and cost-effectiveness, leading to more intelligence per dollar, as seen with Gemini 2.0 Flash. For organizations requiring on-premises solutions, Google Distributed Cloud (GDC) now supports Gemini models through partnerships with NVIDIA and Dell.

The conference also highlighted advancements in Google's network infrastructure with the introduction of Cloud Wide Area Network (WAN), making Google's global private network available to enterprises. Cloud WAN offers improved network performance and reduced total cost of ownership. These advancements collectively demonstrate Google Cloud's focus on delivering a comprehensive AI platform with enhanced performance, simplified development, and broad applicability across various industries.