Global AI Investment Hotspots: Exploring Key Drivers of a Future Technology-Driven Economy

Artificial intelligence (AI) technology is transforming the global industrial landscape at an unprecedented pace, with investment trends and hotspots becoming a focal point for policymakers and investment institutions worldwide. According to data from the European Parliamentary Research Service (EPRS), the global AI market value reached €130 billion in 2023 and is projected to grow to €1.9 trillion by 2030, indicating its enormous market potential. This article will analyze investment trends and global AI industry hotspots across three major markets (the United States, China, and the European Union), and delve into key future investment directions and challenges.

I. Investment Trends in the Three Major Markets

Global AI investment is primarily concentrated in the United States, China, and the European Union. Private and public capital injections in these markets constitute the main driving force behind the advancement of AI technology and applications.

1. United States: Global Leader in Generative AI

The United States leads in AI investment in both scale and depth. In 2023, private AI investment in the U.S. reached €62.5 billion, accounting for the vast majority of the global market. Particularly in the field of generative AI, U.S. companies such as OpenAI, Anthropic, and Google led 73% of large language model (LLM) development globally, becoming the core drivers of technological innovation.

At the government level, U.S. federal AI investment has also seen explosive growth. According to analysis by Brookings, between 2022 and 2023, the potential value of AI-related contracts increased from $355 million to $4.561 billion, an increase of nearly 1200%. Of this, AI investment in the defense sector accounted for the largest share at 95%. Furthermore, the U.S. Department of State announced in 2024 the establishment of the "Partnership for Global AI Inclusion" (PGIAI), collaborating with tech giants such as Amazon, Microsoft, and Nvidia, to promote AI applications in developing countries and enhance technological safety and reliability.

2. China: Government Guidance and Private Capital Advance Together

China ranks second globally in AI investment, with private AI investment reaching €7.3 billion in 2023. China particularly emphasizes the development of large language models, accounting for 15% of global LLM development. Additionally, the Chinese government supports the full-chain development of the AI industry through specialized funds and diversified investment strategies, such as fund-of-funds and direct investment.

According to research by Beraja et al., the Chinese government has invested $184 billion in 9,623 AI companies. These government funds not only boost enterprises' technological output but also provide a solid foundation for the rapid growth of AI startups. For example, SenseTime's breakthroughs in computer vision benefited from early government support, subsequently attracting international capital injections from institutions like Temasek, achieving both technological and commercial development.

3. EU: Trust-Based Investment Strategy

The EU and the UK jointly attracted €9 billion in private AI investment in 2023, primarily focusing on trustworthy AI and digital infrastructure construction. The EU is promoting the "Digital Europe Programme," planning to invest €2.1 billion between 2021 and 2027 to support the application and implementation of AI technology. Concurrently, the EU EIC Fund employs a risk-sharing mechanism, providing financial support for high-risk AI projects to attract more private capital into the market. For example, Graphcore's AI processor technology development successfully proceeded with the support of the EIC Fund, subsequently attracting investment from institutions like Sequoia Capital.

II. International AI Investment Hotspots

Global AI investment hotspots in 2025 are concentrated on three levels: application services, core technologies, and computing resources. The distribution of investments in these areas reflects different stages of technological and market demand.

1. Application Services: The Largest Investment Proportion with Multi-Domain Penetration

The application services layer accounted for 45% of global AI investment in 2024, making it the highest invested area. Productivity tools (e.g., ChatGPT, DeepL) and creative industries (e.g., Midjourney) continue to be favored by the market. Simultaneously, investments in vertical domains such as healthcare (e.g., Insitro) and defense (e.g., Anduril) are also on the rise, indicating the diversification of AI applications.

2. Core Technologies: The Technical Cornerstone of Large Language Models and Generative AI

The core technologies layer accounts for 38%, focusing on the development of large language models (LLMs) and foundational models. Companies like LangChain and Anthropic have attracted substantial funding to accelerate model performance optimization and application expansion. These technologies are not only the bedrock of AI applications but also determine the future competitive landscape of the market.

3. Computing Resources: Foundational Support for Data and Computing Power

The computing resources layer accounts for 17% of global AI investment, primarily concentrated in cloud service providers (e.g., AWS, Google Cloud) and data annotation tools (e.g., Cleanlab). As AI models increasingly demand data storage and processing capabilities, the investment potential in this area continues to climb.

Figure 1 Global AI Investment Hotspots 

Figure 2 Global AI Investment Hotspot Applications

 III. Conclusion

Artificial intelligence is leading a wave of global economic and technological revolution, with investment hotspots showing highly diversified trends, from application services and core technologies to computing resources. The three major markets, centered around the United States, China, and the European Union, not only boast significantly larger capital scales but also demonstrate distinct competitive advantages and strategic priorities in technological innovation and application implementation. From the U.S.'s leadership in generative AI to China's government-guided funds and the EU's trustworthy AI promotion strategy, all fully demonstrate the effectiveness of "hybrid model" investment strategies.

Looking ahead, AI investment will focus more on technological breakthroughs such as large-scale language models, multimodal AI, and edge computing. Simultaneously, as technology deepens its applications, data governance, ethical regulations, and international cooperation will also become core issues for policymakers and investment institutions. Nations, enterprises, and investors need to find a balance between technological innovation, commercialization, and social responsibility to jointly build a smarter, more efficient, and inclusive global economic system.