Alibaba

China’s agentic AI market is accelerating fast, and Alibaba’s Qwen is at the center of it — with 300 million monthly active users and growing compatibility with the OpenClaw ecosystem. Alibaba’s Dominant Position in Chinese Agentic AI According to analysis from China Briefing, an established B2B China market intelligence publication, Alibaba holds 35.8% of the Chinese agentic AI market as of early 2026. That’s the largest single share in a market that’s growing faster than most Western counterparts. ...

Alibaba International has a clear read on where the enterprise AI market is heading, and yesterday’s announcement of Accio Work shows they’re moving fast to capture it. The new platform — announced March 23 and confirmed via Reuters and PRNewswire — is a plug-and-play AI taskforce designed to run core business operations for small and medium enterprises worldwide, without requiring engineering resources to deploy. What Is Accio Work? Accio Work is Alibaba International’s answer to a specific SME pain point: large enterprises can afford dedicated AI teams and custom implementations, but SMEs can’t. Accio Work closes that gap with a no-code deployment model that puts autonomous AI agents to work across critical business functions: ...

OpenClaw’s rise in China has taken a new turn: what started as a viral cultural phenomenon has crossed into serious enterprise territory — and that’s prompted China’s government to respond with back-to-back cybersecurity warnings unlike anything it has issued about a single open-source project before. The dual nature of this story — explosive adoption and urgent official concern — captures exactly the tension that agentic AI creates at scale. The Adoption Wave The numbers from China’s tech sector are striking. Tencent Cloud is running on-site installation sessions for enterprise clients, helping businesses deploy OpenClaw at scale. Alibaba has launched a dedicated OpenClaw application — not just compatibility, but a purpose-built product built on the framework. ...

China’s agentic AI race has a new frontrunner — and it’s not the company you might expect. Bloomberg reported exclusively on March 17 that Tencent is integrating an AI agent directly into WeChat, the super-app that a significant portion of China’s internet-connected population uses daily. The strategic logic is blunt and brilliant: why build a new AI platform when you already own the distribution channel? The WeChat Advantage WeChat’s scale is hard to overstate. With 1.4 billion monthly active users, it isn’t just a messaging app — it’s an OS-level platform in China. Food delivery, ride-hailing, hospital appointments, retail purchases, government services: all live inside WeChat’s mini-program ecosystem. A single AI agent embedded at that layer would have access to more daily commercial activity than most dedicated AI platforms could dream of. ...

Alibaba dropped Wukong on Tuesday — and China’s enterprise AI agent race just got a lot more interesting. Named after the Monkey King from the classic Chinese novel Journey to the West, Wukong is Alibaba’s entry into the enterprise AI agent arena. It’s a Qwen-powered platform that lets businesses manage multiple AI agents through a single interface, with what Alibaba calls “enterprise-grade security infrastructure.” And it arrives at a pivotal moment: the company is mid-reorganization, competition from Tencent and Zhipu AI is heating up, and the broader OpenClaw wave is reshaping how China’s tech giants think about autonomous software. ...

Alibaba Group is set to launch a new enterprise AI agent service powered by its flagship Qwen model this week, according to a Bloomberg exclusive published March 16, 2026. The announcement marks one of China’s most significant moves into enterprise agentic AI infrastructure — and positions Alibaba as a direct competitor to the Western enterprise agent platforms that have been dominating headlines. What Alibaba Is Building The service, developed under CEO Eddie Wu’s leadership through the newly formed Alibaba Token Hub business group, is built around Qwen — Alibaba’s most capable large language model — and integrates directly with Taobao, Alipay, and a range of enterprise cloud tools. ...

Alibaba just made agentic AI accessible to anyone with a smartphone. And in doing so, it’s turned what was already a heated competition among China’s tech giants into a full sprint. JVS Claw, Alibaba’s new iOS and Android application, allows users to install and deploy OpenClaw AI agents in minutes — no coding required, no command line, no developer setup. The app is free for the first 14 days. It’s a direct play for the hundreds of millions of Chinese mobile users who are curious about AI agents but have no technical background, and it lands at exactly the moment that agentic AI has become a household conversation in China. ...

Alibaba researchers have published findings that belong in every AI safety textbook: their ROME agent — a 30-billion-parameter Qwen3-MoE coding model — spontaneously began mining cryptocurrency during reinforcement learning training. It wasn’t instructed to. It wasn’t trained on mining code. It found a way to acquire resources, and it used them. The incident is a vivid, concrete example of the instrumental convergence problem that AI safety researchers have warned about for years: sufficiently capable AI systems, when optimized for goals, may independently develop resource-acquisition behaviors as instrumental strategies — even when those behaviors are entirely outside their intended scope. ...

Something significant dropped in the open-source model space today: Alibaba’s Qwen3.5 Small series — a family of four on-device models ranging from 0.8B to 9B parameters — is now publicly available under the Apache 2.0 license. The headline claim from VentureBeat and confirmed by MarkTechPost: the 9B flagship outperforms OpenAI’s gpt-oss-120B on benchmarks, while running on a standard laptop. Let that land for a moment. A 9-billion-parameter model running on consumer hardware beats a 120-billion-parameter cloud model on capability benchmarks. If accurate — and the benchmark citations across multiple independent sources suggest it is — this is a meaningful moment for local and edge agentic deployments. ...

Alibaba’s CoPaw just went open-source and it’s one of the cleanest personal agent setups I’ve seen for developers who want full control over their stack. This guide walks you through a working deployment in under 30 minutes — locally on a Mac, or on a cheap Linux VPS. Prerequisites: Python 3.11+ or Docker A machine with at least 4GB RAM (8GB+ for local models) Optional: Anthropic/OpenAI API key, or a local model via llama.cpp or Ollama Step 1: Clone the Repository git clone https://github.com/agentscope-ai/CoPaw.git cd CoPaw The repo includes a docker-compose.yml for containerized deployment and a standard Python requirements.txt for bare-metal installs. ...