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Google Cloud pitches itself as the operating system for enterprise AI agents

Google Cloud pitches itself as the operating system for enterprise AI agents

New Capabilities

Cloud Next 2026 marks Google's shift from selling AI features to selling the platform that runs, governs, and connects autonomous agents across the enterprise

April 22nd, 2026: Cloud Next 2026 opens with 'The Agentic Cloud' keynote

Overview

For two years, every major cloud vendor has been bolting artificial intelligence onto its existing products. At Google Cloud Next 2026, which opened April 22 in Las Vegas, chief executive Thomas Kurian argued that era is over. His keynote, titled 'The Agentic Cloud,' positioned Google's Gemini model not as a feature layer but as a full enterprise operating system—an orchestration engine, agent runtime, governance system, and integration bus for autonomous AI agents that act on behalf of workers, not just advise them.

The stakes are structural. Cloud computing's three dominant providers—Google, Microsoft, and Amazon Web Services—are each betting that whoever controls the platform layer for AI agents will lock in the next decade of enterprise spending, much as whoever controlled virtualization and containers shaped the last one. Google is wagering that openness wins: its Agent-to-Agent protocol, launched at last year's Cloud Next, now underpins its pitch that enterprises should be able to mix agents from different vendors on a single control plane. Whether that openness is genuine strategy or a market-share play by the third-place cloud provider is the question analysts will be asking all week.

Why it matters

The company that becomes the default runtime for enterprise AI agents could dominate cloud spending for the next decade.

Play on this story Voices Debate Predict

Key Indicators

500+
Conference sessions
Google Cloud Next 2026 runs April 22–24 with over 500 sessions, the largest Next to date
#3
Google Cloud market position
Google Cloud trails Amazon Web Services and Microsoft Azure in global cloud infrastructure market share
~50
Agent-to-Agent protocol partners
Google's open A2A interoperability standard launched in 2025 with roughly 50 enterprise partners including Salesforce and SAP
$11.4B
Google Cloud quarterly revenue (Q4 2025)
Google Cloud crossed profitability in 2023 and has grown revenue roughly 30 percent year-over-year since

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People Involved

Thomas Kurian
Thomas Kurian
Delivered opening keynote at Cloud Next 2026
 Sundar Pichai
Sundar Pichai
Overseeing company-wide AI strategy

Organizations Involved

Google Cloud (Alphabet Inc.)
Google Cloud (Alphabet Inc.)
Cloud Infrastructure Provider
Hosting Cloud Next 2026; positioning as agentic AI platform

Google Cloud is Alphabet's enterprise cloud division, the third-largest global cloud infrastructure provider behind AWS and Microsoft Azure.
Microsoft Azure
Microsoft Azure
Cloud Infrastructure Provider
Primary competitor with Copilot Studio and Azure AI Agent Service

Microsoft Azure is the second-largest cloud platform and Google Cloud's most direct competitor in enterprise AI, leveraging its close partnership with OpenAI and deep integration with Microsoft 365 and Dynamics 365.
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Cloud Infrastructure Provider
Market leader pursuing model-agnostic agent strategy via Bedrock

AWS is the largest cloud infrastructure provider by market share, pursuing an agentic AI strategy centered on Amazon Bedrock Agents and a model-agnostic marketplace approach backed by a multi-billion-dollar investment in Anthropic.

Timeline

  1. Cloud Next 2026 opens with 'The Agentic Cloud' keynote

    Product Launch

    Thomas Kurian opened Google Cloud Next 2026 in Las Vegas by positioning Google Cloud as a full enterprise operating system for autonomous AI agents—not just an AI feature provider. Gemini was presented as an orchestration layer, agent runtime, governance system, and enterprise integration hub.

  2. Google launches A2A protocol and Agentspace at Cloud Next 2025

    Product Launch

    Google unveiled the Agent-to-Agent protocol, an open standard for interoperability between AI agents from different vendors, and Agentspace, an orchestration product for enterprise agent management. About 50 partners signed on at launch.

  3. Anthropic releases Model Context Protocol

    Industry Standard

    Anthropic open-sourced its Model Context Protocol (MCP), a standard for connecting AI models to external data and tools. It was rapidly adopted across the industry and became a building block for agentic AI systems.

  4. Microsoft unveils agentic AI tools at Ignite 2024

    Competitive

    Microsoft announced Copilot Studio for building custom AI agents and Azure AI Agent Service, signaling its own pivot from passive copilots to autonomous agents integrated into Office and Dynamics.

  5. Salesforce launches Agentforce at Dreamforce 2024

    Competitive

    Salesforce chief executive Marc Benioff declared the copilot era dead and launched Agentforce, a suite of autonomous AI agents for sales, service, and marketing. The enterprise industry's language shifted from 'copilots' to 'agents.'

  6. Cloud Next 2024: Gemini replaces Duet AI, Agent Builder debuts

    Product Launch

    Google rebranded its AI tools under the Gemini name and launched Vertex AI Agent Builder, marking the first explicit shift from AI assistance to AI agents in Google's enterprise messaging.

  7. Google Cloud launches Duet AI at Cloud Next 2023

    Product Launch

    Google introduced Duet AI as its umbrella brand for generative AI assistants across Workspace and Cloud, along with major Vertex AI enhancements. The 'AI copilot' era began in earnest.

Scenarios

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1

Google becomes the default agent runtime for multi-vendor enterprises

Google's bet on openness—particularly the A2A protocol—pays off. Enterprises running agents from multiple vendors (Salesforce, SAP, custom-built) choose Google Cloud as the neutral orchestration layer precisely because Google's enterprise application footprint is smaller than Microsoft's, making it a less threatening platform owner. Google Cloud's market share grows significantly, narrowing the gap with Azure.

Discussed by: SiliconANGLE, Forrester analysts covering cloud platforms
Consensus —
2

Microsoft's distribution advantage makes Copilot Studio the enterprise default

Microsoft's installed base of hundreds of millions of Office and Teams users proves decisive. Enterprise buyers prefer agents embedded in the tools their employees already use daily over a separate orchestration platform. Google Cloud remains a strong number-three provider but fails to meaningfully close the gap, and the 'agentic operating system' pitch is absorbed into Azure's broader platform narrative.

Discussed by: Gartner, Goldman Sachs cloud research
Consensus —
3

Agent governance failures slow adoption across all platforms

High-profile incidents—autonomous agents making unauthorized purchases, leaking sensitive data through cross-system integrations, or producing costly hallucination-driven errors—trigger a backlash. Enterprises pull back to supervised 'copilot' modes and regulators impose new requirements on autonomous AI systems. The agentic platform race stalls, and the real winners are governance and observability vendors, not the cloud providers themselves.

Discussed by: Gartner Hype Cycle analysis, enterprise CIO surveys, McKinsey
Consensus —
4

The agent platform layer fragments along industry lines

Rather than a single horizontal platform winning, industry-specific agent ecosystems emerge: Salesforce dominates sales and marketing agents, ServiceNow owns IT operations agents, Epic and Cerner control healthcare agents, and the cloud providers become commodity infrastructure beneath these vertical platforms. Google's 'operating system' pitch proves too horizontal for how enterprises actually deploy agents.

Discussed by: IDC, Deloitte AI practice leaders
Consensus —

Historical Context

Cloud platform wars: AWS vs. Azure vs. Google (2006–2020)

2006–2020

What Happened

Amazon Web Services launched in 2006 and ran effectively unopposed for years. Microsoft Azure launched in 2010 and used its enterprise relationships and Office integration to climb to second place. Google Cloud, despite superior technology in areas like Kubernetes and BigQuery, consistently struggled in enterprise sales and remained a distant third.

Outcome

Short Term

AWS established market dominance that persists. Microsoft closed the gap by bundling Azure with enterprise agreements. Google hired Thomas Kurian from Oracle in 2019 specifically to fix its enterprise sales problem.

Long Term

The pattern established that technical superiority alone does not win platform wars—distribution, enterprise relationships, and ecosystem lock-in matter more. Google learned this lesson painfully.

Why It's Relevant Today

Google's 'Agentic Cloud' pitch is an attempt to reset the competitive dynamics of cloud computing around a new paradigm—AI agents—where its Gemini model and A2A protocol could provide a first-mover advantage that raw infrastructure scale did not.

The mobile platform duopoly (2007–2013)

2007–2013

What Happened

Apple launched the iPhone in 2007 and controlled a tightly integrated hardware-software-services stack. Google responded with Android, an open platform available to any hardware maker. Dozens of competitors—BlackBerry, Windows Phone, Palm—offered technically capable alternatives. Within six years, only two platforms survived.

Outcome

Short Term

Apple won the premium segment through integration. Android won market share through openness and manufacturer diversity. Everyone else was eliminated.

Long Term

The duopoly locked in for over a decade. App developers built for two platforms, creating a self-reinforcing ecosystem barrier that no competitor could overcome.

Why It's Relevant Today

Google is running the Android playbook again—championing openness (A2A protocol) against Microsoft's more integrated approach (agents embedded in Office). The question is whether enterprise AI agents will consolidate into a duopoly the way mobile did, and whether Google's openness strategy will capture enough share to survive the consolidation.

Salesforce and the SaaS platform shift (1999–2012)

1999–2012

What Happened

Salesforce launched in 1999 arguing that enterprises should rent software as a service rather than install it on their own servers. Incumbents like Oracle, SAP, and Microsoft dismissed the model as insecure and unsuitable for serious enterprise use. Salesforce's 'No Software' campaign was provocative and polarizing.

Outcome

Short Term

Enterprise adoption was slow—it took nearly a decade for SaaS to move from early adopters to mainstream acceptance. Security and data-sovereignty concerns were persistent objections.

Long Term

SaaS became the default enterprise software delivery model. The incumbents who initially dismissed it were forced to rebuild their products for the cloud. The transition from license revenue to subscription revenue took most of them 5–10 years.

Why It's Relevant Today

The shift from 'AI copilots' to 'autonomous AI agents' echoes the shift from on-premise to SaaS: incumbents are skeptical, early adopters are enthusiastic, and the governance concerns (security, control, auditability) sound remarkably similar. If the pattern holds, adoption will be slower than boosters predict but more total than skeptics expect.

Sources

(4)
Google Cloud Events Fortune SiliconANGLE BizTech Magazine