How Google just revamped Gemini Enterprise for the agentic era - here's what's new

2026-04-22 · Source: News and Advice on the World's Latest Innovations | ZDNET · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Cloud Computing & IT Infrastructure · Depth: Intermediate, short

Summary

Google has launched the new Gemini Enterprise Agent Platform for developers at its annual Cloud Next conference, evolving from Vertex AI. This platform integrates model selection, building, and tuning services with new features for agent integration, security, DevOps, and orchestration. It offers over 200 models, including Gemini 3.1 Pro, Nano Banana 2, Gemma open models, and Anthropic's Opus 4.7. Developers can design, scale, and govern agents, utilizing MCP support and an upgraded Agent Development Kit for complex tasks. The platform also features Agent Identity for cryptographic IDs and an Agent Simulation tool for stress-testing. Additionally, Google announced Agentic Data Cloud for scaling AI agents and Workspace Intelligence, which enhances Gemini's ability to automate tasks by understanding semantic relationships across Workspace apps and organizational knowledge.

Key takeaway

For CTOs and VPs of Engineering evaluating enterprise AI solutions, Google's Gemini Enterprise Agent Platform offers a unified, secure environment for developing and deploying autonomous agents. Your teams can leverage its comprehensive tooling, including over 200 models and built-in security features like Agent Identity and Agent Simulation, to manage complex agentic workflows with greater control and auditability. Consider integrating this platform to standardize governance and scale your organization's AI agent initiatives efficiently.

Key insights

Google's new Agent Platform streamlines secure, end-to-end agent development and deployment for enterprise AI workflows.

Principles

• Secure agent management is critical.
• End-to-end platforms simplify agent lifecycle.
• Layered agent design enhances complex task handling.

Method

Developers build agents using an Agent Development Kit, structure them into sub-networks for complex tasks, and stress-test with Agent Simulation before publishing to the Gemini Enterprise app for employee use.

In practice

• Use Agent Identity for cryptographic agent IDs.
• Employ Agent Simulation for pre-deployment testing.
• Leverage Agentic Data Cloud for scalable data access.

Topics

• Gemini Enterprise Agent Platform
• Agentic AI
• Vertex AI
• AI Security
• Agentic Data Cloud

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Engineer, MLOps Engineer, AI Architect

Related on AIssential

• Google makes an interesting choice with its new agent building tool for enterprises — Google's Gemini Enterprise Agent Platform enables scalable AI agent development for technical and business users.
• Gemini Enterprise Agent Platform lets you build, govern, and optimize your agents. — The Gemini Enterprise Agent Platform offers a unified environment for developing and managing AI agents using multiple leading models.
• 7 highlights from Google Cloud Next ‘26 — Google Cloud is transitioning to an "agentic era" with new platforms, infrastructure, and tools for autonomous AI.
• Google Cloud Next 2026: The End Of The AI Pilot Era — Google Cloud is consolidating its AI offerings into a unified agent platform to manage enterprise-scale AI deployments.
• Managing AI Agents at Scale with Google Cloud's Riyaz Habibbhai — Google Cloud's AI strategy focuses on an integrated, open, and simplified full-stack platform, evolving Vertex AI into the Gemini enterprise agent platform.
• Cloud Next: Develop and Defend AI Agents with Google Cloud — Google Cloud is rapidly scaling its AI infrastructure and tools to support the development and defense of enterprise AI agents.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by News and Advice on the World's Latest Innovations | ZDNET.