It’s no longer about having the best AI model: The challenge lies in agents

As the AI arms race between the United States and China intensifies, the spotlight is shifting from large language models to autonomous AI agents. While powerful models like Gemini, DeepSeek, or Qwen compete on benchmarks such as token generation speed or programming accuracy, experts now argue that true strategic advantage lies in building agents capable of independent decision-making.

Agents mark the next frontier in the AI race

Unlike traditional models that respond to individual prompts, AI agents are designed to plan, reason, and act autonomously. This evolution allows them to perform complex tasks—such as managing workflows or executing multistep goals—without requiring constant human input. According to researchers like Arthur Lai and Jason Corso, this paradigm shift could redefine what counts as meaningful progress in AI.

In the current geopolitical landscape, AI agents represent a deeper integration of intelligence into national infrastructure, from industrial automation to defense strategy. Models still matter—especially since agents rely on them as a core component—but the focus is now on building systems that can operate dynamically and with minimal supervision.

Both the U.S. and China have made significant strides. China’s DeepSeek, Hunyuan, and Ernie are impressive, but they still function within the boundaries of prompt-response interaction. Meanwhile, the real contest is unfolding in developing systems that think and act, not just predict and reply.

Ultimately, AI success will hinge less on isolated model performance and more on real-world applicability—a space where agents can outpace static models. Companies that master this leap will lead the next phase of the AI revolution.