At Google Cloud Next 2026, Google moved from selling AI as potential to selling it as infrastructure. The company rebranded Vertex AI as the Gemini Enterprise Agent Platform, absorbed its employee AI assistant Agentspace into a unified Gemini Enterprise product, and committed $750 million to accelerate partners’ agentic AI deployments. “The experimental phase is behind us,” Google Cloud CEO Thomas Kurian said in the opening keynote. “And now the real challenge begins.”

Key takeaways:

• Google rebranded Vertex AI to the Gemini Enterprise Agent Platform at Cloud Next 2026, signaling agents are its core enterprise product.
• Google committed $750 million to help its 120,000-member partner ecosystem accelerate agentic AI deployments for joint customers.
• Workspace Studio lets business users build AI agents across Gmail, Docs, Sheets, and Slack in plain language — no code required.
• 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall.
• A2A (Agent2Agent) protocol v1.0 is already in production at 150 organizations, enabling agents to communicate across platforms.

The shift matters for any organization still treating AI agents as a pilot program. Google’s message is that the infrastructure is ready, the governance tools exist, and waiting is now a competitive liability — not a prudent hedge.

What did Google actually announce at Cloud Next 2026?

The announcements fell into four categories: platform consolidation, new tooling for builders and non-builders alike, infrastructure upgrades, and partner funding.

Platform consolidation. Vertex AI — Google’s model-as-a-service layer — is now the Gemini Enterprise Agent Platform. The rename is substantive, not cosmetic. The platform gained Agent Designer, a visual flow canvas for building agent workflows (in preview); Agent Engine Sessions and Memory Bank for persistent agent context across interactions (generally available); and an Agent Garden offering prebuilt solutions for customer service, data analysis, and creative tasks. The Model Garden now hosts more than 200 models, including Anthropic’s Claude, as listed in Google Cloud’s Next ‘26 announcements, giving enterprise teams a multi-model option without leaving Google Cloud.

No-code agent builder. Workspace Studio is the broadest-reach announcement. It lets any business user build agents across Gmail, Docs, Sheets, Drive, Meet, and Chat by describing what they want in plain language. An employee can type “every Friday, remind me to update my project tracker” and Gemini builds the automation. Workspace Studio connects to Asana, Jira, Mailchimp, Salesforce, and external APIs via webhooks — making it an accessible entry point for teams that have been sitting on the sidelines waiting for AI tooling they could actually use.

New chips. Google unveiled the TPU 8t and TPU 8i — its eighth-generation tensor processing units. Per Sundar Pichai’s Cloud Next blog post, the TPU 8t is designed for training and scales to 9,600 chips per pod with 2 petabytes of shared high-bandwidth memory — three times the processing power of the prior Ironwood generation. The TPU 8i targets inference, connecting 1,152 chips per pod with three times more on-chip SRAM to run millions of agents concurrently at low latency.

Partner investment. The $750 million fund supports 120,000 ecosystem partners — including Accenture, Deloitte, PwC, TCS, Capgemini, and HCLTech — with credits, embedded engineers, early model access, and agentic AI prototyping resources. Google’s 330,000 partner-trained experts can now get hands-on implementation support directly from Google’s forward-deployed engineering teams. Separately, 95% of the top 20 SaaS companies and over 80% of the top 100 already use Gemini models, giving Google enormous distribution reach before a single line of new code is written.

Why does the “agentic enterprise” framing matter for your business?

The product announcements are real, but the strategic signal matters more. Google is explicitly positioning AI agents not as tools but as a new operational layer — one that sits between your employees, your data, and your workflows. This is the same bet Microsoft has made with Copilot and Snowflake is making with its Intelligence control plane.

The competitive dynamic is three-way and accelerating. Per The Next Web’s Cloud Next 2026 coverage, OpenAI’s Operator scores 87% on complex browser task benchmarks and enterprise revenue now accounts for 40% of OpenAI’s total. The same reporting notes that Anthropic’s Model Context Protocol has reached 10,000 servers and 97 million monthly SDK downloads. Google is fighting from third place in cloud market share behind AWS and Azure, but exited Q4 2025 with 50% year-over-year growth — the fastest rate among the three hyperscalers.

What Google has that OpenAI and Anthropic don’t is vertical integration. It owns the model (Gemini), the runtime (Gemini Enterprise Agent Platform), the silicon (TPU 8t and 8i), and the distribution channel (Workspace, used by hundreds of millions of employees). Kurian framed it directly in the keynote: competitors “hand you the pieces, not the platform.”

What is the A2A protocol, and why should you care?

The Agent2Agent (A2A) protocol v1.0 is the least-hyped but potentially most consequential announcement. It is an open standard for agents built on different platforms — Google, Salesforce, ServiceNow, Box, Workday — to communicate with each other without custom integration work. With v1.0 already in production at 150 organizations, per The Next Web’s April 22, 2026 coverage, A2A addresses one of the core practical objections to agent adoption: that agents locked inside one vendor’s platform can’t do the cross-system work that actually saves time.

For a business leader, A2A means an agent built in Gemini Enterprise can hand off a task to an agent in Salesforce, retrieve data from a Workday process, and return a result without your team writing glue code. That’s the difference between an impressive demo and a deployed workflow.

Should you be deploying AI agents now?

The honest answer depends on your organization’s data readiness and risk tolerance. Google’s momentum data is real: nearly 75% of Google Cloud customers now use its AI products, 330 customers are each processing over a trillion tokens per quarter, and Gemini Enterprise saw 40% growth in paid monthly active users in Q1 alone. The tooling is maturing rapidly.

But “the experimental phase is behind us” is a vendor’s claim about production readiness, not an independent audit. The governance features Google announced — new security controls, managed MCP servers, agent monitoring — suggest Google is aware that scale without oversight is how organizations end up with thousands of agents no one fully understands. Those governance tools are worth exploring before the agents are.

A reasonable starting point for most businesses: use Workspace Studio for low-stakes automation (internal summaries, routine scheduling, data-retrieval tasks), build familiarity with the Gemini Enterprise Agent Platform in a sandboxed environment, and wait for the A2A ecosystem to broaden before betting cross-platform workflows on it.

Frequently asked questions

What is the Gemini Enterprise Agent Platform?

The Gemini Enterprise Agent Platform is Google Cloud’s rebranded and expanded version of Vertex AI, announced at Cloud Next 2026 on April 22. It is a full-stack platform for building, deploying, scaling, and governing AI agents. Features include Agent Designer (a visual workflow builder), Agent Engine for persistent agent memory, a Model Garden with 200-plus models including Anthropic Claude, and prebuilt agents from partners including Salesforce, Workday, Box, and ServiceNow.

What is Workspace Studio and who is it for?

Workspace Studio is a no-code AI agent builder for Google Workspace users — meaning any employee, not just developers. It lets users describe automations in plain language and Gemini creates them across Gmail, Docs, Sheets, Drive, Meet, and Chat. It connects to external tools like Asana, Jira, Salesforce, and Mailchimp via webhooks. It is rolling out to Workspace business, enterprise, and education customers.

What is the $750 million Google Cloud partner fund?

Google Cloud announced a $750 million fund at Cloud Next 2026 to accelerate agentic AI adoption through its 120,000-member partner ecosystem. The money supports AI value assessments, Gemini proofs-of-concept, agentic prototyping, and embedded Google engineers deployed alongside partners including Accenture, Deloitte, PwC, Capgemini, HCLTech, and TCS. Early model access goes to BCG and McKinsey to refine Gemini models before general release.

What are Google’s new TPU 8t and TPU 8i chips?

Google unveiled two eighth-generation tensor processing units at Cloud Next 2026. The TPU 8t is optimized for model training, delivering three times the processing power of the prior Ironwood generation and scaling to 9,600 chips per superpod. The TPU 8i is built for inference — running live AI agent responses — with three times more on-chip SRAM and enough throughput to run millions of agents concurrently. Both are available to Google Cloud customers.

What is the Agent2Agent (A2A) protocol?

A2A is an open standard that allows AI agents built on different platforms to communicate with each other without custom integration. Version 1.0 launched at Cloud Next 2026 and is already in production at 150 organizations. In practice, it means a Gemini agent can pass tasks to agents in Salesforce, ServiceNow, or Workday and receive results back — enabling genuine cross-platform automation without writing glue code for each vendor combination.

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Published April 23, 2026. Based on announcements from Google Cloud Next ‘26 (Las Vegas, April 22–24, 2026).

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