Cloud AI Agents
AWS, Azure, Google Cloud, and Databricks Solutions for 2026
Key Takeaways
- AWS Bedrock AgentCore offers consumption-based pricing where I/O wait is free, with 13 pre-built evaluation systems and Policy controls for enterprise security
- Azure AI Foundry Agent Service reached GA with 10,000+ customers, featuring one-click deployment to Teams and Deep Research capabilities
- Google Vertex AI Agent Development Kit (ADK) has 7M+ downloads; Wells Fargo became the first major bank to deploy AI agents company-wide
- Databricks Mosaic AI introduced Agent Bricks for auto-optimized agents and Storage-Optimized Vector Search with 7x lower cost
CLOUD AI AGENTS BY THE NUMBERS (2026)
Sources: Microsoft, Google Cloud, Databricks
Why Cloud Platforms for AI Agents
Cloud AI agents represent a major shift in how enterprises deploy autonomous AI systems. Building production-grade AI agents requires sophisticated infrastructure for orchestration, memory management, tool integration, security, and observability. The major cloud providers—AWS, Microsoft Azure, and Google Cloud—have all launched comprehensive platforms specifically designed for cloud AI agents, while Databricks offers specialized capabilities for data-centric agent workflows.
According to Gartner, 40% of enterprise applications will feature task-specific AI agents by the end of 2026. However, they also predict over 40% of agentic AI projects will be canceled by 2027 due to escalating costs, unclear business value, or inadequate risk controls. This makes platform selection critical for enterprise success. For SaaS-based enterprise platforms like Salesforce Agentforce and ServiceNow, see our guide to enterprise AI agents.
What Cloud AI Agent Platforms Provide
- •Runtime Infrastructure: Secure, serverless deployment with automatic scaling
- •Tool Integration: Unified access to APIs, databases, and enterprise systems
- •Memory Systems: Session context and long-term memory management
- •Security and Governance: Enterprise-grade identity, authentication, and policy controls
- •Observability: Monitoring, debugging, and evaluation capabilities
Platform Comparison Overview
Before diving into individual platforms, here is a high-level comparison of cloud AI agent offerings from the major providers:
| Platform | Primary Strength | Best For | Status |
|---|---|---|---|
| AWS Bedrock AgentCore | Multi-model access, enterprise security | AWS-native enterprises, regulated industries | GA Dec 2025 |
| Azure AI Foundry | Microsoft 365 integration, Entra governance | Microsoft-centric organizations | GA May 2025 |
| Google Vertex AI | Observability, Gemini integration | GCP users, data-centric workflows | GA Mar 2025 |
| Databricks Mosaic AI | Data lakehouse integration, MLOps | Data teams, RAG applications | GA |
AWS Bedrock Agents and AgentCore
Amazon cloud AI agent infrastructure
AWS AI agents through Amazon Bedrock enable developers to build applications that respond dynamically by accessing enterprise systems, executing actions, and retaining memory across sessions. At AWS re:Invent 2025, Amazon launched AgentCore—a comprehensive platform for building, deploying, and operating enterprise-scale agents without infrastructure management.
AgentCore Components
- •Runtime: Secure, serverless deployment with consumption-based pricing
- •Gateway: Unified tool access and connections to enterprise systems
- •Memory: Intelligent context retention across sessions
- •Identity: Authentication across AWS and third-party services
- •Browser and Code Interpreter: Enhanced agent capabilities
Enterprise Features
- •Policy: Natural language boundaries for agent actions
- •Evaluations: 13 pre-built evaluation systems for quality scoring
- •Observability: Comprehensive monitoring and debugging
- •Flows: Visual workflow builder for multi-step agents
Unique Pricing Model
Unlike traditional compute services, AgentCore Runtime charges only for active resource consumption. Agentic workloads typically spend 30-70% of time in I/O wait (waiting for LLM responses, API calls). With AgentCore, I/O wait time is free, delivering substantial cost savings compared to pre-allocated instance pricing.
Azure AI Foundry Agent Service
Microsoft cloud AI agent platform
Azure AI agents through the Foundry Agent Service empower developers to securely design, deploy, and scale AI agents with ease. The platform reached general availability in 2025 and has been adopted by over 10,000 customers. Azure AI Foundry agents work with a rich ecosystem of models from the Foundry model catalog, knowledge sources like Bing, SharePoint, and Azure AI Search, plus 1,400+ action connectors via Azure Logic Apps.
Multi-Agent Workflows
Enable dynamic collaboration among specialized agents with built-in orchestration
One-Click M365 Deployment
Instantly deploy agents to Microsoft 365 Copilot and Teams Chat without manual setup
Computer Use Tool
Perform tasks by interacting with computer systems through their user interfaces
Latest Capabilities (2025-2026)
| Feature | Description | Status |
|---|---|---|
| Deep Research | OpenAI's advanced agentic research capability via API and SDK | Preview |
| Browser Automation | Real-world browser tasks via Playwright Workspaces | Preview |
| Hosted Agents | Fully managed agent hosting with built-in memory | GA |
| MCP and A2A Support | Open standards for agent interoperability | GA |
Customer Success: NTT DATA leveraged Azure AI Foundry Agent Service to automate routine customer service inquiries, resulting in 50% faster time to market and improved productivity across functions.
Source: Microsoft Tech Community
Google Vertex AI Agent Builder
Google Cloud AI agent platform
Google AI agents through Vertex AI Agent Builder provide a comprehensive and open platform to build, scale, and govern reliable agents in production. The Python Agent Development Kit (ADK) has been downloaded over 7 million times since Agent Builder's public inception, demonstrating strong developer adoption. Google Vertex AI agents 2025 updates include general availability of Agent Engine, new regions, and the Gemini 2.5 Computer Use model.
Build Capabilities
- •Agent Development Kit (ADK): Open-source framework for multi-agent systems
- •Agent Designer: Low-code visual designer for rapid prototyping
- •Agent Garden: Library of prebuilt sample agents and tools
- •Memory Bank: Topic-based memory using ACL 2025 research
Security and Governance
- •Threat Detection: Built-in Security Command Center integration
- •Agent Identity: IAM-based security and access management
- •Private VPC: Deploy agents in private network environments
- •HIPAA Support: Agent Engine now supports HIPAA workloads
Gemini 2.5 Computer Use
The Gemini 2.5 Computer Use model and tool is now available in Preview. It enables applications to interact with and automate tasks in the browser, including:
- Automating repetitive data entry or form filling
- Navigating websites to gather information
- Performing action sequences in web applications
- Testing and QA automation workflows
Databricks Mosaic AI Agents
Data-centric AI agent platform
Databricks AI agents through Mosaic AI provide a unified platform for building production-quality AI agent systems integrated with enterprise data. At the Data + AI Summit 2025, Databricks announced major updates including Agent Bricks, MLflow 3.0, and Storage-Optimized Vector Search with 7x lower cost.
Agent Bricks (New)
A new way to build high-quality agents that are auto-optimized on your data. Simply provide a description and connect enterprise data—Agent Bricks handles the rest.
- →Structured information extraction
- →Reliable knowledge assistance
- →Custom text transformation
- →Multi-agent systems
MLflow 3.0
Redesigned from the ground up for Generative AI with monitoring, evaluation, and lifecycle management. Monitor agents deployed anywhere, even outside Databricks.
- →Cross-platform agent observability
- →Agents on AWS, GCP, or on-premise
- →Unified governance controls
- →GenAI-specific evaluation metrics
Platform Integrations
- •MCP Integration: Anthropic's Model Context Protocol integrated directly into the platform with MCP servers hosted on Databricks Apps
- •Vector Search: Storage-Optimized Vector Search scales to billions of vectors with 7x lower cost
- •Mosaic AI Gateway: Generally available for unified model access and governance
Customer Success: Block built an AI agent system using Mosaic AI to automate operations for sellers, such as generating customized menus. Intercontinental Exchange (ICE) built an agent system that securely uses unique financial data to provide highly accurate answers to customer questions.
Source: Databricks Blog
Case Study: Wells Fargo and Google Cloud AI Agents
Wells Fargo Google Cloud AI Agents
First major commercial bank to comprehensively adopt AI agents
In August 2025, Wells Fargo announced an expansion of their strategic relationship with Google Cloud to transform how the bank uses and deploys agentic AI at scale. As an early adopter of Google Agentspace, Wells Fargo became one of the first major banks to deploy AI agents company-wide.
Use Cases Deployed
- •FX post-trade inquiry triage and summarization
- •Policy and procedure navigation across internal systems
- •250,000 vendor agreement documents queried by custom agent
- •24/7 customer service with hyper-personalization
Employees Equipped
- •Branch bankers
- •Investment bankers and traders
- •Marketing teams
- •Customer relations and corporate teams
"Wells Fargo's adoption of Google Agentspace marks a bold step forward in making banking simpler and smarter—for our customers and employees."
Sources: Google Cloud Blog, Banking Dive, PYMNTS
Pricing Comparison
Cloud AI agent pricing varies significantly by provider and component. Here is a side-by-side comparison of key infrastructure costs:
| Component | AWS AgentCore | Azure AI Foundry | Google Vertex AI |
|---|---|---|---|
| Runtime (vCPU/hour) | $0.0895 | No additional charge | $0.00994 |
| Memory (GiB/hour) | $0.00945 | Pay for underlying services | $0.0105 |
| Workflow Transitions | $0.035/1K | Varies by service | Varies by usage |
| Free Tier | $200 credits | Free to explore | $300 credits + Express Mode |
| I/O Wait Billing | Free | N/A | Standard billing |
Model Inference Costs Add Up
The prices above cover infrastructure only. Model inference costs (per token/request) are billed separately and often represent the largest portion of AI agent expenses. Claude, GPT-4, and Gemini each have different pricing that varies by context length and model version.
For current pricing, see official documentation: AWS | Azure | Google Cloud
How to Choose Your Platform
Selecting the right cloud platform for AI agents depends on your existing investments, team capabilities, and specific use cases:
Choose AWS Bedrock AgentCore if...
- →Your organization is AWS-first with existing VPC, IAM, and infrastructure investments
- →You need enterprise-grade security controls and compliance certifications
- →You want access to Claude, Llama, and Amazon Nova models in one platform
- →Consumption-based pricing with free I/O wait aligns with your workloads
Choose Azure AI Foundry if...
- →Your organization uses Microsoft 365, Teams, and Copilot extensively
- →You need one-click agent deployment to collaboration tools
- →You want access to both OpenAI and Anthropic frontier models
- →You need 1,400+ pre-built connectors via Azure Logic Apps
Choose Google Vertex AI if...
- →You prioritize observability and want built-in dashboards for agent monitoring
- →You want deep Gemini integration including Computer Use capabilities
- →You prefer low-code visual tools alongside pro-code SDKs
- →You need HIPAA compliance for healthcare workloads
Choose Databricks Mosaic AI if...
- →You have existing data lakehouse investments and need unified governance
- →Your agents need deep integration with enterprise data
- →You want auto-optimized agents via Agent Bricks
- →You need to monitor agents across multiple clouds with MLflow 3.0
Frequently Asked Questions
What are cloud AI agents?
Cloud AI agents are autonomous AI systems hosted on major cloud platforms like AWS, Azure, and Google Cloud. These services provide the infrastructure to build, deploy, and scale AI agents that can plan tasks, use tools, access enterprise data, and execute actions with built-in security and governance. Examples include AWS Bedrock Agents, Azure AI Foundry Agent Service, and Google Vertex AI Agent Builder.
Which cloud platform is best for AI agents?
The best platform depends on your existing infrastructure: AWS Bedrock AgentCore suits AWS-native enterprises needing multi-model access and enterprise security. Azure AI Foundry is ideal for Microsoft 365 organizations with one-click Teams deployment. Google Vertex AI excels in observability and offers a free tier. Databricks Mosaic AI is best for data teams with existing lakehouse investments.
How much do cloud AI agents cost?
Pricing varies by provider: AWS AgentCore charges $0.0895 per vCPU-hour for runtime. Google Vertex AI Agent Engine costs $0.00994 per vCPU-hour. Azure AI Foundry Agent Service has no additional charge—you pay for underlying compute and models. All providers bill separately for LLM inference, which often represents the largest cost component.
What is Azure AI Foundry Agent Service?
Azure AI Foundry Agent Service is Microsoft's platform for building and deploying AI agents at scale. It reached general availability in May 2025 and has been used by over 10,000 customers. Key features include multi-agent orchestration, one-click deployment to Microsoft 365 and Teams, Computer Use tool, Deep Research capabilities, and 1,400+ action connectors via Azure Logic Apps.
How is Wells Fargo using Google Cloud AI agents?
In August 2025, Wells Fargo expanded their Google Cloud partnership to deploy AI agents company-wide using Google Agentspace. Use cases include FX post-trade inquiry triage, querying 250,000 vendor contract documents, policy navigation, and 24/7 personalized customer service. Wells Fargo became one of the first major commercial banks to comprehensively adopt AI agents across operations.
Summary: Cloud AI Agent Platforms
AWS BEDROCK AGENTCORE
Enterprise security with consumption-based pricing. Free I/O wait billing, 13 evaluation systems, and multi-model access including Claude and Llama.
AZURE AI FOUNDRY
10,000+ customers with deep M365 integration. One-click Teams deployment, Deep Research, and 1,400+ Logic Apps connectors.
GOOGLE VERTEX AI
7M+ ADK downloads with strong observability. Gemini 2.5 Computer Use, Memory Bank research, and HIPAA compliance support.
DATABRICKS MOSAIC AI
Data-centric agents with Agent Bricks auto-optimization. MLflow 3.0 cross-platform monitoring and 7x lower cost Vector Search.
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At Planetary Labour, we help organizations evaluate and implement cloud AI agent platforms that deliver measurable business outcomes while managing risk.
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