CMG unveils top 10 AI trends for 2026

Artificial intelligence is rapidly reshaping economies and daily life across the globe, making its governance, accessibility and sustainability more critical than ever.

Against this backdrop, China Media Group (CMG), in collaboration with leading think tanks and universities, has released a report outlining the top 10 AI trends expected to define 2026, highlighting advances in governance, computing power, applications and safety.

1. AI Governance Goes Global

The report places inclusive and shared AI development at the center of the global agenda. At the 32nd APEC Economic Leaders’ Meeting in November 2025, Chinese President Xi Jinping proposed establishing a World Artificial Intelligence Cooperation Organization to provide AI-related public goods globally. Enhanced international cooperation is seen as essential for economic growth and for addressing challenges such as climate change and public health.

2. Rapid Expansion of Intelligent Computing Power

Advances in chip technology are driving a surge in computing capacity. Domestic AI chips are expected to see large-scale deployment in targeted applications, while GPU clusters with tens of thousands of units have become standard for training large models. China’s “Eastern Data, Western Computing” initiative has further improved nationwide access to computing resources.

3. AI Applications Enter the Mainstream

AI agents are set to be widely adopted across industries, shifting from general-purpose tools to specialized, task-focused solutions. In January, China unveiled an action plan targeting a secure and reliable supply of core AI technologies, including the launch of 1,000 high-level industrial AI agents by 2027.

4. Rise of Multi-Modal Interaction

AI systems are evolving from standalone tools into intelligent collaborators. Breakthroughs by domestic large language models in 2025 significantly reduced deployment costs. Supported by improved computing capacity, AI is increasingly capable of handling multi-modal data such as text, images, audio, video and 3D point clouds.

5. Proliferation of AI-Native Devices

AI-powered smartphones, PCs and extended reality (XR) devices continued strong growth in 2025. Hardware design is shifting from AI-enabled to AI-native, with next-generation smart terminals deeply integrated with multi-modal large models, reshaping education, healthcare and entertainment experiences.

6. AI Meets Embodied Intelligence

The convergence of physical AI and embodied intelligence is enabling robots to learn from real-world interactions and collaborate with humans. The report notes that robots are moving from prototypes to mass production, with applications expanding into manufacturing, logistics, elderly care and healthcare. China’s embodied intelligence market is projected to reach 5.3 billion yuan ($759 million), accounting for roughly 27 percent of the global total.

7. Specialization in Scientific Research

“AI for Science” is accelerating breakthroughs in fundamental research. AI models are increasingly able to generate hypotheses, design experiments and validate results, driving innovation in materials science, astrophysics and life sciences, including drug discovery and antibody design.

8. Convergence of Frontier Technologies

Brain-inspired intelligence is merging with fields such as data science and biological imaging. Advances in brain science are also refining AI algorithms for autonomous driving and intelligent healthcare, while deeper integration is expected to yield progress in spiking neural networks and neuromorphic computing.

9. Growing Emphasis on Green AI

The rapid expansion of AI data centers is pushing up global electricity demand, raising concerns over energy supply and environmental impact. The report highlights efforts to develop energy-efficient model architectures and expand clean-energy-powered computing centers to balance computing growth with carbon reduction goals.

10. Rising Safety and Security Challenges

In response to rapid AI advancements, China released its AI Safety Governance Framework 2.0 in September, promoting a cross-border and cross-industry governance model. The report underscores that ethics, privacy and security will remain central as governance tools and technical safeguards evolve to ensure safe and sustainable AI development.