The Race to Put AI Agents Everywhere

2026-03-17 · Source: The AI Daily Brief: Artificial Intelligence News and Analysis · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Cloud Computing & IT Infrastructure · Depth: Intermediate, extended

Summary

Q1 saw the emergence of AI agents, with Q2 now marked by an intense race to make them enterprise-ready, driven by major players like Nvidia, Manus, Adaptive, and OpenAI. Nvidia's CEO Jensen Huang forecasts a trillion dollars in revenue by 2027, while Meta secured a \$27 billion deal with Nebius, underscoring the massive demand for AI compute capacity. Key developments include Nvidia's Nemo Claw for secure enterprise agents, Manus and Adaptive launching desktop agents, and OpenAI's internal "code red" refocus on enterprise and coding productivity. Concurrently, there's a notable shift in the open-source AI landscape, with Chinese labs like Alibaba and Z.AI increasingly moving their most powerful models to closed-source for monetization, while using lightweight open-source versions for distribution. This push aims to overcome challenges like security and integration, enabling agentic systems to transform enterprise workflows and digital businesses.

Key takeaway

The AI industry is rapidly productizing agents for enterprise, with NVIDIA's NemoClaw providing secure, policy-based OpenClaw integration and OpenAI's Codex leveraging subagents for parallel task execution. This push, also seen in new desktop agents from Manus and Adaptive, aims to unlock agentic AI's estimated \$3 trillion productivity potential by addressing security, scalability, and local context. However, the race faces significant compute capacity constraints, as evidenced by Meta's \$27B Nebius deal, and evolving IP strategies like Z.AI's shift to closed-source models.

Topics

• AI Agents
• Enterprise AI Adoption
• AI Infrastructure
• Open-Source AI Strategy
• NVIDIA Hardware

Best for: Investor, CTO, VP of Engineering/Data, AI Engineer, Director of AI/ML, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI Daily Brief: Artificial Intelligence News and Analysis.