Central SOEs Go All-In on AI: A Breakthrough Year Expected in 2025

Artificial intelligence has transitioned from theoretical research to a critical phase of large-scale commercialization, with China's central state-owned enterprises (SOEs) emerging as key drivers of this trend. By 2024, over 50 central SOEs have significantly ramped up their investments in AI, laying a strong foundation for a technological boom anticipated in 2025. By examining the background and strategies behind these investments, we can glimpse the contours of an industry-wide AI revolution.

SOEs’ Heavy Investment in AI: Not Just a Trend but a Strategic Move

Central SOEs hold a pivotal position in China's economy, and their investment directions often reflect national strategic priorities. From energy to telecommunications to manufacturing, AI's potential has permeated nearly every sector. These investments are not merely a reaction to technological trends but are strategically driven by the dual forces of digital transformation and global competition:

1. Empowering Traditional Industries: AI applications in traditional sectors, such as smart grids, automated production lines, and logistics optimization, allow SOEs to retain their conventional advantages while reducing operational costs and improving efficiency.

2. Driving Industrial Upgrades: SOEs leverage AI to reshape industrial value chains, particularly in advanced manufacturing and new energy sectors, by enhancing competitiveness through intelligent forecasting and precision control.

3. National Security and Independent Innovation: In an increasingly complex global landscape, self-reliant AI technologies are critical to safeguarding national security.

Investment Focus: Multimodal AI, Foundational Models, and Real-World Applications

While AI spans numerous technological branches, SOE investments are concentrated in multimodal AI, foundational model development, and application deployment in specific industry scenarios. These strategies reflect a balanced consideration of technological maturity, industry demands, and future potential:

• Multimodal AI: AI technologies capable of processing text, images, and speech simultaneously are at the forefront of development. These technologies enable advanced AI interactions, such as command-and-control systems in complex environments.

• Foundational Model Development: Large language models and generative pre-trained models (e.g., GPT) are major focal points for SOEs. These models not only significantly enhance the efficiency of industry applications but also serve as core technologies that can be exported to other enterprises.

• Industry-Specific Applications: Examples include smart steel plants, autonomous mining truck fleets, and intelligent energy dispatch systems, where AI technologies are demonstrating tangible value.

2025: Driving Forces Behind the AI Industry Boom

As SOE strategies deepen, 2025 could mark a watershed year for widespread AI adoption. Several factors are converging to drive this momentum:

• Policy Support and Capital Infusion: Numerous national policies are backing AI development, while large-scale investments from SOEs are accelerating technology adoption and promotion.

• Advancements in Technological Maturity: By 2024, breakthroughs in foundational AI technologies, including more efficient training methods and low-power chip technologies, have been achieved.

• An Emerging Industry Ecosystem: SOE investments are fostering not only individual enterprise growth but also a collaborative ecosystem encompassing algorithms, hardware, and applications.

Implications for Businesses: Seizing the Opportunity

For small and medium enterprises (SMEs) and developers, SOE strategies open up significant opportunities for collaboration:

1. Leveraging Open Platforms and APIs: AI ecosystems led by SOEs are often presented in a platformized manner. SMEs can quickly integrate core technologies via APIs, reducing development costs.

2. Focusing on Niche Market Needs: While large enterprises focus on overarching strategies, SMEs can target niche markets with tailored solutions that complement SOE initiatives.

3. Learning from Technical Standards and Best Practices: SOEs' technical practices provide valuable benchmarks for others, especially in areas such as model training, data management, and security governance.

China's central SOEs have become a formidable force in the global AI industry. For developers, technology providers, and even consumers, this is not only an opportunity to observe technological trends but also a defining moment to witness industrial transformation.