State of the Venture Market: 2024 AI Review
and 2025 Outlook (with key takeaways at the end)
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This week, we will explore the global AI venture landscape of 2024, combining several disparate data sources but relying heavily on the recently released PitchBook-NVCA Venture Monitor First Look.
This week’s edition is a great read paired with last week’s 2025 Predictions for AI.
Let’s Dive Into It
AI Had a Comeback Year
The venture capital landscape in 2024 is defined above all by artificial intelligence (AI). While overall global startup investments rose modestly and deal counts fell, the attention of investors, corporates, and governments has increasingly gravitated toward AI as the most promising and transformative technology of our time. As we look ahead to 2025, understanding how AI shapes capital flows, fund formation, and strategic decision-making is crucial for anyone wanting to thrive in this evolving environment.
Although the 2024 venture market remains well below its 2021 peak, AI’s expansive potential has proven an enduring magnet for capital even by 2021 standards. From foundation models attracting mega-rounds of hundreds of millions of dollars to smaller niche funds with specialized AI theses, the ecosystem has reorganized itself around AI’s groundbreaking capabilities in data processing, analytics, automation, and decision support. This year underscores that while the venture market overall is stabilizing, AI is powering much of its growth. Investors may be more cautious when writing big checks but still appear eager to back companies demonstrating true AI innovation.
Looking at the overall market and the AI market compared to its peak in 2021, we are starting to see a move to a comeback overall. In AI, we are approaching the 2021 numbers on almost every front and, in the case of the share of the total venture market, exceed them in deal numbers by a small margin and nearly double the deal value in 2024 compared to the peak in 2021. Even with the billion-dollar-plus deals removed, the significant margin between the 2021 peak and 2024 still holds.
A prominent theme of 2024 was the concentration of capital. Large corporates, mega-funds, and sovereign wealth initiatives have funneled billions into AI ventures, particularly in foundation models—often the bedrock for deploying generative AI and advanced analytics across multiple industries. Meanwhile, smaller VC firms and emerging managers specializing in AI find pockets of opportunity below the radar of the biggest players. This bifurcation has changed the makeup of the venture market and redefined what it means to be “AI-first,” with both hype-driven and genuinely innovative companies vying for finite investment dollars.
2024 AI Funding Landscape
Global venture capital investments reached $368.5 billion in 2024, a 5.4% increase over the previous year’s $349.4 billion. Yet deal counts dropped by about 17%, from 43,320 to 35,686. The disparity highlights a shift toward fewer, more significant AI-driven deals alongside selective mega-rounds for companies with established traction. While the venture market is roughly 50.9% below its 2021 peak of $751.5 billion, AI has emerged as the linchpin of its modest resurgence.
Central to this year’s story is the sheer scale of AI investments. AI deals represented 35.7% of total venture capital value in 2024, up dramatically from 24.7% in 2023. In absolute terms, AI funding climbed to $131.5 billion—an astonishing 52% jump from the $86.3 billion recorded the year prior. This escalation is not simply a function of hype. It reflects substantive advancements in large language models, computer vision, and automation and the expansion of AI beyond core tech verticals into sectors like healthcare, finance, real estate, credit, and even secondary markets. We saw this same trend reflected in deal value in every region globally. Interestingly, even for AI, the deal count was down significantly in every region except North America.
Map View: 2024 Total AI Deal Count by Region, Map: YoY % Increase in AI Deal Value By Region
Map View: 2024 Total AI Deal Value By Region, Map: YoY Change AI’s Share of Total Deals
Despite questions about a potential AI bubble, many investors argue that AI is not a short-lived craze but rather a fundamental shift comparable to the early internet. AI-first business models often promise rapid scalability, relatively high margins, and the potential to disrupt entrenched incumbents. Corporate venture arms have piled in, seeing direct synergies with their R&D initiatives. For instance, enterprise software giants want to harness AI to automate internal processes; automotive firms hope AI can accelerate self-driving capabilities; and healthcare conglomerates foresee AI-based diagnostics revolutionizing patient care. This confluence of corporate buy-in, traditional VC enthusiasm, and government funding from sovereign wealth funds has propelled AI to the forefront of 2024’s venture landscape.
Yet, there is a cautionary undertone. The term “AI washing” has surfaced to describe startups branding themselves as AI-driven without substantial intellectual property or technical depth. Investors previously relaxed about due diligence in AI but now demand more explicit proof of proprietary technology and genuine market fit. This is where having GPs with deep AI domain expertise is extremely valuable. Consequently, while AI’s growth trajectory looks strong, investors increasingly discriminate when deciding which AI companies merit premium valuations.
Foundation Models and Beyond
The large-scale, foundation-model ventures are at the highest end of the AI market. These companies build advanced generative AI systems with billions of parameters. OpenAI, Anthropic, and xAI collectively raised billions of dollars in 2024 alone, often in mega-rounds backed by traditional VC funds and strategic corporate investors. These foundation models serve as a platform layer for downstream applications, from language translation to drug discovery, translating into enormous commercial potential. However, today's market dominance does not guarantee their place at the top tomorrow, as we have seen in the past with technological transformations such as Web 1.0. some of the early winners were the first losers. One of them will lose their dominance in the next two years. In 2024, 11 (eleven) AI deals were one billion dollars or greater in single-round funding.
Corporate partnerships are essential in this space. Tech giants leverage their cloud infrastructure to support AI workloads at scale, while corporate venture arms inject capital to integrate AI solutions into their product suites. This synergy boosts valuations and drives the narrative that AI is indispensable to every large organization’s future. Meanwhile, specialized funds focused on niche AI applications—like generative design, robotics, or advanced analytics—can carve out unique advantages, identifying under-the-radar startups that could eventually become the next wave of unicorns.
Emerging Managers and the AI Advantage
Much of the year’s excitement stems from the fact that AI has so many specialized subfields—computer vision, natural language processing, reinforcement learning, and more—that it allows smaller, domain-expert GPs (general partners) to establish defensible positions. While large, generalist funds typically spread capital across numerous industries, a niche AI-focused fund can develop a deep network of researchers, engineers, and subject-matter experts. This specialization often leads to differentiated deal flow and robust due diligence, enabling these emerging managers to spot nascent AI trends before they hit the mainstream.
However, the fundraising environment remains challenging. The total number of VC funds that closed in 2024 dropped to 1,344 from 2,333 in 2023 and from its peak of 4,283 funds closing in 2021. Despite the intense interest in AI, many LPs still prefer the perceived safety of established brand-name managers with a track record of success. As a result, only 8% of LPs said they planned to invest in more first-time managers, and 43% had explicit “no-first-time manager” rules. Even with AI expertise as a selling point, emerging GPs must often offer concessions—like lower fees or carried interest—and demonstrate a clear plan for delivering tangible value.
Yet the upside can be significant for LPs willing to back new, AI-savvy GPs. Not only do these managers bring specialized knowledge, but they also operate with less overhead than large, multi-strategy funds. They can execute fast-moving deals at earlier stages, uncover overlooked talent, and support founders more intimately. Building strong domain coverage is a compelling differentiator in hypercompetitive subfields of AI, and LPs are increasingly aware that waiting on brand-name funds might mean missing out on future category-defining technologies.
AI’s Global Footprint
While North America remains the leading hub for AI innovation—due mainly to its mature venture ecosystem, talent pool, and corporate headquarters—other regions are also investing heavily in AI capabilities. Europe allocated an estimated €55.6 billion to startups in 2024 across 8,760 rounds, and a growing portion of that capital flows into AI. Names like Mistral AI in France and Poolside in the UK are raising big rounds. Europe’s largest single deal of 2024—a one-billion-pound investment in a sustainable data center platform—also contains strong AI components for energy efficiency and resource optimization.
Asia, especially China, has seen slowed venture activity due to macroeconomic pressures and geopolitical tensions. Nonetheless, AI remains a high priority, with Chinese tech giants and funds investing heavily in generative AI, robotics, and autonomous systems. Meanwhile, countries across the Middle East and Asia are quickly catching up by leveraging their sovereign wealth funds and public investment vehicles. Saudi Arabia’s Public Investment Fund (PIF) and Abu Dhabi’s Mubadala have placed significant bets on advanced AI startups. Kuwait’s Investment Authority (KIA) and Oman’s Technology Fund are ramping up local and foreign AI venture investments. Singapore’s sovereign wealth funds, GIC and Temasek, continue to expand their AI portfolios, reinforcing the city-state’s position as a significant innovation hub in Asia. At the same time, in Africa, the African Development Bank and various government-led initiatives fuel AI-related innovation in key tech centers like Lagos, Nairobi, and Cairo.
The result is a more globally distributed AI market than in previous years. While Silicon Valley still leads cutting-edge research, companies worldwide can tap into specialized AI talent, generous government grants, and rapidly growing startup ecosystems. Globalization also leads to cross-border partnerships, especially in complex areas like supply chain AI or climate-focused analytics, where multinational collaboration can accelerate R&D and market adoption.
Sectoral Intersections: Biotech, Climate, and More
Although “AI-first” has become the rallying cry for many investors, the technology is not an island unto itself. AI is permeating nearly every vertical, from drug discovery in biotech to carbon capture in climate tech. Venture capitalists increasingly favor AI-infused businesses that demonstrate more efficient operations, faster time-to-market, and data-driven decision-making.
Biotech stands out as one of AI's biggest beneficiaries. Rapid developments in computational biology, combined with large-scale data from genomic sequencing, allow AI-driven drug discovery pipelines to iterate at an accelerated pace. Startups that couple proprietary data sets with advanced machine learning tools are raising rounds in the hundreds of millions, betting that algorithmic breakthroughs can slash R&D timelines and cut costs for new therapeutics.
Climate tech is another arena in which AI is profoundly impacting investors. Predictive analytics for resource management, sensor-based automation in agriculture, and AI-driven optimization of renewable energy grids fuel investor excitement. Many climate-oriented funds now emphasize AI as a core part of their theses, seeking synergy between environmental impact and technical sophistication. This cross-pollination underscores that far from displacing other industries, AI often acts as a force multiplier, enhancing capabilities in existing sectors.
Corporate Venture Capital and AI
Corporate venture capital (CVC) has become a key driver of AI adoption, with 93% of CEOs reporting plans to increase or maintain their CVC activities in 2024. From financial services giants exploring algorithmic trading and fraud detection to logistics firms automating supply chains, corporations see direct applications that can yield cost savings and new lines of business. In many cases, these corporations also hope to secure an early foothold in technologies that could disrupt them. Investing in AI startups becomes a strategic hedge, allowing corporations to pivot faster than relying solely on internal R&D.
This CVC presence can have ripple effects throughout the ecosystem. CVC-backed AI startups often gain access to pilot programs, distribution channels, and real-world datasets within the sponsor corporations. That real-world validation can decide on follow-on funding rounds from traditional VCs. Corporations, in turn, may offer rapid acquisition paths or large-scale licensing agreements, further raising valuations for AI startups that prove their efficacy in commercial settings.
The Fundraising Environment in an AI-Centric Market
Despite the enthusiasm for AI, the broader fundraising environment remains selective. Total capital raised by new VC funds in 2024 fell to $169.7 billion, down from $213.8 billion in 2023. This indicates growing caution among limited partners who may be excited about AI but wary of overcommitting in uncertain economic conditions. Nevertheless, established AI-focused funds often fare better, leveraging strong track records and high-profile exits to secure commitments.
Emerging AI managers who lack brand-name pedigree face significant hurdles. They must persuade LPs that their domain expertise and networks give them a better shot at accessing the next cohort of breakthrough AI startups. Concessions on fees or acceptance of smaller fund sizes can sometimes entice reluctant LPs. However, these concessions can limit a fund’s operational flexibility, making it harder to attract top analysts, data scientists, and venture partners crucial for evaluating AI startups. The result is a precarious balance: domain-expert GPs know to execute but must navigate an LP community that remains risk-averse and often defaults to bigger, more established funds.
2025 Outlook: Maturing AI Markets and Stricter Criteria
Many analysts foresee a more buoyant exit environment in 2025. The IPO market, largely dormant in 2023–2024, could reopen, especially for high-performing AI companies that meet public market demands for revenue growth and scalability. Strategic mergers and acquisitions may also accelerate as corporations with considerable cash reserves look to acquire AI capabilities rather than build them from scratch. Such exits, if successful, can recycle capital back into early-stage AI ventures and reaffirm investor confidence.
At the same time, the mania surrounding AI may give way to more exacting standards. Investors will dig deeper into whether an AI startup has a moat: robust technology and/or unique data with product market fit as demonstrated by solid design partners or a proven customer pipeline. If some inflated AI valuations fail to deliver, valuations could be rationalized. This shift favors startups that demonstrate near-term ROI and real-world use cases. The threshold for going public could become more stringent, but once met, IPOs of AI companies may attract significant fanfare.
With AI increasingly viewed as indispensable, non-AI sectors risk being overshadowed unless they incorporate AI-driven strategies. Climate tech, biotech, and enterprise software will continue to flourish precisely because they now integrate advanced machine learning as a core differentiator. The lines between “AI sector” and “other sectors” grow blurrier daily. Investors in 2025 will likely move from asking, “Are you building something in AI?” to “How does your AI solution concretely impact your market, and what unique data or skill sets do you bring to the table?”
Global Government-Backed AI Investments
One of the most significant developments for AI’s future is the rise of government-backed capital in the Middle East, Singapore, and Africa. Sovereign wealth funds in Saudi Arabia, the UAE, Kuwait, Qatar, and Oman have deployed billions in AI ventures abroad and local ecosystems. These massive injections of patient capital can shore up startups against market volatility and accelerate the development of AI clusters in emerging tech hubs.
Through its sovereign wealth funds GIC and Temasek, Singapore has become a hotbed of AI deployment across fintech, logistics, and healthcare. Meanwhile, in parts of Africa, government-linked agencies and pan-continental organizations like the African Development Bank support AI startups tackling problems in finance, agriculture, and infrastructure. These global funding flows underscore that AI is not just a Silicon Valley phenomenon; it is increasingly ubiquitous, shaping how governments diversify their economies and modernize public services.
Such initiatives often have unique policy goals, from fostering domestic talent pools to spreading knowledge. While they can provide robust funding sources, they also create complex due diligence considerations around governance, geopolitical risks, and cross-border collaboration. The rewards can be enormous for AI startups willing to engage with these funding sources, but the partnerships require navigating differing regulatory environments and long-term strategic interests.
Strategic Implications for AI Stakeholders
For AI startups heading into 2025, runway management and clarity of milestones are crucial. Investors now want evidence of tangible progress—both in the form of commercial traction and true technological breakthroughs. Companies that cannot clearly articulate their AI differentiation risk falling into the “AI washing” trap and losing investor confidence. Conversely, those that merge domain expertise with AI mastery can secure premium valuations and capture early customers hungry for advanced, data-driven solutions.
Venture firms are likewise navigating a new normal in which AI coverage is almost a prerequisite. Supporting AI portfolio companies requires on-staff data scientists, technical advisors, and proven go-to-market strategists. Firms that only dabble in AI may miss the next breakout wave or fail to help their portfolio companies effectively. Consequently, many VCs are building specialized AI teams or forging alliances with corporations and research institutions to refine their investment strategies.
Established AI funds have a clear fundraising advantage: They can showcase successful deals, marquee partners, and an operational playbook tailored for AI startups. Emerging managers must still convince LPs that their specialized approach will deliver unique opportunities that are inaccessible through bigger funds. Transparent communication around sourcing advantage, technical expertise, and ongoing market research can help secure commitments, though it remains an uphill battle in an era of heightened selectivity.
(Insert Figure 8 here to depict a framework or matrix for evaluating AI startups, focusing on technical depth, data strategy, market readiness, and potential for real-world impact.)
A More Disciplined AI Era
In 2024, the venture capital market stood at the intersection of modest global recovery and an AI revolution that continues to redefine industries. AI now accounts for over one-third of all VC funding, demonstrating growth beyond early-stage hype. The sector’s range—spanning massive foundation-model investments to niche sub-fields with specialized applications—speaks to AI’s transformative possibilities.
Yet the landscape is not without caution. Deal scrutiny has intensified, and LPs remain selective, favoring large established funds or smaller domain-expert managers with clear AI theses. Nonetheless, signs indicate an even more active AI exit environment in 2025, powered by a potential IPO rebound and robust M&A demand. Corporations are doubling down on AI, governments worldwide are deploying vast sums to energize domestic innovation, and early-stage AI startups continue to proliferate at an impressive pace.
The market is poised for a more disciplined, fundamentals-driven AI era. While AI mania is real, it aligns with genuine technological leaps that promise to reshape how we live, work, and interact with one another. For founders, this means honing operational execution and demonstrating core AI competence; for investors, it means exercising due diligence, technical acumen, and a willingness to support teams that can prove AI’s real-world impact. As 2025 unfolds, the challenge and opportunity lie in recognizing which AI ventures can stand the test of time and deliver on AI’s extraordinary, if still evolving, promise.
Let’s Wrap This Up (key takeaways)
For VCs:
Double Down on AI Specialization: Even if you’re running a large, established fund, consider building specialized AI teams or partnering with deeply technical advisors. AI quickly becomes the core of every investment thesis, so a standalone “AI strategy” is no longer optional.
Balance Mega-Deals with Emerging Opportunities: High-profile AI rounds (foundation models, generative AI) will grab headlines, but niche AI segments—robotics, synthetic data, sector-specific analytics—can deliver outsized returns if discovered early. Diversify between mega-rounds and under-the-radar opportunities.
For LPs:
Reassess the Bias Toward ‘Safe Hands’: Established managers have track records, but emerging AI-specialized GPs offer insider advantages, especially in fast-evolving subfields. By allocating some capital to domain-expert funds, LPs can gain exposure to early-stage breakthroughs that larger, generalist managers might miss.
Demand Clear AI Differentiation in Portfolios: Whether you invest directly or through fund-of-funds, insist on robust technical and commercial due diligence. “AI washing” is real, so ask GPs to provide concrete proof of their expertise to assess their pipeline and portfolio.
For Founders:
Demonstrate Tangible AI Impact: In a market flooded with “AI-first” pitches, show a clear link between your technology and a verifiable use case. Be prepared to answer tough questions on model uniqueness, data pipeline, and actual ROI rather than relying on AI buzzwords.
Secure the Right Strategic Backers: Beyond the check size, look for investors who can offer specialized AI expertise, large-scale data partnerships, or corporate connections. This is especially critical if you aim to commercialize scientific breakthroughs (e.g., generative biotech or advanced robotics).
For Corporate Executives:
Leverage CVC to Acquire or Invest in AI Startups to Accelerate Innovation: Venture investments or targeted acquisitions can rapidly expand AI capabilities while insulating your core business from lengthy in-house development cycles. Strategic deals often bring immediate technical talent and IP, making them a shortcut to staying ahead of competitors in an arms race for AI leadership.
Future-Proof the Business Model with AI: AI’s transformative potential extends beyond operational efficiency. It can unlock new revenue streams and reimagine product and service delivery. By strategizing around long-term AI capabilities rather than one-off use cases, corporate executives position their organizations to remain competitive, regardless of how rapidly the technological landscape evolves.
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