Alibaba VS OpenClaw: New Autonomous AI Agent

Alibaba vs OpenClaw, new autonomous AI agent. So Alibaba just leaked what might be the most important enterprise AI tool of 2026 and nobody in the west is talking about it. Bloomberg broke the story this morning, Alibaba is about to release a brand new AI agent built on the QEM model designed specifically for businesses, not consumers, not developers tinkering on the weekends, businesses. The kind of companies that process thousands of invoices, manage hundreds of employees and run operations across multiple countries.

This tool is being built by the same team that runs DingTalk and is basically China's version of Slack. Over 700 million people use DingTalk, 26 million organizations and now the team behind that platform is building an AI agent that can operate computers, run web browsers and cloud servers on behalf of entire companies. And here's the part that really matters, they're planning to plug this thing into Taobao which is their massive e-commerce platform and Alipay which is how hundreds of millions of people pay for everything in China. So imagine an AI agent that doesn't just answer your questions, it logs into your systems, processes your orders, handles your payments, manages your inventory and does it all without a human clicking a single button.

This is not a chatbot, it's a digital employee. Now if you've been paying attention, this didn't come out of nowhere right. Two weeks ago Alibaba's Tongyi Lab team quietly open-sourced a tool called Kopor. And Kopor is fascinating because it's basically Alibaba's answer to OpenQL for individual users.

It stands for Co-Personal Agent Workstation. You install it on your own machine or deploy it to the cloud, it connects to your DingTalk, Discord, iMessage, Lark and QQ. It remembers your preferences across sessions, it schedules tasks automatically, it runs local AR models so your data never has to leave your computer. Think about that for a second right, Kopor is a personal version.

It handles your emails, summarizes your meetings, scrapes the web for you, drafts your documents and now Alibaba is building the enterprise version. The version that does all of that but for an entire company with built-in security, with data protection features, with direct access to one of the largest ecosystems on the planet. So you've got two products now, Kopor for individuals and this new unnamed enterprise agent for businesses. That is a full stack AI agent strategy, personal and professional, open source and proprietary.

That's not experimentation, that's a product roadmap and the timing is not an accident. Let me tell you what's happening in China right now because it's genuinely hard to overstate. OpenQL, the open source AI agent built by Austrian programmer Peter Steinberger has become a cultural phenomenon in China. Not just a tech product, a cultural phenomenon.

People are lining up by the thousands outside tech company headquarters to get it installed on their laptops. Tencent held a public event in Shenzhen where nearly a thousand people showed up. Students, retirees, office workers, all waiting in line for an engineer to help them set up an AI agent. They're calling it raising a lobster because of OpenQL's red lobster mascot.

People are wearing lobster hats, companies are handing out lobster plush toys. A 77 year old man in Beijing asked his son to install a lobster for him. Local governments are offering subsidies and cash rewards to startups building their OpenQL. ByteDance released their own version called ArcCorp, runs in a browser.

Minimax, one of the companies riding this wave, saw its stock jump up over 600% from its IPO price and according to security scorecard, China-based usage of OpenQL has already surpassed the United States. More people in China are using this tool than in America where it was created. Chinese AR models for the first time surpassed US models in share of tokens processed among the top nine models on the open router marketplace according to HSBC. So this is the environment that Alibaba is launching into.

A country that's going absolutely all in on AI agents. Not just in Silicon Valley boardrooms, in regular people's lives, in their phones, their laptops or offices of government programs. And Alibaba looked at that and said, okay that's cool but now let's build the enterprise version. And here's why I think this matters way beyond China and this is about where you need to pay real attention right.

Gartner, which is one of the most respected research firms in the world, predicted that 40% of enterprise applications will include AI agents by the end of 2026. Up from less than 5% in 2025. That's an eightfold jump in a single year and they project that by 2035, agentic AI could drive 30% of all enterprise software revenue. That's over 450 billion dollars.

The AI agent market is growing at 46% a year from about 7.8 billion dollars in 2025 to over 52 billion by 2030. 50% of companies already have agents in production and 93% of leaders believe the organizations who successfully scale AI agents in the next 12 months will gain a competitive advantage over everyone else. This isn't a trend, it's a phase change and Alibaba just made one of the biggest moves in the entire space. Let me put this in context.

Alibaba's CEO Eddie Wu pledged over 53 billion dollars toward AI infrastructure and development. He said the company could spend even more. Their cloud division has been growing at 34% year over year. AI related product revenue has been growing at triple digits for nine consecutive quarters.

Nine quarters in a row of triple digit growth. The Kuen model family has been downloaded over a billion times globally. Their consumer AI app surged from 31 million monthly active users in January to 203 million in February this year. That's not a typo, it actually went from 31 million to 203 million users in a single month.

But here's the tension underneath all of this and I want to be honest about this because I think it really matters. Two weeks ago the tech lead of Kuen, a 32 year old engineer named Junyang Lin, suddenly resigned. He posted five words on x. Me stepping down, bye my beloved Kuen.

Alibaba's stock dropped 5.3% in Hong Kong that same day. It was their biggest intraday lost since October and Lin wasn't the only one. The head of post training for Kuen, Yu Bowen, left the same day. The lead of Kuen code, Hui Bin Yue, had already left in January and joined Meta.

Three senior departures in two months for the most important AI team in all of China. The reason? Alibaba reorganized the Kuen team. They split it from a tight vertically integrated unit where Lin had full control into separate horizontal teams managed by different leaders.

Lin didn't agree with the new structure. He believed AI development works best when one team controls everything from pre-training to development and deployment. Alibaba's leadership believed the projects had gone too big for one person to run. And I get the skepticism when you hear about leadership turmoil at a major AI company.

I also get that reorganizations happen all the time at companies that size. What matters is what they do next. And what Alibaba is doing next is launching an enterprise AI agent that could be the most commercially significant product in their AI portfolio. Because here's the thing about the enterprise AI agents that most people don't understand.

The consumer side is exciting, the viral moments are fun, the lobster hats make awesome photos in China. But the money is in the enterprise. Think about it this way. OpenCore is incredible for individual productivity.

It can book your flights, manage your inbox, browse the web for you. But when a company with 10,000 employees needs AI agents that can operate their cloud servers or process their supply chain data or integrate with their payment systems to do all of that whilst keeping sensitive business data secure, that's a completely different product. That's a completely different level of complexity. And that's where the real revenue is.

Alibaba knows this. Their AI revenue has been growing at triple digits, but of a relatively small base. Their AI revenue run rate is estimated at around a billion dollars. Microsoft Azure's AI revenue is about 13 times larger.

To close that gap, Alibaba needs enterprise customers spending real money on real AI products, not just consumers downloading a free app. And that's exactly what this new enterprise AI agent is designed to do. Now I want to talk about Copore for a minute because I think it's being massively underrated and it connects directly to the enterprise plate. Copore launched on February 28th as an open source project on the Apache 2.0 license.

It was built by the AgentScope team at Alibaba's CloudTiny lab. And on the surface, it looks like just another AI system. But when you dig into what it actually does, it's genuinely different from most things out there. First, it has persistent memory.

And this is huge. Most AI tools forget everything the second you close the chat. Copore uses a memory system called REME, which stands for Remember Me, Refine Me. It stores your preferences, your workflows, your past conversations, not just in a basic way.

It uses a hybrid system that combines semantic vector search and keyword search to find the right memories at the right time. And all of that memory is stored in files that you can read, edit, move around, your data with your control. Bear in mind this is free, right? This is a free open source project.

Second, it works across every platform you use. So, DingTalk, Discord, iMessage, LarQQ. You set up one Copore instance and talk to it from any of those platforms. Now, you might not use those platforms yourself, right?

Apart from Discord or iMessage. But imagine China, right? QQ, LarQQ, these are big, big platforms along with DingTalk as well. So it's the same memory, same context, same agent everywhere.

Third, it's designed for automation, not just conversation. So you can schedule tasks, tell it to check your server logs every morning at 9am, tell it to compile a daily list of trending posts from Reddit, and send it to your DingTalk chat. Tell it to draft a weekly report every Friday at 5pm. It just does it autonomously.

And fourth, this is the part that really matters for developers, it has an extensible skill system. You can write custom Python functions and drop them into a skill directory. If you want your agent to query a specific database, write a skill. If you want it to scrape a particular website, write a skill.

If you want it to integrate with your company's internal API, just write a skill, right? You don't have to touch the core code, just add your function in the agent pixel. Now, here's why this is so important in the context of the new enterprise agent. Copore is the testing ground.

It's where Alibaba is working out the architecture, the memory systems, the multi-channel deployment, the skill extensibility. All of that R&D directly feeds into the enterprise product. Copore is the open source lab. The enterprise agent is the commercial product.

It's the same playbook Meta used with Lama, right? Release the open source version, let the community find the bugs, build the ecosystem, prove the concept, and then sell the enterprise-grade version with security, compliance, and integration features that big companies need. And Alibaba has something that almost no other AI company does. They have the commerce ecosystem.

They have Taobao with hundreds of millions of shoppers. They have Alibaba processing payments at massive scale. They have DingTalk with 700 million users managing their work lives. They have cloud infrastructure serving millions of businesses.

So when their enterprise AI agent plugs into all of that, the possibilities are staggering. Now, imagine you're running a mid-sized e-commerce company in China. Right now, you have a team managing your Taobao storefront. You have another team handling customer service.

You have people processing orders, managing inventory, coordinating suppliers, handling returns. Now, imagine an AI agent that sits inside DingTalk, connects to your Taobao store, processes orders through Alipay, manages your inventory on the cloud, handles routine customer inquiries, and escalates only the complex issues to a human. That's not science fiction. That's what this product is designed to do.

And when you understand that, you understand why Alibaba is spending $53 billion on it. Now, I know what some of you are thinking. You're thinking, okay, Julian, this is a Chinese company, Chinese market. Why should I care?

And I get that. Here's why this matters to everyone. Because enterprise AI agents are coming everywhere, not just in China, everywhere, right? Salesforce is building them, NVIDIA, Microsoft ServiceNow building them, UiPath.

Every major enterprise software company on the planet is racing to embed AI agents into their products. And right now, China is moving faster on adoption than anyone else. When Gartner says 40% of enterprise apps will have AI agents by the end of 2026, they're not just talking about Silicon Valley startups. They're talking about the global enterprise software market.

And what's happening in China right now is the leading indicator of what's about to happen everywhere else. The pattern is always the same. First, the technology works, then early adopters go crazy. Then enterprises figure out how to deploy it safely.

Then it becomes a new normal. China is somewhere between stages two and three right now. The rest of the world is really between one and two. And if you're sitting there watching that and thinking, you have time, you don't, right?

The companies that figure out AI agents in the next 12 months are going to operate at a completely different level than the ones that wait. And this is exactly why I built the AI Profit Boarding, because this stuff is moving so fast. By the time you read about it in mainstream news, the opportunities already moved. Inside the AI Profit Boarding, we're breaking down these tools, those strategies, those shifts in real time.

Not in theory, in practice. We give you video tutorials, step-by-step guides. You can connect with me, you can ask a community of 2,600 people what to use, how to use it, and how to build systems that actually make money with AI agents. If you're not inside, you're already behind.

Link in the description or just go to the AIProfitBoarding.com. Let me bring this back to the bigger picture. What Alibaba is doing right now is building the infrastructure for an AI-first economy, right? Copor handles the individual.

The new enterprise agent handles the business. DingTalk provides the communication layer. Quen provides the intelligence. Taobao and Alipay provide the commercial backbone.

$3 billion in investment provides the fuel. That is a full-stack AI agent ecosystem from personal assistant to enterprise platform to commercial engine, all connected, all powered by the same underlying AI. And here's the part that should really make you think. Alibaba isn't alone.

Tencent is building AI agents for WeChat. ByteDance launched ArtCore. Baidu has an OpenCore app. Every major Chinese company, tech company especially, is in this race.

And they're competing in a market where adoption is happening at a speed that makes Silicon Valley look slow. In the West, people are still debating whether AI agents are ready for prime. In China, the elderly even are queuing up for AI agent installations for OpenCore outside Tencent's headquarters. There was actually thousands of them last week, right?

So that gap in adoption speed is going to have consequences, serious ones, because the companies and the countries that figure out AI agents first are going to have a structural advantage in productivity and efficiency in the abilities to do more with less. I'll keep saying this and I'll say it again. The question isn't whether AI agents are going to transform business already happening. The question is whether you're going to use them and be using them or competing against people who aren't.

Now, let me give you some concrete things you can do right now. If you're technical, go look at CodePort. It's open source, it's free, it's one of the most well-architected AI agent frameworks I've seen. Install it, connect it to your word tool, start building skills.

Documentation is pretty solid, right? So both in Chinese and English, it runs on Windows, Mac, and Linux, and you can have it set up in three commands. If you're not technical, start paying attention to which enterprise tools in your workflow are adding AI agent capabilities. Salesforce, HubSpot, Notion, Monday.com, Slack, they're all building this, right?

Ask your vendors what their AI agent roadmap looks like. If they don't have one, that's a big red flag. If you're a business owner or a leader, start thinking about which repetitive processes in your company could be handled by an AI agent. Customer service, scheduling, data entry, report generation, inventory management.

Start small, pick one workflow, automate it, learn what works, and then you scale it up. If you're an investor or just someone who follows markets, pay very close attention to what happens when Alibaba reports earnings this Thursday. They're expected to show continued triple digit AI revenue growth. The question is whether this new enterprise agent becomes a meaningful revenue driver, because if it does, the implications are massive, not just for Alibaba, for the entire enterprise AI market.

And I want to leave you with something that I think gets lost in all the headlines and the hype and the stock market moves. What we're watching right now is the beginning of a fundamental shift in how work gets done. Not just a tool, not just a new app, a new paradigm. The idea that every person in every company will have AI agents working alongside them, handling the routine, managing the complexity, so humans can focus on the things that actually require human judgment.

Alibaba is betting 53 billion dollars. That is where this world is going, right? China is adopting it faster than anyone expected, and the tools are getting better every single week. The people who figure this out early are going to have an enormous advantage, and the people who wait are going to wonder how they fell so far behind so quickly.

That's the story, that's what's happening. And if you're watching this, you're already ahead of most people. The question is what you do next. If you want to stay ahead of every development like this, if you want to make sure that you never miss an update again, if you want to know how to actually implement this, make sure you subscribe.

And if you want to go deeper and actually learn how to build these tools, with these tools, and how these updates work for you, the AR Profit Ballroom is waiting for you. Link in the comments description, or just go to the arprofitballroom.com. Thanks for watching.