The AI investment boom continues, with a large influx of venture capital in the first half of 2025.

In the first half of 2025, global AI startup financing reached a new high, far exceeding the levels of the same period in 2024. Data shows that in just the first quarter, the AI sector attracted about $60-73 billion in investments, already surpassing half of the total for the entire year of 2024, with a year-on-year growth of over 100%. Venture capital received by AI companies accounted for about 58% of the total, a significant increase from around 28% a year ago. This fully reflects investors' enthusiasm for AI.

Capital is concentrating on the AI field at an unprecedented scale, with major institutions increasing their bets on potential winners in the AI sector, which could reshape the funding allocation landscape for the second half of the year.

Large-scale financing dominated by giants

During this period, the super-large-scale late-stage financing rounds, led by leading companies, were particularly prominent. In March, an AI company raised $40 billion, setting a record for the largest private financing in history, with a valuation of $300 billion. Another AI company's $3.5 billion Series E financing brought its valuation to $61.5 billion. Several other substantial deals, such as a company's $2 billion financing and another company's $650 million Series E financing, further boosted the total amount.

This "winner takes all" situation is concentrating most of the funds in the hands of a very small number of companies, thereby squeezing out the funding that could have flowed to early-stage or smaller companies.

Financing scale shows polarization

In addition to the highly publicized large financings, the number of medium-sized transactions has surged, while seed round financing activities remain selective. The median for seed round financing in the AI sector has reached about $15 million (with an average of about $41 million), and the median for Series A financing is approximately $75 million to $80 million, both significantly higher than historical averages (with the global median for Series A financing across all industries in 2022 being around $10 million). The median for growth stage financing in Series C and D is concentrated between $250 million and $300 million, while the average is skewed upwards due to a few extreme cases.

The expansion of trading volume reflects fierce competition among leading companies in the industry. Investors unable to write nine-figure checks may turn to niche areas or earlier-stage investments, while any startup claiming to have AI narratives can secure larger-scale financing and higher valuations.

Industry and regional distribution is highly concentrated

Generative AI and core models/infrastructure attracted over $45 billion in funding in the first half of the year, accounting for more than 95% of the total disclosed funding. In contrast, applied AI verticals are relatively underfunded (approximately $700 million in the healthcare/biotechnology sector; about $2 to $3 billion in the fintech/corporate sector). Geographically, the United States (especially Silicon Valley) dominates: over 99% of the global AI funding in the first half of the year flowed to companies headquartered in the U.S. Asia and Europe lag behind, with China's largest deal financing $247 million; while Europe saw only a few medium-sized funding rounds (for example, a company in the UK raised $50 million).

This wave is centered around the United States, led by a few large companies; it is expected that governments and investors outside of the U.S. will respond in the second half of the year by establishing national AI funds, providing incentives, or engaging in cross-border investments to avoid falling behind.

Outlook for the Second Half of the Year: Enthusiasm High but Caution Remains

Despite record capital investment, investor caution is returning. Many funding rounds in the first half of the year have focused on strategic or corporate investors (cloud service providers, chip manufacturers, defense companies), indicating that investors prefer projects with practical application scenarios and strategic synergies. As we enter the second half of the year, investors will closely monitor the performance of startups that have received large amounts of funding in terms of product delivery, revenue, and regulatory compliance, especially in the context of increasing competition.

In the second half of the year, capital may favor those companies that demonstrate efficiency and real market appeal—especially "tools and shovel" suppliers (tools, chips, enterprise software), which will raise the entry barrier for new entrants, consolidate the advantages of existing companies, and pose challenges to new entrants.

Importance

The first half of 2025 is a critical moment for AI investment. The large influx of capital into the AI field (and its tilt towards a few participants and regions) will shape the innovation landscape and competitive dynamics for the years to come. For investors, understanding the flow of funds and the reasons behind it is crucial for navigating the second half of 2025. Will the winners be able to prove their valuations are justified, or will there be a pullback and a refocus? The data from the first half of the year provides early clues, offering insights for portfolio strategies, policy considerations, and the fundraising prospects for founders in the coming six months.

Macroeconomic and Trend Analysis

1. Financing Momentum: Soaring Compared to Previous Year

In the first half of 2025, venture capital investment in AI startups far exceeded the levels of the same period in 2024. Reliable data shows that approximately $70 billion flowed into AI companies in just the first quarter, surpassing half of the total financing in the AI sector for the entire year of 2024. This means that financing in the first half of 2025 reached more than double that of the first half of 2024 (in USD).

In the first quarter of 2025, the share of AI in global venture capital jumped to about 53% to 58%, compared to around 25% to 30% a year ago. This means that currently, over half of the global venture capital is directed towards the AI sector.

Driving factors: A few large financing deals; without these, global venture capital funding is roughly flat year-on-year.

Impact on the second half of 2025: Overall venture capital indicators may depend on the trading volume in the AI sector; any cooling of enthusiasm in the AI field could lower the overall financing levels.

2. Financing Stage: Significant growth in later-stage financing, early-stage financing varies significantly.

Data shows that the trading scale in the AI field exhibits a barbell distribution.

Late-stage (C+ round) dominates: In the first quarter of 2025, the total amount of late-stage financing across all industries reached $81 billion, a year-on-year increase of approximately 147%, with AI being the main driving force.

• The average size of Series D and E financing is approximately $300 million to $950 million (with a median of about $250 million to $450 million).

Early stage: The number of transactions has decreased (global early stage transactions have decreased by about 19% year-on-year), but the scale of financing has increased significantly.

• The median seed round financing for AI startups in the first half of 2025 is approximately $15 million; however, a certain company's $200 million seed financing is considered an outlier.
• The median of Series A financing is approximately 75 million to 80 million US dollars.

Key points: Investors are putting funds into fewer, larger stakes — confident in specific AI themes while being cautious in other areas. This polarization is expected to continue in the second half of the year.

3. Industry Allocation: Basic Models and Infrastructure Development

About 95% of AI funding is chasing generative AI model developers and their infrastructure (cloud computing, chips, development platforms). Only two leading companies have absorbed about 60% of the funding in the AI sector in the first half of the year.

In contrast, vertical application fields are insignificant:

• Healthcare/Biotechnology AI: Approximately $700 million (for example, one company raised $141 million, while another company raised $110 million).
• Financial services and corporate productivity sector: totaling only several billion dollars.
• Robotics/Defense AI: A niche field but worth paying attention to (for example, a certain company raised $240 million in funding).

Investor logic: control the "AI stack"; vertical applications may become commoditized or face longer GTM cycles.

4. Regional Distribution: Concentrated in the United States, with the Bay Area accounting for half of the financing amount.

71% to 73% of global venture capital in the first quarter flowed to North America; in terms of value, about 99% of funding in the AI sector is concentrated in the United States. The San Francisco Bay Area alone accounts for nearly half of global venture capital.

Europe, the Middle East, and Africa: Only a few medium-sized AI transactions (one company raised $50 million, another company raised $44 million).

Asia-Pacific: Only $1.8 billion was raised for AI in Q1 2025 (a year-on-year decrease of 50%); China's largest round of financing was $247 million obtained by a certain company.

In summary: The United States has an advantage in funding in this "AI arms race."

5. Investor Landscape:

Sovereign wealth funds and cross-border funds led multiple rounds of financing.

The corporate venture capital divisions of large technology companies are very active.

Net effect: Capital influx from all parties.

Mid-Year Forward-Looking Outlook:

Regulatory Milestone

Governments around the world are still exploring how to respond to AI. In the EU, the AI Act is expected to be finalized by the end of 2025. In the second half of the year, startups are likely to engage in a lobbying battle, and early compliance signals may also emerge. In the US, any movement regarding AI administrative orders and Congress—such as hearings and proposed legislation—will be crucial. New regulations around data usage, model transparency, or chip export controls could reshape the economic situation of startups and investor confidence.

• Positive expectations: Clearer and more business-friendly guidelines legalize the application of AI across various industries.
• Negative expectations: Strict regulations (for example, accountability for AI errors) may scare away startups and investors.

In addition, attention should also be paid to the AI procurement situation of the US government - rumors about a multi-billion dollar plan may provide important demand signals for AI companies focused on enterprises.

IPO Channels and Exit Strategies

Despite the surge in private financing in 2025, there have not yet been any groundbreaking AI IPOs. This situation may change in the second half of the year. Some large AI-related companies could be potential IPO candidates.

• A successful initial public offering (IPO) may reprice the market, release liquidity for later stages, and provide comparable data.
• The ongoing IPO stagnation may shake investors' confidence in the exit timeline for AI startups.

At the same time, M&A activity may escalate. Large tech companies may take action: some leading firms may acquire smaller AI teams or core infrastructure providers. A significant AI acquisition could reshape the competitive landscape and yield returns for venture capital firms.

Technological Breakthroughs and Product Releases

Looking forward to the disclosure of significant news: it could be the next-generation model of a certain company or hardware launched in collaboration with a well-known figure.

Any significant breakthrough in capability (e.g., a model that can reason or a model that reduces costs by 10 times) could validate the overvaluation and trigger a new wave of capital.

We should also pay attention to enterprise-level attractiveness - API sales, SaaS adoption, and revenue situation. However, there are risks; if a security incident or public abuse occurs, it may provoke strong regulatory opposition, thereby dampening market sentiment.

In summary, the technical and business execution in the second half of the year will determine whether the optimism of the first half can be sustained.

Regulatory and Ethical Resistance

If the government or the public feels that AI has gone out of control, it is expected that intervention measures will be implemented quickly: for example, introducing a licensing system, imposing fines based on the General Data Protection Regulation (GDPR), or imposing strict restrictions on certain models.

Moral resistance: Scandals, mass layoffs due to automation, or AI-generated misinformation can quickly change market sentiment, making it harder for funds to be invested.

Calculation and Talent Limitations

The lifeline of AI—graphics processing units (GPUs) and elite engineers—remains scarce.

GPU bottlenecks may force underfunded teams to withdraw, while well-funded companies will hoard computing resources.

The talent war is escalating, with leading companies scrambling to recruit top talent.

The rate of burning money is skyrocketing: some startups spend on cloud services every year.