Gartner: Half of global enterprises to adopt Chinese AI models by 2027

Half of the enterprises worldwide are expected to include Chinese large language and multimodal models in their AI portfolios by 2027, surging from 5 percent in 2025, the latest Gartner report showed.

The forecast, presented at Gartner's top 10 AI trends in China for 2026, points to growing international demand for Chinese models as companies seek affordable, adaptable foundations for AI applications.

Fay Fei, director analyst at Gartner, said China's emphasis on cost efficiency and engineering optimization is making its models a foundation for developers worldwide, with openness helping turn technical strengths into lasting competitive advantages.

"This is lowering deployment barriers for developers and enterprises worldwide," Fei said.

Making model weights available allows businesses to customize models and choose how to deploy them, offering greater flexibility over costs and data management. Fei said collaboration around these models also supports faster experimentation and innovation.

The report also highlights China's push for greater technological self-reliance. The country met 45 percent of its domestic demand for consumer electronics semiconductors in 2025, according to Gartner data. By 2030, the research and advisory platform expects that share to reach 75 percent, with self-sufficiency across the overall semiconductor market rising to 51 percent.

China's large domestic market, AI talent, and infrastructure provide further advantages, Fei said. Rapid deployment across varied business settings can generate feedback that helps developers improve applications and expand their use.

Open-weight strategies and a scalable AI agent workforce feature prominently in this year's report, which traces China's progress from pursuing affordable AI to integrating intelligent systems into everyday operations.

With 16 percent of respondents having embedded AI agents in their products or services, the report identifies agent capabilities, personal agents, and business knowledge structures as key elements of a scalable AI workforce.

Fei said personal agents are becoming more adaptable to individual preferences and work contexts, while enterprises are building systems that help agents understand business relationships, rules, and decision-making constraints.

These developments connect China's model strengths to a broader commercial challenge: turning increasingly capable AI into dependable tools for daily work.

However, Fei noted that the industry still remains in transition from proof of concept to deployment at scale, and strong model performance does not necessarily translate into reliable business outcomes.

"Model capabilities emerge suddenly with version releases, but the value and impact of real-world commercial applications must grow incrementally through deployment," she said.