AI remains the most attractive frontier in the venture capital field, but the flow of funds will be more cautious.
Written by: Catalaize
Compiled by: Felix, PANews
From January to June 2025, global investment in AI startups far exceeded that of the first half of 2024. In just the first quarter of 2025, approximately $60 billion to $73 billion was attracted, surpassing half of the total amount for all of 2024, with a year-on-year growth of over 100%. In the first quarter, AI companies received about 58% of the total venture capital, while a year ago, this proportion was around 28%. This clearly indicates the investors' "AI FOMO" mentality.
This means that capital is concentrating in the AI field on an unprecedented scale, and major institutions will double down on those companies that are believed to succeed in the AI domain, which may reshape the funding allocation pattern for the second half of the year.
Huge Financing Dominated by a Few Giants
During this period, the ultra-large-scale late-stage financing rounds led by leading companies were particularly prominent. In March, OpenAI raised $40 billion (the largest private financing round in history), with a valuation reaching $300 billion, while Anthropic's $3.5 billion Series E funding increased its valuation to $61.5 billion. Several other deals, such as Safe Superintelligence's $2 billion financing and Neuralink's $650 million Series E funding, further boosted the total amount.
This means that a "winner-takes-all" situation is concentrating most of the funds in the hands of a very small number of companies, thereby crowding out the funds that could have flowed to early-stage or smaller enterprises.
Trading Volume under the Barbell Effect
In addition to the highly publicized large-scale financing, medium-sized transactions have surged, while seed round financing activities remain selective. The median for seed round financing in the AI sector has reached approximately $15 million (with an average of about $41 million), and the median for Series A financing is around $75 million to $80 million, both significantly higher than historical averages (the median for Series A financing across all industries globally in 2022 was about $10 million). The median for growth stage financing in Series C and D is concentrated between $250 million and $300 million, while the average has been skewed higher due to extreme cases like OpenAI.
This means: the expansion of trading scale reflects fierce competition among industry leaders. Investors who cannot write nine-figure checks may turn to niche markets or earlier stage investments, and any startup claiming to have AI narratives can secure larger financing and higher valuations.
Industry and Regional Concentration
Generative AI and core model/infrastructure players attracted over $45 billion in funding in the first half of the year, accounting for more than 95% of the total disclosed funding. Application-oriented AI verticals, on the other hand, 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 (particularly Silicon Valley) dominates: over 99% of 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 (Zhihub AI) raising $247 million; while Europe only saw some medium-sized funding rounds (for example, Latent Labs in the UK raised $50 million).
This means: this wave is centered around the United States, led by a few large companies; it is expected that governments and investors outside the United States will respond in the second half of the year by establishing national AI funds, providing incentives, or making cross-border investments to avoid falling behind.
Outlook for the Second Half of the Year: High Enthusiasm but Cautious Still
Despite record capital inflows, investor caution is returning. Many funding rounds in the first half of the year focused on strategic or corporate investors (cloud service providers, chip manufacturers, defense companies), indicating that investors are more inclined towards projects with practical application scenarios and strategic synergies. As we enter the second half of the year, investors will closely monitor the performance of those startups that have secured significant funding in terms of product delivery, revenue, and regulatory compliance, especially against the backdrop of increasing competition.
This means that in the second half of the year, capital may favor those companies that demonstrate efficiency and real market appeal—especially "tool and shovel" suppliers (tools, chips, enterprise software). This will raise the entry barriers for newcomers, 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 funds into the AI sector (along with its tilt towards a few participants and regions) will shape the innovation landscape and competitive dynamics for the coming years. 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 correction and a shift in focus? Data from the first half of the year provides early clues that can inform portfolio strategies, policy considerations (such as antitrust and national security issues), and the fundraising prospects for founders in the upcoming six months.
The most noteworthy funding in the AI sector over the past month
Macroeconomic and Trend Analysis
1. Financing Momentum: Soaring Year-on-Year
In the first half of 2025, venture capital investment in AI startups far exceeded the same period in 2024. Reliable data shows that about $70 billion flowed into AI companies in the first quarter alone, more than half of the total funding in the AI space for all of 2024. This means that the first half of 2025 will more than double the amount raised in the first half of 2024 (in US dollars).
In the first quarter of 2025, AI's share of global venture capital surged to approximately 53% to 58%, compared to about 25% to 30% a year earlier. This means that currently over half of the global venture capital is directed towards the AI field.
Driving factors: A few large financing rounds; 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 field; any cooling of enthusiasm in the AI sector could lower the overall funding levels.
2. Financing Stage: Late-stage financing has increased significantly, while early-stage financing varies widely
Data shows that the trading scale in the AI field follows 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 driver.
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 decreased by about 19% year-on-year), but the scale of financing has significantly increased.
In the first half of 2025, the median seed funding for AI startups was approximately $15 million; however, Lila's $200 million seed funding is considered an outlier.
The median for Series A financing is approximately 75 million to 80 million US dollars.
Key points: Investors are putting funds into fewer, larger bets - confident in specific AI themes while taking a cautious stance in other areas. This polarization is expected to continue in the second half of the year.
3 Industry Allocation: Basic Models and Infrastructure Construction
Over 95% of AI funding is chasing generative AI model developers and their infrastructure (cloud computing, chips, development platforms). Only OpenAI and Anthropic have attracted about 60% of the funding in the AI field in the first half of the year.
In contrast, vertical application fields are simply insignificant:
Healthcare / Biotechnology AI: approximately $700 million (for example, Hippocratic AI raised $141 million, Insilico raised $110 million).
Financial services and corporate productivity sectors: a total of only tens of billions of dollars.
Robotics / Defense AI: A niche area worth paying attention to (for example, Shield AI raised $240 million in funding).
Investor logic: control the "AI stack"; vertical applications may be commoditized (Note: the unique value of brands and other attributes that originally belong to commodities may disappear due to sufficient market competition) or face longer GTM cycles.
4 Geographic Distribution: Concentrated in the United States, the Bay Area accounts for half of the financing amount
In the first quarter, 71% to 73% of global venture capital flowed into North America; in terms of value, approximately 99% of funding in the AI sector is concentrated in the United States. The San Francisco Bay Area (including OpenAI) alone accounts for nearly half of the global venture capital.
Europe, the Middle East, and Africa: Only a few medium-sized AI transactions (Latent Labs raised $50 million, Speedata raised $44 million).
Asia-Pacific: In the first quarter of 2025, only $1.8 billion was raised for AI (a year-on-year decrease of 50%); the largest round of financing in China was $247 million obtained by Zhipu AI.
In summary: The United States has an advantage in funding投入 in this "AI arms race."
5 Investor Landscape:
Sovereign wealth funds and cross-border funds (Saudi Arabia's Prosperity7, Malaysia's Khazanah, Thrive Capital) led multiple rounds of financing.
The corporate venture capital departments of large tech companies (Microsoft, Salesforce, Google) are very active.
Net effect: Capital influx from all parties.
Outlook for the Second Half of the Year:
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 emerge. In the US, any movement from the administration regarding AI, as well as Congress—hearings, proposed legislation—will be crucial. New regulations surrounding data usage, model transparency, or chip export controls could reshape the economic landscape for 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 drive away startups and investors.
In addition, attention should be paid to the AI procurement situation of the U.S. government—rumors about a multi-billion dollar plan may provide important demand signals for AI companies focused on enterprises.
IPO channels and exit routes
Despite the surge in private financing in 2025, there have yet to be any groundbreaking AI IPOs. This situation may change in the second half of the year. Companies like Databricks, Stripe (AI-related), and even OpenAI could be potential IPO candidates.
A successful initial public offering (IPO) can reprice the market, release liquidity in 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, merger and acquisition activities may escalate. Large tech companies may take action: Google, Microsoft, or Nvidia may acquire smaller AI teams or core infrastructure providers. A significant AI acquisition could reshape the competitive landscape and bring returns to venture capital firms.
Technological Breakthroughs and Product Releases
Looking forward to the disclosure of significant news: it could be OpenAI's next-generation model, or hardware launched in collaboration by Sam Altman and Jony Ive.
Any significant breakthroughs in capability (for example, a model capable of reasoning or a model that reduces costs by a factor of 10) could validate overestimations and trigger a new wave of capital.
Also pay attention to enterprise-level attractiveness - API sales, SaaS adoption, and revenue situation. However, risks also exist; once a security incident or public misuse occurs, it may provoke strong opposition from regulators, thereby dampening market sentiment.
In summary, the technical and business performance in the second half of the year will determine whether the optimism from 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: such as the implementation of a licensing system, imposing fines under the General Data Protection Regulation (GDPR), or imposing strict restrictions on certain models.
Moral resistance: Scandals, mass layoffs caused by automation, or AI-generated misinformation can quickly change market sentiment, making it more difficult to deploy capital.
Calculation and Talent Constraints
The lifeblood of AI—graphics processing units (GPUs) and elite engineers—remains scarce.
GPU bottlenecks may force underfunded teams to exit, while well-funded companies hoard computing resources.
The competition for talent is intensifying, with OpenAI and Google both vying for top talent.
The burn rate is skyrocketing: some startups are spending over $100 million a year on cloud services without being able to quickly launch products. If the gap between costs and products continues to widen, a funding discount and a brutal market reset are expected.
Model commercialization
Ironically, the competition among large language models (LLMs) is driving rapid commodification. Open source releases (such as Meta's LLaMA, Mistral, etc.) blur the distinctions.
The moat is shifting towards data quality, distribution channels, or vertical integration.
If OpenAI starts to lose to streamlined open-source participants or models developed in-house by companies, venture capitalists may reassess the true meaning of "defensibility."
The second half of the year may sound the alarm: not every carefully calibrated wrapper is worth a valuation of 1 billion dollars.
Forecast for the Second Half of 2025
The scale of financing has slowed down but remains at a high level.
After the frenzy in the first half of the year, the trading pace will slow down. It is expected that there will not be another round of financing of 40 billion dollars, but the quarterly AI financing amount will still be double that of the 2024 level. The boom continues, just in a more stable manner.
A major liquidity event is coming.
At least one exit of over ten billion dollars is expected: an IPO (for example, Databricks) or acquisition by a traditional company trying to maintain influence.
This will affect investor sentiment and reset pricing expectations.
A clear layering of the startup ecosystem will become apparent by the fourth quarter, with differentiation being evident:
The top 5-10 AI companies (with strong funding and development momentum) will gradually exit and may recruit talent through acquisitions.
What about those startups that are in the mid-tier or are overly hyped but have yet to achieve product-market fit? Many will transform, experience valuation adjustments, or gradually disappear.
Investors will reward the execution ability that can generate income, rather than just the research plans or investment in GPUs.
Final Conclusion
The next six months will put AI narratives to the test. Will 2025 mark the beginning of ongoing transformation, or is it a bubble that needs correction?
Some bubbles will burst, but the core argument still holds. AI remains the most attractive frontier in venture capital, but the flow of funds will be more cautious.
View Original
The content is for reference only, not a solicitation or offer. No investment, tax, or legal advice provided. See Disclaimer for more risks disclosure.
Overview of AI Investment in the First Half of 2025: 58% of Global Venture Capital Funds Flow to AI
Written by: Catalaize
Compiled by: Felix, PANews
From January to June 2025, global investment in AI startups far exceeded that of the first half of 2024. In just the first quarter of 2025, approximately $60 billion to $73 billion was attracted, surpassing half of the total amount for all of 2024, with a year-on-year growth of over 100%. In the first quarter, AI companies received about 58% of the total venture capital, while a year ago, this proportion was around 28%. This clearly indicates the investors' "AI FOMO" mentality.
This means that capital is concentrating in the AI field on an unprecedented scale, and major institutions will double down on those companies that are believed to succeed in the AI domain, which may reshape the funding allocation pattern for the second half of the year.
Huge Financing Dominated by a Few Giants
During this period, the ultra-large-scale late-stage financing rounds led by leading companies were particularly prominent. In March, OpenAI raised $40 billion (the largest private financing round in history), with a valuation reaching $300 billion, while Anthropic's $3.5 billion Series E funding increased its valuation to $61.5 billion. Several other deals, such as Safe Superintelligence's $2 billion financing and Neuralink's $650 million Series E funding, further boosted the total amount.
This means that a "winner-takes-all" situation is concentrating most of the funds in the hands of a very small number of companies, thereby crowding out the funds that could have flowed to early-stage or smaller enterprises.
Trading Volume under the Barbell Effect
In addition to the highly publicized large-scale financing, medium-sized transactions have surged, while seed round financing activities remain selective. The median for seed round financing in the AI sector has reached approximately $15 million (with an average of about $41 million), and the median for Series A financing is around $75 million to $80 million, both significantly higher than historical averages (the median for Series A financing across all industries globally in 2022 was about $10 million). The median for growth stage financing in Series C and D is concentrated between $250 million and $300 million, while the average has been skewed higher due to extreme cases like OpenAI.
This means: the expansion of trading scale reflects fierce competition among industry leaders. Investors who cannot write nine-figure checks may turn to niche markets or earlier stage investments, and any startup claiming to have AI narratives can secure larger financing and higher valuations.
Industry and Regional Concentration
Generative AI and core model/infrastructure players attracted over $45 billion in funding in the first half of the year, accounting for more than 95% of the total disclosed funding. Application-oriented AI verticals, on the other hand, 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 (particularly Silicon Valley) dominates: over 99% of 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 (Zhihub AI) raising $247 million; while Europe only saw some medium-sized funding rounds (for example, Latent Labs in the UK raised $50 million).
This means: this wave is centered around the United States, led by a few large companies; it is expected that governments and investors outside the United States will respond in the second half of the year by establishing national AI funds, providing incentives, or making cross-border investments to avoid falling behind.
Outlook for the Second Half of the Year: High Enthusiasm but Cautious Still
Despite record capital inflows, investor caution is returning. Many funding rounds in the first half of the year focused on strategic or corporate investors (cloud service providers, chip manufacturers, defense companies), indicating that investors are more inclined towards projects with practical application scenarios and strategic synergies. As we enter the second half of the year, investors will closely monitor the performance of those startups that have secured significant funding in terms of product delivery, revenue, and regulatory compliance, especially against the backdrop of increasing competition.
This means that in the second half of the year, capital may favor those companies that demonstrate efficiency and real market appeal—especially "tool and shovel" suppliers (tools, chips, enterprise software). This will raise the entry barriers for newcomers, 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 funds into the AI sector (along with its tilt towards a few participants and regions) will shape the innovation landscape and competitive dynamics for the coming years. 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 correction and a shift in focus? Data from the first half of the year provides early clues that can inform portfolio strategies, policy considerations (such as antitrust and national security issues), and the fundraising prospects for founders in the upcoming six months.
The most noteworthy funding in the AI sector over the past month
Macroeconomic and Trend Analysis
1. Financing Momentum: Soaring Year-on-Year
In the first half of 2025, venture capital investment in AI startups far exceeded the same period in 2024. Reliable data shows that about $70 billion flowed into AI companies in the first quarter alone, more than half of the total funding in the AI space for all of 2024. This means that the first half of 2025 will more than double the amount raised in the first half of 2024 (in US dollars).
In the first quarter of 2025, AI's share of global venture capital surged to approximately 53% to 58%, compared to about 25% to 30% a year earlier. This means that currently over half of the global venture capital is directed towards the AI field.
Driving factors: A few large financing rounds; 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 field; any cooling of enthusiasm in the AI sector could lower the overall funding levels.
2. Financing Stage: Late-stage financing has increased significantly, while early-stage financing varies widely
Data shows that the trading scale in the AI field follows 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 driver.
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 decreased by about 19% year-on-year), but the scale of financing has significantly increased.
In the first half of 2025, the median seed funding for AI startups was approximately $15 million; however, Lila's $200 million seed funding is considered an outlier.
The median for Series A financing is approximately 75 million to 80 million US dollars.
Key points: Investors are putting funds into fewer, larger bets - confident in specific AI themes while taking a cautious stance in other areas. This polarization is expected to continue in the second half of the year.
3 Industry Allocation: Basic Models and Infrastructure Construction
Over 95% of AI funding is chasing generative AI model developers and their infrastructure (cloud computing, chips, development platforms). Only OpenAI and Anthropic have attracted about 60% of the funding in the AI field in the first half of the year.
In contrast, vertical application fields are simply insignificant:
Investor logic: control the "AI stack"; vertical applications may be commoditized (Note: the unique value of brands and other attributes that originally belong to commodities may disappear due to sufficient market competition) or face longer GTM cycles.
4 Geographic Distribution: Concentrated in the United States, the Bay Area accounts for half of the financing amount
In the first quarter, 71% to 73% of global venture capital flowed into North America; in terms of value, approximately 99% of funding in the AI sector is concentrated in the United States. The San Francisco Bay Area (including OpenAI) alone accounts for nearly half of the global venture capital.
Europe, the Middle East, and Africa: Only a few medium-sized AI transactions (Latent Labs raised $50 million, Speedata raised $44 million).
Asia-Pacific: In the first quarter of 2025, only $1.8 billion was raised for AI (a year-on-year decrease of 50%); the largest round of financing in China was $247 million obtained by Zhipu AI.
In summary: The United States has an advantage in funding投入 in this "AI arms race."
5 Investor Landscape:
Sovereign wealth funds and cross-border funds (Saudi Arabia's Prosperity7, Malaysia's Khazanah, Thrive Capital) led multiple rounds of financing.
The corporate venture capital departments of large tech companies (Microsoft, Salesforce, Google) are very active.
Net effect: Capital influx from all parties.
Outlook for the Second Half of the Year:
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 emerge. In the US, any movement from the administration regarding AI, as well as Congress—hearings, proposed legislation—will be crucial. New regulations surrounding data usage, model transparency, or chip export controls could reshape the economic landscape for 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 drive away startups and investors.
In addition, attention should be paid to the AI procurement situation of the U.S. government—rumors about a multi-billion dollar plan may provide important demand signals for AI companies focused on enterprises.
IPO channels and exit routes
Despite the surge in private financing in 2025, there have yet to be any groundbreaking AI IPOs. This situation may change in the second half of the year. Companies like Databricks, Stripe (AI-related), and even OpenAI could be potential IPO candidates.
A successful initial public offering (IPO) can reprice the market, release liquidity in 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, merger and acquisition activities may escalate. Large tech companies may take action: Google, Microsoft, or Nvidia may acquire smaller AI teams or core infrastructure providers. A significant AI acquisition could reshape the competitive landscape and bring returns to venture capital firms.
Technological Breakthroughs and Product Releases
Looking forward to the disclosure of significant news: it could be OpenAI's next-generation model, or hardware launched in collaboration by Sam Altman and Jony Ive.
Any significant breakthroughs in capability (for example, a model capable of reasoning or a model that reduces costs by a factor of 10) could validate overestimations and trigger a new wave of capital.
Also pay attention to enterprise-level attractiveness - API sales, SaaS adoption, and revenue situation. However, risks also exist; once a security incident or public misuse occurs, it may provoke strong opposition from regulators, thereby dampening market sentiment.
In summary, the technical and business performance in the second half of the year will determine whether the optimism from 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: such as the implementation of a licensing system, imposing fines under the General Data Protection Regulation (GDPR), or imposing strict restrictions on certain models.
Moral resistance: Scandals, mass layoffs caused by automation, or AI-generated misinformation can quickly change market sentiment, making it more difficult to deploy capital.
Calculation and Talent Constraints
The lifeblood of AI—graphics processing units (GPUs) and elite engineers—remains scarce.
GPU bottlenecks may force underfunded teams to exit, while well-funded companies hoard computing resources.
The competition for talent is intensifying, with OpenAI and Google both vying for top talent.
The burn rate is skyrocketing: some startups are spending over $100 million a year on cloud services without being able to quickly launch products. If the gap between costs and products continues to widen, a funding discount and a brutal market reset are expected.
Model commercialization
Ironically, the competition among large language models (LLMs) is driving rapid commodification. Open source releases (such as Meta's LLaMA, Mistral, etc.) blur the distinctions.
The moat is shifting towards data quality, distribution channels, or vertical integration.
If OpenAI starts to lose to streamlined open-source participants or models developed in-house by companies, venture capitalists may reassess the true meaning of "defensibility."
The second half of the year may sound the alarm: not every carefully calibrated wrapper is worth a valuation of 1 billion dollars.
Forecast for the Second Half of 2025
The scale of financing has slowed down but remains at a high level.
After the frenzy in the first half of the year, the trading pace will slow down. It is expected that there will not be another round of financing of 40 billion dollars, but the quarterly AI financing amount will still be double that of the 2024 level. The boom continues, just in a more stable manner.
A major liquidity event is coming.
At least one exit of over ten billion dollars is expected: an IPO (for example, Databricks) or acquisition by a traditional company trying to maintain influence.
This will affect investor sentiment and reset pricing expectations.
A clear layering of the startup ecosystem will become apparent by the fourth quarter, with differentiation being evident:
Final Conclusion
The next six months will put AI narratives to the test. Will 2025 mark the beginning of ongoing transformation, or is it a bubble that needs correction?
Some bubbles will burst, but the core argument still holds. AI remains the most attractive frontier in venture capital, but the flow of funds will be more cautious.