TL;DR – Google Cloud Next 2026 in 30 Seconds
- Gemini Enterprise Agent Platform: No-code AI agents for business workflows, available now.
- 8th-gen TPUs & Virgo Network: 10 TB/s data transfer, major AI throughput boost.
- Cross-Cloud Lakehouse: Query AWS & Azure data without migration via Apache Iceberg.
- Wiz integration: Unified security across Databricks, AI Studios, multi-cloud.
- Scale signal: 1 trillion tokens processed in 12 months; 75% of Cloud customers use AI.
Part of our Gemini & AI Agents guides. See our complete Google Gemini Guide for models, benchmarks & API details — and our AI Agents Guide for frameworks and build patterns.
Google Cloud Next 2026 demonstrates how practical AI agents and multi-cloud solutions are already becoming part of everyday business. The key announcements focus on efficiency, security, and new opportunities for professional workflows.
Google Cloud launches “Gemini Enterprise Agent” and brings AI into the workplace
What happened?
At the Google Cloud Next ’26 conference, more than 260 product enhancements were unveiled—with a focus on AI applications, agent platforms, cloud infrastructure, and security. Of particular note is the launch of the Gemini Enterprise Agent Platform and the integration of powerful AI tools into enterprises. Google also reported that approximately 75% of all cloud customers are already using AI.
Here is the full-length keynote (90 min):
AI Agents and Gemini: From Experiment to Business Tool
The Gemini Enterprise Agent Platform allows users to create AI agents and integrate them into processes without coding skills. The new Gemini Enterprise App merges workflow and AI—relevant business data is thus accessible via chat at any time, and tasks can be automated. According to Google, over one trillion tokens have been processed with these models in the last 12 months; the API is currently running at 16 billion tokens per minute.
- Real-world example: Companies can use AI agents to process orders or perform complex research tasks.
- Link to Docs: Gemini/Vertex AI Documentation
Multi-cloud infrastructure and new hardware
The eighth generation of TPUs (Tensor Processing Units) significantly accelerates AI processes. With Virgo Network and Managed Lustre Storage, data transfers of 10 terabytes per second can be achieved. New is the Cross-Cloud Lakehouse based on Apache Iceberg: Data can be queried instantly across clouds (e.g., from AWS) without having to migrate it. The Agentic Data Cloud aims to enable seamless data access across multiple platforms.
- More on Lakehouse for Apache Iceberg (formerly: BigLake): https://cloud.google.com/products/lakehouse
- More info on Apache Iceberg: Official Iceberg website
Enhanced security and simplified management
With the acquisition of Wiz, Google Cloud now gains an expanded security layer that spans from Databricks to AI Studios. The Technology Intel Center provides an aggregated feed of updates, migrations, and end-of-life announcements for admins. Goal: greater transparency for cloud users and centralized updates.
Context: Why this matters for businesses now
Companies face the challenge of operating AI solutions securely, efficiently, and scalably (“AI Velocity Paradox”). Google focuses on simplified workflows, lower barriers to entry for AI (no-code development), and increased speed through specialized hardware and software. These developments address current market needs: cost reduction, security, and rapid implementation.
Conclusion
Google Cloud Next ’26 delivers practical solutions for AI agents, multi-cloud data management, and security tools. With low barriers to entry and strong ecosystems, Google is positioning itself as the central platform for scalable AI workflows in enterprises.
Source: Google Cloud Blog
Gemini Enterprise Agent Platform vs. AWS Bedrock vs. Azure AI Foundry — 2026 Comparison
How does Google’s 2026 push compare to the two main hyperscaler rivals? Here is the side-by-side based on each vendor’s public positioning at their most recent flagship events.
| Capability | Google Cloud (Gemini Enterprise) | AWS (Bedrock + Agents) | Azure (AI Foundry) |
|---|---|---|---|
| No-code agent builder | Gemini Enterprise App (chat & visual) | Bedrock Studio (limited no-code) | Copilot Studio |
| Custom silicon | TPU v8 (newest gen, 2026) | Trainium2 / Inferentia3 | Maia 100 (partnered NVIDIA) |
| Cross-cloud query | Cross-Cloud Lakehouse (Iceberg) | Limited (S3 federation) | Fabric OneLake (Azure-centric) |
| Security layer | Wiz (multi-cloud, AI-aware) | GuardDuty + Security Hub | Defender for Cloud |
| Model catalog | Gemini 3.1, Imagen, Veo, partner models | Claude, Llama, Titan, Mistral | OpenAI GPT-5 series, Phi, Mistral |
Google’s 2026 differentiator is the bet on cross-cloud data access via Iceberg-based lakehouses — a direct answer to enterprises stuck with data scattered across AWS and Azure that don’t want costly migrations.
What Google Cloud Next 2026 means for businesses — 5 concrete takeaways
- No-code AI agents are now real. The Gemini Enterprise App means non-engineers can spin up automation agents for order processing, research, or reporting without writing code. This collapses the build-vs-buy decision for many internal workflows.
- Your cloud lock-in just got looser. Cross-Cloud Lakehouse on Apache Iceberg means you can leave your data where it is (S3, ADLS) and still query it from Google’s tools. Less migration risk, lower switching costs — in both directions.
- TPU v8 changes the cost-per-token math. If you were quoting workloads against H100 / B100 / Trainium2, get fresh numbers. The new TPU generation is positioned for inference-heavy agent workloads, which is exactly where token volumes explode.
- Security finally caught up with multi-cloud. Wiz inside Google Cloud’s security stack means a single posture management layer for AWS + Azure + GCP. For CISOs running heterogeneous estates, this is a real architectural shift.
- Agent maturity is the new battleground. Google joined AWS and Microsoft in shipping production-grade agent tooling. The market signal is clear: 2026 is the year “AI agent” becomes a checkbox on RFPs, not a science project.
Strategic context: Why Google had to ship this
Behind the polished keynote, Google Cloud is still the #3 hyperscaler by revenue. Each Next conference is a credibility test, and 2026 was the year Google had to prove its AI-native infrastructure thesis. The headline metrics — 1 trillion tokens processed and 16 billion tokens/minute on Gemini APIs — were chosen carefully. They signal that Vertex AI is now operating at hyperscaler volumes, not as an experiment.
The Wiz acquisition (closed in early 2026) is the more interesting strategic move. Wiz isn’t a Google-only security tool — it covers AWS, Azure, and GCP. By integrating it as the default security layer across Google Cloud, Google is implicitly saying: “we don’t need to be your only cloud to be useful to you.” That’s a meaningful pivot from the lock-in-first playbook that defined hyperscaler competition until 2024.
Related coverage on AI Rockstars
- Google Gemini: Complete Guide — Models, Benchmarks & API (2026) — full Gemini model lineup, pricing, and API patterns.
- AI Agents: Complete Guide — Frameworks, Tools & How to Build — how Gemini Enterprise stacks up against open-source agent frameworks.
- Anthropic: 10 AI Agents for Financial Workflows — the competing template-based approach from Anthropic.
Frequently Asked Questions
What is the Gemini Enterprise Agent Platform?
The Gemini Enterprise Agent Platform is Google Cloud’s no-code service for building and deploying AI agents inside business workflows. Users describe a task in natural language; the platform handles model selection, tool calls, and data access, including connections to enterprise systems like CRMs, ERPs, and storage.
What is Cross-Cloud Lakehouse based on Apache Iceberg?
Cross-Cloud Lakehouse is Google Cloud’s service for querying data that lives on other clouds — primarily AWS S3 and Azure ADLS — without migrating it. It uses the Apache Iceberg open table format as a common metadata layer, so analytics, ML, and AI workloads can read data in place.
What changed with TPU v8?
TPU v8 is the eighth generation of Google’s custom AI accelerator, announced at Cloud Next 2026. Compared to TPU v7, Google reports significant gains in inference throughput per dollar, which is the dominant cost driver for agentic workloads that issue many short model calls.
Is Gemini Enterprise available outside the US?
Yes. Google Cloud lists Gemini Enterprise availability across its major regions including EU (Frankfurt, Belgium), UK, and APAC. EU customers can pin processing to in-region endpoints for GDPR considerations, though enterprises should review the latest regional contracts directly with Google.
How does Gemini Enterprise compare to AWS Bedrock?
Both offer managed access to first-party and partner foundation models plus an agent layer. The key 2026 differentiators are Google’s Cross-Cloud Lakehouse (read AWS data from Google without migration) and the Wiz-based unified security posture across all three clouds. AWS Bedrock leads on third-party model breadth (Claude, Llama, Mistral) and on tight integration with the AWS data stack.
Final take
Google Cloud Next 2026 was less about new shiny demos and more about closing the credibility gap on enterprise AI. With usable no-code agents, multi-cloud query support, a refreshed TPU, and Wiz as the security backbone, Google is now positioning Cloud as a viable hub for heterogeneous AI workloads — not just for shops already on GCP. The next 12 months will show whether enterprises actually move workloads, or whether 2026’s announcements stay on the slide deck.
