Global AI Companies Are Integrating OpenClaw: What Are They Really Fighting For?
On March 17, at the GTC 2026 conference, NVIDIA launched NemoClaw. But NVIDIA isn't alone. Over the past two weeks, everyone from Kimi, Zhipu, and MiniMax to Tencent, Alibaba, Baidu, and Xiaomi has been building around OpenClaw.
Some are building enterprise security shells, others are creating one-click deployment tools, office entry points, or even specialized models dedicated to agents.
Today, let's discuss what lies behind this "bandwagon effect": What are the tech giants truly fighting for?
It's Not Just About the Open Source Project
On the surface, it looks like collective跟风 (following the trend). But if you look closer, every company is targeting a different layer of value. The industry has moved past simply competing on model parameters (which is becoming like the late-stage mobile phone market). OpenClaw has pierced through to the next layer of value: Execution.
If AI can truly take over task flows, the most valuable assets are no longer just the models themselves, but:
- Who captures the User Entry Point?
- Who hosts the Agent Runtime Environment?
- Who solves the critical Security and Permission issues for enterprises?
- Whose model is optimized for Long-Chain Execution to consume more tokens?
Decoding the Giants' Strategies
1. NVIDIA: Seizing the Enterprise Infrastructure
Product: NemoClaw
Strategy: Providing the "Running Ground" for Agents.
At GTC 2026, Jensen Huang announced NemoClaw, describing it as a toolchain to build and verify OpenClaw agents locally on DGX Spark/Station before scaling to data centers. NVIDIA isn't trying to build a consumer agent product; they are building the infrastructure that allows agents to enter the enterprise safely.
OpenClaw is powerful but "wild." Enterprises ask: "Who manages this? What data can it touch? Can it run only on our intranet?" NVIDIA answers these questions by providing isolated sandboxes (OpenShell), security protocols, and scalable deployment. They are selling the "AWS" of the Agent era.
2. Alibaba: Capturing the Cloud & Collaboration Layer
Alibaba is playing a dual game:
- Front-end: Wukong, a multi-agent platform for document editing, spreadsheet updates, and meeting transcription, integrating with DingTalk, Slack, Teams, and WeChat.
- Back-end: HiClaw, focusing on private deployment, collaboration, and management capabilities on Alibaba Cloud.
The Goal: If you want to run OpenClaw in your company, the smoothest path is through the Alibaba Cloud and DingTalk ecosystem. They are positioning themselves as the primary service provider for agent operations and token consumption.
3. Baidu: Building the Full-Stack Digital Layer
Baidu is rolling out the "Lobster Family Bucket":
- DuMate: Desktop assistant.
- RedClaw: Mobile platform.
- DuClaw: Cloud services.
- Xiaodu: Integration with smart hardware.
The Goal: Unlike a single tool, Baidu wants to weave agent capabilities into every layer of the user's digital life—desktop, mobile, cloud, and hardware. They are fighting for the Omni-channel Entry Point.
4. Tencent: Securing the Ecological Niche
Tencent is leveraging its massive existing user base:
- WorkBuddy: A desktop AI agent for office scenarios, compatible with OpenClaw skills.
- QClaw: Internal testing for one-click deployment and natural language PC control.
- Sponsorship: Becoming a major sponsor of the OpenClaw community.
The Goal: Tencent doesn't need to define the底层 (bottom-layer) standards. They just need to ensure that when users habitually hand tasks to AI, that interaction happens within WeChat, QQ, or Tencent Office. They are fighting for the Habitual Entry Point.
5. Model Providers (Kimi, Zhipu, MiniMax): Optimizing the "Brain"
For model companies, the game is about Token Consumption and Task Completion.
- Kimi (Moonshot): Integrated OpenClaw to simplify deployment, turning agents into high-frequency model consumption scenarios.
- Zhipu AI: Released GLM-5-Turbo, explicitly optimized for OpenClaw long-chain tasks. They distinguish between "Chat Models" (one-off answers) and "Agent Models" (completing complex workflows).
- MiniMax: Launched MaxClaw, a cloud-based assistant to run agents directly without local setup.
The Goal: In the agent era, a single user request triggers a long chain of planning, tool usage, and error correction. This means significantly higher token usage. These companies are fighting to be the Default Brain that powers these long workflows.
6. Xiaomi: The Terminal Invasion
Xiaomi is testing Xiaomi miClaw, a mobile AI agent system based on the MiMo large model. It aims to understand user intent and execute tasks by calling apps and system tools directly on the phone.
The Goal: Embedding the agent directly into the OS and Hardware that users cannot live without.
The Four Layers of the New Business War
Summarizing the movements of the past two weeks, we see four distinct business layers igniting simultaneously:
- The Entry Layer (User Habit): Who is closest to the user? (Tencent, Baidu, Xiaomi)
- The Runtime Layer (Infrastructure): Who handles deployment, scheduling, and orchestration? (NVIDIA, Alibaba)
- The Security Layer (Enterprise Trust): Who makes enterprises feel safe enough to sign the purchase order? (NVIDIA, specialized security firms)
- The Model Layer (The Brain): Whose model is best suited for long-chain execution? (Kimi, Zhipu, MiniMax)
Conclusion: Execution is the Next Big Business
OpenClaw is hot, but it is not yet mature. Challenges in stability, control, security, and auditing remain. However, precisely because it is still growing, this window of opportunity exists.
Why are global and Chinese AI companies suddenly moving in unison around OpenClaw?
Because "Execution" is the next true big business after Large Language Models. The era of just "chatting" is ending; the era of "doing" has begun.