As we stand in the final quarter of 2025, the global artificial intelligence (AI) industry has transcended the realm of speculative technology and become a core driver reshaping global economic patterns. From record-breaking investment scales to the increasingly fierce geopolitical competition around technology dominance, and from the accelerated landing of practical applications to the urgent call for global governance, the AI sector presents a complex landscape of opportunities and challenges. This analysis, from an objective third-party international perspective, aims to dissect the current state of the global AI industry and provide insights into its investment prospects.

Current State of the Global AI Industry: A Turning Point of Intensive Growth

The year 2025 marks a critical turning point for the global AI industry, following the explosive growth in 2024. Multiple core indicators reflect the industry’s robust momentum, while structural changes and regional dynamics are reshaping its development trajectory.

1. Investment Scale Hits New Highs, with Mega-Deals Dominating the Landscape

The global AI venture capital market achieved a historic breakthrough in 2024, surpassing the $100 billion mark for the first time to reach $100.4 billion, according to a report by CB Insights . This growth momentum peaked in the fourth quarter of 2024, with financing volume surging to $43.8 billion, a sequential increase of over 250%. A prominent feature of this investment boom is the dominance of large-scale transactions: ultra-large financing (single transactions exceeding $100 million) accounted for 80% of the total financing in Q4 2024 and 69% for the full year. Among the 13 financing deals exceeding $1 billion globally in 2024, four of the top five went to large model developers and infrastructure providers such as OpenAI, xAI, and Anthropic . This trend underscores the rigid demand for high-cost inputs such as computing power, talent, and energy in the AI industry, as well as investors’ strong confidence in leading enterprises.

Notably, the early-stage investment market remains active amid the prevalence of mega-deals. Data shows that 74% of investment transactions occurred in the early stages, a significant increase from 67% in 2021 . This dual-track investment pattern—simultaneously betting on industry giants and nurturing emerging innovations—reflects the rationality of capital to a certain extent while laying the groundwork for the next wave of technological breakthroughs.

2. Investment Focus Shifts Upstream: Infrastructure Gains Preeminence Over Vertical Sectors

A structural change in AI investment is the declining proportion of vertical sectors. The share of AI investment in fintech, digital healthcare, retail technology, and other vertical fields has dropped from 38% in 2019 to 24% in 2024 . This shift indicates that capital is increasingly flowing to upstream infrastructure and horizontal application platforms driven by the rise of generative AI. Investors are more inclined to deploy funds in technology platforms that can provide basic support for various industries, reflecting a strategic layout for the core links of the AI industrial chain.

Meanwhile, generative AI has become a core driver of global AI market growth. According to IDC forecasts, the global generative AI market will achieve a five-year compound annual growth rate (CAGR) of 56.3%, reaching $607.1 billion by 2029, accounting for 48.1% of the total AI investment scale . This technology is accelerating its penetration into software development, telecommunications, finance, and other fields, driving improvements in industry efficiency and innovation capabilities.

3. Regional Competition Intensifies: The U.S. Leads, Europe Emerges, and Sino-U.S. Divergence Takes Shape

Geographically, the U.S. remains the dominant force in the global AI market, capturing 76% of the total financing in 2024 . IDC data further confirms that the U.S. accounts for over 55% of the global AI market scale, and the combined market share of China and the U.S. is close to 70%, making them the two major driving forces of the global AI industry .

Europe is emerging as a strong contender, with remarkable potential. It occupies eight of the top ten high-potential regions outside the U.S., and Israeli AI enterprises lead with a median Mosaic score of 700, thanks to their strong technical talent pool and mature entrepreneurial ecosystem . Europe’s early-stage investment ratio reached 81%, a seven-year high, and the EU has emphasized the strategic importance of expanding late-stage investment scale, striving to build a complete innovation chain .

China and the U.S. have formed differentiated development paths. The U.S. has launched initiatives such as the “Winning the AI Race: U.S. AI Action Plan” and the AI “Genesis Program,” aiming to maintain technological leadership through deregulation and closed-source models to build technical barriers . In contrast, China is advancing the “AI +” action, focusing on scenario cultivation and application expansion domestically, and adopting an open-source and cooperative strategy internationally . This geopolitical game has led to increased demands for sovereign AI from countries in Europe, the Middle East, Southeast Asia, and Africa, which are adopting a “hedging balance” strategy between China and the U.S. .

4. M&A Activities Remain Active, and Ecosystem Layout Becomes a Strategic Focus

The global AI M&A market maintained strong momentum in 2024, with 384 transactions completed, nearly matching the 2023 record of 397 . Europe performed particularly prominently, accounting for more than one-third of global AI M&A activities, with the UK leading Europe with 32 transactions, followed by Germany (18) and France (16) . Meanwhile, U.S. tech giants such as NVIDIA, AMD, and Salesforce actively participated in this wave of integration through acquisitions to improve their AI technology layouts .

Tech giants are also deepening their ecosystem layout through strategic investments. In Q4 2024, active corporate investors included Google (GV), NVIDIA (NVentures), Qualcomm Ventures, and Microsoft (M12) . For start-ups, cooperating with these giants not only provides financial support but also access to key cloud computing infrastructure and chip resources, forming a mutually beneficial ecological cycle .

AI Investment Prospects: Opportunities Amid Uncertainty

The long-term growth potential of the AI industry is undeniable, but the short-term market also faces risks such as valuation bubbles and uncertain business models. For investors, clarifying investment logic, identifying high-potential tracks, and avoiding potential pitfalls are crucial.

1. Long-Term Growth Drivers: Clear Track and Huge Market Space

IDC predicts that the global AI IT investment scale will grow from $315.9 billion in 2024 to $1.2619 trillion in 2029, with a five-year CAGR of 31.9% . This indicates that the AI industry will maintain high-speed growth in the next five years. From a regional perspective, emerging markets such as the Middle East, Africa, and Latin America are expected to become new growth engines, with a five-year CAGR of 40% . In China, driven by the “AI +” action, the AI investment scale is expected to reach $111.4 billion by 2029, with a five-year CAGR of 25.7% .

From an application perspective, software and information services, telecommunications, and banking are the three industries with the largest AI investment. By 2029, their respective shares will be 43.5%, 7.0%, and 6.0% . Generative AI’s in-depth application in these fields—such as intelligent code generation, network optimization, and real-time anti-fraud—will continue to release commercial value, providing sustained impetus for market growth.

2. Core Investment Logic: From Revenue Expectations to Talent and Technological Potential

The market’s evaluation criteria for AI enterprises are undergoing profound changes. Investors are no longer simply based on current revenue expectations but pay more attention to technical talent reserves, innovation path choices, and the potential value of breakthrough technologies . Emerging enterprises such as Safe Superintelligence and Thinking Machines Lab have gained investor favor despite not yet launching commercial products, largely due to their assembly of top-tier talent and differentiated technical routes . This shift reflects the recognition that scarce research talent capable of achieving breakthrough innovations is the key to determining an enterprise’s long-term competitiveness in the AI field.

3. Potential Risks: Valuation Bubbles and Unproven Business Models

While the AI industry is booming, potential risks cannot be ignored. The first is the risk of valuation bubbles. Many venture capital firms have raised large-scale funds and face pressure to deploy capital, coupled with frequent competitive bidding in the market, which has pushed up the valuations of related enterprises . This irrational factor may lead to a disconnect between enterprise valuations and their actual value.

Second, the sustainability of business models is questionable. Although global tech giants have launched trillion-dollar AI infrastructure investment sprees, a McKinsey report shows that fewer than 10% of enterprises have achieved profit growth through AI deployment . This gap between investment and return has aroused market concerns about whether AI commercialization can form a sustainable profit closed loop to feed back upstream massive capital expenditures.

In addition, geopolitical risks and regulatory uncertainties pose challenges to the industry. The U.S.’s chip export control measures against China and the differing regulatory standards among countries may disrupt the global AI industrial chain and supply chain . Meanwhile, the call for global governance of AI is increasing, and future regulatory policy changes may have a significant impact on enterprise operations.

Conclusion: Rational Layout in the Boom

The global AI industry is in a critical period of transition, with technological breakthroughs and industrial applications advancing hand in hand, and global competition and governance needs coexisting. For investors, the AI sector undoubtedly represents a long-term high-growth track worthy of attention, but it requires rational judgment amid the boom.

In terms of investment strategy, it is advisable to adopt a diversified layout: on the one hand, focus on leading enterprises with core technologies and stable ecological advantages in the upstream infrastructure field; on the other hand, appropriately allocate funds to early-stage innovative enterprises with potential breakthrough capabilities. At the same time, close attention should be paid to the verification of business models, changes in global regulatory policies, and geopolitical dynamics to avoid unnecessary risks. Only by grasping the core logic of industry development and balancing innovation potential and risk control can investors achieve sustainable returns in the rapidly evolving AI industry.