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Introduction:
Alibaba Cloud, a global leading provider of AI infrastructure and intelligence backbone of Alibaba Group, has named as a Leader in the newly released report titled “Omdia Market Radar: Agentic AI Cloud Titans in Asia & Oceania, 2026”. Alibaba Cloud achieved the highest ranking across six out of nine evaluative dimensions, including Agent Infrastructure, Model Services & Development Tools, Agent Development Suite, Native Agent Support, Security for Agentic AI, and Open-Source Model.
Omdia’s report systematically evaluates the technical capabilities, market penetration, and strategic positioning of major cloud service providers across the entire agentic AI cloud stack. The report categorizes the Agentic AI cloud stack into three core layers: Agentic AI Infrastructure, MaaS (Model-as-a-Service) & Development Environments, and Agentic AI SaaS (AI Applications).
According to the report, Alibaba Cloud stands out as a true full-stack AI service provider, owning every critical layer of this stack. This comprehensive ecosystem spans proprietary AI chips, high-performance networking, the Lingjun AI compute cluster, the PAI machine learning platform, Model Studio, AgentScope, AgentRun, AgentBay, ACS Agent Sandbox, and Function Compute.
A Massive Market Opportunity in Asia & Oceania
According to Omdia’s AI software revenue forecast, the agentic AI software market in Asia & Oceania is projected to grow from $782m in 2025 to $11.2bn in 2030, with a CAGR of 94%.
The report highlights key market dynamics driving this growth. Information technology, financial services, and retail are the top verticals leading the enterprise adoption of agentic AI software. Beyond large-scale enterprise deployment, the rise of open-source tools such as OpenClaw and its variants has also led to explosive growth in personal AI agent deployments.
A Full-Stack Agentic AI Powerhouse
As a full-stack AI service provider, Alibaba Cloud remains uniquely positioned to capture this booming market. Its AI+Cloud capabilities seamlessly bridge powerful foundations with enterprise deployment, spanning its widely acclaimed Qwen open-source and commercial models, world-class cloud infrastructure, advanced model services, and developer tools highly optimized for the next generation of AI agents.
Alibaba recently announced a series of upgrade to its full AI stack capabilities. In May, Alibaba debuted Qwen3.7-Max, its latest large language model engineered for advanced agentic coding, complex reasoning, and long-horizon task execution. The model delivers exceptional agent capabilities across diverse domains. As a frontier-level coding assistant, it supports coding tasks from rapid frontend prototyping to complex, multi-file software engineering. To enhance office work productivity, it reliably orchestrates multi-agent workflows to tackle sophisticated operations.
Alibaba Cloud has also upgraded its infrastructure to address surging compute and AI workload demands in the agentic era. The Panjiu AL128 Supernode Server, designed to empower scalable agent inference and large-scale model training, is an optimization update within Alibaba's model service platform that continuously refines model performance.
To simplify access to and deployment of AI models, Alibaba Cloud unveiled Qwen Cloud, a new AI-native cloud platform designed to provide a seamless model service experience for both businesses and AI agents. The platform enables developers, enterprises, and prosumers to build AI-powered applications and agents with greater ease and efficiency.
To enable AI agents to interact more seamlessly with cloud resources, Alibaba Cloud has launched a new Skills portal that converts common cloud capabilities across more than 60 cloud products into Skill-based and MCP-compatible formats. This allows AI agents to invoke cloud resources as naturally as calling functions. Alibaba Cloud’s core products, including databases, big data, operations and maintenance (O&M), and security, have developed dedicated product-level agents to help manage complex cloud environments more efficiently.
