The investment question has changed with it. The first phase of AI investing was led by hyperscalers, advanced semiconductors, and large language model developers. The current phase has been driven by infrastructure buildout, and markets have already recognized much of that trade. Over the next few years, we expect the most attractive opportunities to center on more persistent bottlenecks, particularly around power, and on companies that control workflow, own the customer relationship, bring domain expertise, and turn AI output into business action. That includes the software infrastructure and applications that will shape how AI is deployed and managed. As companies integrate AI into workflows, adopters across industries should benefit. We expect much of the next phase of value creation to come from emerging AI-native companies and disruptive business models, though at this early stage, even today’s disruptors may be displaced.

In this edition of VantagePoint, we focus on three questions:

• Which bottlenecks are durable?
• Can rising revenues justify the capital required to sustain leadership?
• Where can value persist as AI becomes cheaper, more capable, and more widely available?

The broader consequences for labor and society may prove profound, but they remain harder to observe clearly and are progressing slower than the technology itself. Regulation and sovereignty risk considerations clearly matter, as does society’s willingness to absorb the pace of change and its consequences. Those forces will shape AI’s development, but they are not the focus of this paper. We focus instead on where the evidence is strongest today and where the investment implications are becoming harder to ignore.

Tech is still early, moving fast

AI capabilities continue to improve at breakneck speed. The leading labs remain in a tight race, and each major release raises the bar while increasing disruption risk for incumbents and start-ups alike. Leadership among US models continues to oscillate. Chinese models have narrowed the gap on several technical measures despite US export controls on advanced chips. The open-model ecosystem, much of it coming from China, has also become a credible lower-cost option for use cases outside of mission-critical workflows that still demand premium US tools.

Frontier intelligence is becoming more capable, more available, and less exclusive. That should expand adoption, but it also makes raw model access a less reliable source of durable advantage and shifts value toward the assets and capabilities that make intelligence useful, governable, and hard to replace.

AI is shifting from a tool that generates responses to a tool that performs useful work. Recent model releases have improved reasoning, reliability, memory, and the ability to work across different types of data. Anthropic’s AI model, Claude, helped accelerate the move from coding assistant to autonomous coding agent through Claude Code, then extended that logic into broader knowledge work. While this is a major disruptive theme and a central focus of this paper, it is only one part of a broader transformation. Specialist models in mathematics, biology, and other fields are proliferating, while researchers continue to experiment with non-transformer architectures such as world models designed for physical AI. Smaller models are improving as well, pushing more inference to run on local systems instead of keeping them entirely in centralized cloud environments.

These advances are beginning to make disruption more visible. In software, faster model improvement is compressing product cycles, narrowing functional differentiation, and pressuring application-level moats that once appeared durable. In labor-intensive workflows such as customer service, the effects are already showing up in shorter handle times, lower staffing needs, and greater pressure to automate routine work. Much of the broader disruption still lies ahead, but the direction is clearer.

Enterprise AI adoption is rising, but scaled deployment remains limited

The pace of enterprise adoption is becoming increasingly apparent, even if scaled deployment remains limited and difficult to track in real time. McKinsey survey data captures the key point for investors: adoption is rising, but much of it still reflects experimentation, piloting, and limited deployment rather than full integration across core workflows.

Coding remains the clearest use case, though productivity gains are still early and uneven. Deployment inside real organizations will be challenging, requiring integration, oversight, and governance as much as good model performance. Usage will evolve as service models change. For example, firms are still enjoying subsidized model pricing, internal controls are weak, and many firms are still learning to use these tools effectively while keeping token costs under control.

As AI advances rapidly, the need for stronger corporate governance is becoming more urgent, even if progress is moving at a more human pace. Some early adopters are pulling ahead in part because they addressed governance, access controls, and oversight sooner, making scaled deployment in sensitive workflows easier. Others may appear to be moving faster precisely because they are deferring those disciplines and accumulating a governance backlog that has not yet surfaced in operating results. Recent events also show how quickly regulatory and security concerns can affect commercialization. Anthropic’s temporary withdrawal of Fable 5 and Mythos 5 following a US government directive serves as a reminder that deployment risk may increasingly hinge on security, liability, and policy judgments. Public backlash is also growing, which could make regulation more political over time. As AI use broadens, questions of data provenance, auditability, security, and liability are likely to matter even more.

This shift from experimentation to scaled use is changing the investment question. Technical progress and broader adoption are making AI more commercially relevant, but they do not by themselves determine where durable returns will accrue. That depends increasingly on the economics of deployment and on which firms can turn AI capability into repeatable business action.

How AI economics are evolving

In our last edition of VantagePoint: The Rearview Mirror Problem, we argued that investors often mistake recent winners for future return drivers. That risk is especially acute in AI. The first-wave beneficiaries are well known, and the infrastructure buildout has become the market’s central focus. The harder question now is how the economics are evolving beneath that narrative, and which parts of the opportunity set can still deliver durable returns. We think investors should focus on three underwriting questions: Which bottlenecks are durable? Can rising revenues justify the capital required to sustain leadership? Where can value persist as AI becomes cheaper, more capable, and more widely available?

The economics are changing along with the technology. Constraints have shifted from training toward inference, usage, and deployment, and value capture is broadening with them. The relevant opportunity set now extends beyond frontier-training hardware to a broader mix of inference and data infrastructure, deployment software, workflow and permission layers, governance tools, and applications that shape how AI is embedded in business processes.

Earnings have begun to catch up with enthusiasm in parts of the AI ecosystem. Recent gains in AI-linked equities no longer rest on expectations alone. Several leading firms have reported strong revenue growth tied to AI demand, especially in semiconductors, cloud, and selected infrastructure segments. Private model providers, such as Anthropic, appear to be seeing similar momentum, though their economics remain less transparent. Stronger fundamentals validate part of the move. They do not settle the harder question of whether revenue growth will prove durable enough to justify the operating and capital costs required to sustain it.

Which bottlenecks are durable?

This first question deals with whether bottlenecks are persistent or simply reflect temporary undersupply. Early in the cycle, scarcity centered on training compute and raw GPU capacity. That is no longer the full story. As AI deployment scales, the tighter constraints are becoming more physical. Data center infrastructure, memory, and advanced packaging remain important, but power is emerging as the clearest hurdle. Reliable electricity, cooling, transmission, and the ability to bring new capacity online increasingly matter as much as access to chips. ¹

Falling prices in one layer of the stack do not remove constraints in another. Listed token prices have fallen sharply, which should broaden adoption. But lower prices do not mean lower compute demand. As models have become more capable and AI systems take on more complex tasks, the compute required to complete useful work has continued to rise. More autonomous and always-on systems will reinforce that trend by increasing token consumption and placing greater strain on the physical stack.

Power deserves particular attention because it is increasingly one of the hardest constraints to relieve. Utilities, grid equipment, cooling, and related enabling infrastructure can be difficult to replicate quickly because they depend on permitting, transmission access, engineering capacity, and time to build. Those are more durable barriers than the temporary scarcity that can emerge in parts of the hardware stack early in a buildout.

Memory and advanced packaging also remain important choke points, supporting stronger pricing and earnings across parts of the semiconductor ecosystem. The key investment question, however, is not whether these areas are constrained today, but whether those rents are likely to persist. Some supply bottlenecks may prove temporary as capacity expands. Others may reflect capabilities that are harder to replicate quickly.

In some parts of the market, security, compliance, and regulatory approval may also function as bottlenecks. Where customers need trusted systems for sensitive workflows, firms that can meet higher standards for resilience, auditability, and control may accrue durable advantage.

Not every bottleneck supports durable economics. Some stem from short-lived pricing power. Others are tied to assets, regulation, siting, expertise, or customer relationships that are harder to reproduce. Open and lower-cost models reinforce that point. They may broaden adoption and accelerate experimentation, but they also challenge the idea that frontier capabilities alone guarantee durable pricing power. In areas where customers do not require frontier performance or tightly integrated proprietary systems, improving open models are compressing economics at both the model and software layer.

Can rising revenues justify the capital required to sustain leadership?

The second question asks whether rising revenues and earnings can justify the capital required to sustain AI leadership. That issue is now most visible in the capex cycle. For current spending to earn attractive returns, revenue growth must continue to catch up with investment, usage must remain high, enterprise monetization must deepen, and margins must hold up despite a much larger capital base.

Consensus expectations for the five major hyperscalers call for combined revenue to increase 54% while EBITDA is expected to increase about 111% from year-end 2025 through 2028. Over the same period, depreciation is expected to rise much faster. Depending on assumed asset lives, it could increase by roughly 175% to more than 340%. That drag is large enough to matter. At the low end of those estimates, 2028 depreciation would come close to the group’s 2025 net income of $405 billion.

AI is making important parts of technology more capital intensive. Some parts of the market may still be valued as if AI were reinforcing capital-light software economics, when in fact it is making important parts of the stack more asset-heavy and operationally demanding. Investors should place more weight on depreciation, reinvestment needs, financing conditions, and the durability of pricing power on these more asset-heavy companies.

Memory is not a direct analogue for hyperscalers, and the current AI cycle has different drivers. Still, its history is a useful reminder that periods of tight supply, strong pricing, and high margins can look more durable than they prove to be once capacity expands. Shortages have repeatedly lifted margins and encouraged new investment, only to erode those same margins as supply caught up. AI may not follow that path exactly, but the lesson is familiar. Strong demand does not by itself protect returns when supply can respond and pricing power is not well defended.

Indeed, Micron and SK Hynix—two of the memory companies most directly exposed to advanced AI demand—have increased capex by a combined 70% in each of the last two years, and consensus expects another roughly 55% increase in 2026. Investors should be careful not to assume that today’s strong pricing and profitability will persist unchanged as capital spending rises and supply responds.

The quality of demand matters as well. Investors should distinguish between durable end demand and demand supported by ecosystem-linked commercial arrangements, strategic subsidy, or circular deal structures that make near-term economics look stronger than they are. As the system matures, leverage and structured financing also deserve more attention. Risk rises when capital assumptions become aggressive ahead of proven cash flows. After rising by roughly $900 billion since the start of this year, gross supply of investment-grade credit is expected to increase by about 17% over the full year to a record $2.1 trillion, with much of the increase coming from hyperscalers and related infrastructure. Structured credit markets are expected to see data center securitizations rise by nearly 50% in 2026 to $30 billion.

Stronger fundamentals have made the buildout more credible, but not necessarily more durable. High depreciation expense creates a demanding hurdle for hyperscalers that are increasingly competing with one another for business. Capital-intensive businesses facing rising competition may struggle even if the addressable market continues to grow. Not all participants will fare well. Semiconductors and advanced memory should benefit from tight supply and, in some cases, multi-year contracts, but supply is likely to catch up over time as capacity expands and technology becomes more efficient. Investors should be cautious about extrapolating today’s pricing and profitability too far into the future.

Where can value persist as AI becomes cheaper, more capable, and more widely available?

The final question considers where durable value can persist. Access to models alone will not remain enough. As intelligence diffuses, we expect more defensible positions to belong to firms that control how it is used: who owns the workflow, governs permissions, controls distribution, and connects output to execution. Hyperscalers and other large platforms are trying to capture value across multiple layers of the stack through vertical integration, from compute and cloud infrastructure to model access, routing, deployment, and enterprise tooling.

The most important shift is in what software and adjacent systems actually do. As agentic systems begin to perform economically meaningful work rather than simply assist users, part of the addressable market shifts from software budgets to labor budgets, which are much larger. That may expand revenue pools, deepen integration, and create stronger business models. It may also intensify disruption across software, services, and selected consumer sectors.

Software and adjacent control layers may still be where much of the value ultimately accrues, but they also pose the hardest underwriting questions. AI may expand revenue pools even as it weakens traditional moats. Customers may expect broader functionality without proportional price increases, while model, compute, orchestration, and support costs remain material. We expect the stronger positions belong to firms that are deeply embedded in a workflow, possess privileged task-specific context, and can convert AI output into completed work rather than simply sell access to a feature.

That distinction matters because control over the workflow is different from access to the model. A firm that helps generate an answer may be easy to displace. In an agent-driven environment, durable advantage should rest increasingly on control over permissions, approvals, and execution rather than on data alone. Systems that determine what autonomous software can access, trigger, and complete could have a competitive upper hand over systems of record alone.

This logic extends beyond enterprise software. In consumer markets, such as commerce, education, and travel, AI is likely to reshape discovery, service, and execution. New products and business models should emerge. But these same layers may also face the greatest pressure from improving models and larger platforms, especially where functionality is easy to replicate, customer relationships are weak, or distribution is controlled by someone else.

The same logic also shapes investment underwriting. Strong adoption and fast top-line growth may not be enough if a company with limited bargaining powers depends heavily on a single model provider, hyperscaler, or distribution platform. Downstream growth may prove real without translating into durable economics. Strategic acquisition may become a common end state for promising firms, supporting investment outcomes alongside a select group of independent long-duration compounders. For private equity and venture investors, underwriting should place more weight on customer ownership, monetization after model and compute costs, governance quality, likely end states, and the durability of economics if acquisition interest fades.

Investment implications

AI should be treated as a system-wide set of exposures rather than a narrow thematic trade. We see the stronger opportunities ahead in harder-to-relieve bottlenecks—especially power and related infrastructure—alongside the software and application layers that govern deployment in real workflows and emerging AI-native businesses that can reshape industry economics. The same shift should benefit adopters that use AI to improve their own economics while increasing disruption risk for incumbents that fail to adapt or are displaced by new business models.

This shift argues for more caution toward parts of the AI ecosystem where expectations, capital spending, and competition have all risen sharply at once. Large hyperscalers remain central to the buildout and may continue to benefit from scale, distribution, and enterprise integration. But they are also engaged in an increasingly costly race to secure compute, power, and physical infrastructure, and the associated depreciation burden is becoming harder to ignore. We therefore lean away from the most crowded first-wave winners, particularly where valuations still leave limited room for disappointment. The same caution applies to parts of semiconductors and memory, where recent earnings strength has been real, but history suggests investors should be careful not to mistake tight supply and current pricing power for durable advantage.

By contrast, we are more constructive on select infrastructure and real assets tied to harder-to-relieve constraints, particularly electricity infrastructure, grid access, and related enabling assets. These areas appear better positioned to benefit as AI deployment scales and physical bottlenecks become more binding.

The widening opportunity set also creates room for emerging disruptors, many of which were inconceivable before recent AI advances. As AI becomes cheaper, more capable, and more widely available, value will migrate toward firms that control workflows, permissions, customer relationships, and operational integration rather than those relying on thin wrappers or temporary model arbitrage. In software, the more durable positions are likely to belong to companies that can embed AI into economically meaningful tasks, govern it effectively, and monetize completed work rather than simple access. Private equity may benefit where businesses need capital, operational support, and technology investment to adapt successfully to AI-driven changes in cost structure and competition.

Venture capital remains the key channel for accessing emerging AI-native companies and disruptive business models, and investors seeking that upside likely need some participation in private markets. But this technology cycle is still early and, as in past cycles, a few winners are likely to emerge alongside many losers as innovation advances faster than commercial adoption. In that environment, exposure to AI is not the same as access to strong investment returns. Because private commitments are long-lived, pacing matters as much as manager selection. Investors should continue to allocate selectively, with discipline on timing and valuation rather than rushing to add exposure simply because the theme is compelling. As a new wave of highly anticipated technology IPOs comes to market this year, investors should be thoughtful about redeploying capital to venture capital, balancing those opportunities against other market segments with more attractive valuations and differentiated return potential.

The same framework should also be applied defensively. AI is not only a source of new opportunity. It is also a source of disruption risk in existing holdings. Businesses with weak differentiation, labor-intensive models, or information-heavy processes may be more vulnerable than they appear, even if they sit outside any obvious AI category. Equity long/short hedge funds may be well positioned to benefit from rising dispersion as AI creates clearer winners and losers across software, services, and other information-intensive industries. As disrupted companies—especially ones that took on private debt during the period of zero interest rates and high valuation from 2021 to early 2022—struggle to refinance over the next few years, stressed and distressed opportunities may emerge.

AI remains an important area of exposure. From here, we expect the best opportunities to come from identifying durable bottlenecks, defensible control points, and the businesses most likely to benefit from disruption rather than suffer from it. Active management across public and private markets will be central to success.

Graham Landrith and Justin Hopfer also contributed to this publication.

Index Disclosure

MSCI All Country World Index (ACWI)
The MSCI ACWI captures large- and mid-cap representation across 23 developed markets (DM) and 24 emerging markets (EM) countries. With 2,558 constituents, the index covers approximately 85% of the global investable equity opportunity set. DM countries include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland, Israel, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the United Kingdom, and the United States. EM countries include Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Korea, Kuwait, Malaysia, Mexico, Peru, the Philippines, Poland, Qatar, Saudi Arabia, South Africa, Taiwan, Thailand, Turkey, and the United Arab Emirates.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.

The post VantagePoint: Artificial Intelligence Investing After the First Wave appeared first on Cambridge Associates.

The implications for public equity indexes are meaningful. Together, these companies are expected to list at a combined valuation approaching $4 trillion, more than the total amount raised in all IPOs during the entire dot-com era. While the initial free float for each is likely to be far smaller, ² index requirements have either already been waived, or are likely to be waived, so these firms could enter major indexes relatively quickly. Over time, as floats and index weights increase, OpenAI and Anthropic would further expand the large weight of technology in public benchmarks, while SpaceX could blur traditional sector lines across industrials, communications, and technology. Their addition could also make expensive parts of the market look richer still. None of the three companies are yet profitable, and SpaceX’s targeted $1.75 trillion valuation would equate to roughly 100x its 2025 revenues.

Public market investors will gain access to the leading artificial intelligence (AI) franchises and the dominant private space and satellite communications platform. But by the time these companies list, much of the earliest and most explosive upside may already have accrued to private investors. That points to how the financing model for innovative companies has changed. Previous generations of high-growth firms often went public relatively early to fund expansion; today’s largest private companies can remain private much longer because they have access to enormous pools of capital. OpenAI raised more than $120 billion in a private round earlier this year, and Anthropic is reportedly raising about $30 billion privately. As a result, these IPOs are not just about raising capital but also about providing liquidity, establishing transparent price discovery, and broadening the shareholder base. Public markets are no longer the first engine of scale for companies like these, but they remain the main venue for liquidity, governance visibility, and wide ownership.

These offerings could affect the broader IPO market by drawing capital away from other new issues. While Anthropic has not yet filed, SpaceX and OpenAI are each rumored to be seeking at least $60 billion in IPO proceeds, more than double the previous US record set by Alibaba in 2014. In any issuance window, investors have finite risk budgets, portfolio capacity, and attention. Offerings of this size could dominate the calendar and lead investors to fund participation by trimming allocations elsewhere. Even so, Goldman Sachs expects total equity issuance in 2026 to be around $600 billion, including IPOs, which would still amount to less than 1% of US equity market capitalization. That suggests the broader market should absorb these deals without major dislocation, even if they temporarily crowd out smaller offerings.

For venture investors, the implications are more nuanced. Successful IPOs could boost fund-level marks and eventually help convert paper gains into realized distributions, though liquidity may be more gradual because initial floats are small and, at least in SpaceX’s case, tiered lock-ups would make some future sales partly dependent on stock performance. Because funding in these companies has been so concentrated, their IPOs could further widen the gap between top- and bottom-performing venture funds, reinforcing the importance of manager selection. They may also influence future capital deployment by requiring some funds to cast a wider net. Five companies, including OpenAI and Anthropic, accounted for more than 80% of US venture funding in first quarter 2026. Subject to tax and cost considerations, some investors may wish to consider hedging arrangements for what may end up being outsized single positions. For taxable investors specifically, there may be additional options to diversify risk and offset or defer taxes, including direct indexing or extension strategies.

Overall, these mega-IPOs matter less because of the immediate size of their public floats than because of what they signal about valuation, liquidity, and capital formation. Their small initial floats should limit near-term market impact, but their rich valuations raise the risk that public investors gain access only after much of the upside has been captured privately. And while the offerings are likely to be digested by the overall market, their prominence may crowd out other issuers in the near term. For venture investors, that creates both tailwinds and headwinds: stronger marks, realizations, and distributions for the best-positioned funds, but also greater concentration risk and a tougher environment for other portfolio companies seeking to go public.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.

The post Do Mega-IPOs From Companies Like SpaceX, OpenAI, and Anthropic Mark a Changing Relationship Between Public and Private Markets? appeared first on Cambridge Associates.

The conversation covers key topics such as the importance of longevity in venture investing, the impact of allocation size, and the often-overlooked role of governance. Michael also shares practical guidance on defining an illiquidity budget, understanding the risks and rewards of co-investing, and why elite limited partners are comfortable with “spiky” returns.

Whether you’re an experienced investor or new to venture capital, this discussion offers valuable perspectives on building a thoughtful, resilient portfolio in a complex and evolving market.

Watch the full conversation below to gain deeper insights into effective venture portfolio construction.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.

The post The Biggest Mistake Investors Make When Building a Venture Capital Portfolio appeared first on Cambridge Associates.

Not long after the Federal Reserve began increasing interest rates in March 2022, ChatGPT was publicly launched and became the fastest-growing consumer application in history. Alongside rising interest rates, beginning in late 2022, software revenue growth rates and valuations quickly receded, creating long-term challenges for general partners who overinvested based on growth and valuation assumptions that turned out to be short-lived. By December 2022, median valuations for publicly traded software companies—which are used in valuing private software companies—had tumbled from a pandemic high of 19.0x revenue to 5.6x revenue.

More recently, median software revenue multiples have further compressed to 3.4x, reflecting investor concern that AI is going to eat software. Advancements in AI and their impact on the thousands of privately held software companies and valuations will not be as universal or immediate as what we have seen recently in the public markets. Some business models are immediately vulnerable, while others may exhibit more resilience due to having well-established moats across a range of attributes, such as solutions leveraging longstanding proprietary data or deeply embedded in customer workflows. AI represents both a risk and an opportunity in the private markets; thoughtful management of existing exposure and careful allocation toward this development could be long-term value drivers for today’s private investment portfolios.

Most private investment portfolios have long had material exposure to technology, and not just through their venture capital allocations. Technology, and really enterprise software, has held the top spot in private equity for more than ten years with a commanding lead. From a private markets perspective, current investment outcomes for this sector may ultimately sort themselves into two cohorts: pre-mid-2022 investments and post-mid-2022 investments. The first cohort is arguably most at risk, deployed at entry values, growth rates, and leverage assumptions reflecting a bygone era; it is not surprising that returns have come down and distributions have slowed for these vintages overall. While the second cohort was deployed in an environment that had begun to reset, it still must grapple with the implications of AI for its business models and investment success.

Managers and management teams have been assessing AI’s risk to business models while also integrating AI as a means to enhance, expand, or protect those models. At present, private equity managers are busy communicating with investors about their firms’ AI capabilities and portfolio company initiatives because sustained operating performance proof is yet to come. It will take varying amounts of time for these ongoing efforts to show up in the financials, which will ultimately determine investment value. In the meantime, we expect to see a slowdown in overall enterprise software transaction activity as managers and companies re-tool for this paradigm shift, alongside an increase in investment activity involving AI-native companies, either as platforms or as add-ons.

The paradigm shift isn’t down, it’s forward. AI will further expand the technology sector and will drive more investment; it already has, having largely taken over venture capital activity. Appreciating that it is a tumultuous period for enterprise software, technology as a whole is not going to stop being a dominant sector for investment. In fact, it’s likely to continue to expand. Limited partners are actively monitoring existing software investment developments in their portfolios for indications of progress or regress, which in turn will inform portfolio management decisions and also forward investment. In addition, as managers adjust to current developments, forward investing activity should reflect and express their views on how to earn their target return in this new paradigm. As performance unfolds, there will be a separation between those who find their way successfully through this market and those who do not; investor capital will move accordingly.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.

The post Has Private Equity Hit Peak Software? appeared first on Cambridge Associates.

First half 2025 highlights

• The US PE index has had mixed results against public markets over the last five years, generally outperforming small-cap and equaling or underperforming large-cap indexes. In periods ten years and longer, PE’s outperformance is more consistent. Amid a historically strong market for large, public tech companies, the US VC benchmark has only consistently outperformed small-cap stocks, while struggling to keep up with the large-cap S&P 500® and tech-heavy Nasdaq indexes.
• By market value, public companies accounted for a larger percentage of the VC index (about 7%) than the PE index (about 4%), as of June 30, 2025. Non-US companies represented almost a quarter of PE and a little less than 15% of VC.

US private equity performance insights

Vintage years

As of June 2025, eight vintage years (2016–23) were meaningfully sized—representing at least 5% of the benchmark’s net asset value—and, combined, accounted for 85% of the index. Six-month returns among the key vintages ranged from 0.6% for vintage year 2016 to 6.9% for vintage year 2023 (Figure 2).

Double-digit returns from communication services investments and mid-single-digit returns from healthcare, industrials, and IT were the biggest return drivers of for the 2023 vintage, while slightly negative returns in its two largest sectors, industrials and IT, dampened performance for the 2016 funds. The fund’s age or vintage year is one consideration when comparing returns across vintages as time is a component of the internal rate of return (IRR) calculation used for PE investments. In the current environment, hold periods have been extended, which will impact IRRs but not necessarily other return metrics, such as multiples of invested capital.

During the first two quarters of 2025, fund managers distributed more capital than they called—$78.9 billion and $67.6 billion, respectively. If this pace holds for the remainder of the year, 2025 will be a slower year than 2024 for both calls and distributions.

Five vintages (2021–25) accounted for almost all the capital called during the first six months. Two of those vintages, 2022 and 2023, were responsible for more than half the calls ($37 billion), which reflects both where they are in their investment periods and the size of those vintages in relation to the 2024 and 2025 cohorts. As is often the case, distributions were much less concentrated than contributions, and in this period, every vintage from 2012 to 2021 accounted for at least 5% of the distributions. The five most active vintages on the distribution front were 2016, and 2018–21, a potentially hopeful sign for limited partners (LPs) feeling a liquidity crunch.

Sectors

Figure 3 shows the Global Industry Classification Standard (GICS®) sector comparison by market value of the PE index and a public market counterpart, the Russell 2000® Index. The breakdown provides context when comparing the performance of the two indexes. The PE index has a significant overweight to IT and communication services as well as a meaningful underweight in “real assets,” including energy, real estate, and utilities (reflected in the “Other” category), while the public market has consistently been overweight to financials.

As of June 2025, at about 36% of the index’s market value, IT continued to be the largest among the six meaningfully sized sectors. Combined, the next four sectors by size—industrials, healthcare, consumer discretionary, and financials—accounted for almost 50% of the index’s value. Among the key sectors, first half returns ranged from 2.5% for consumer discretionary to 7.2% for financials. Healthcare and industrials both returned about 5%.

Three sectors garnered 70% of the capital invested by US PE managers in the first half of 2025: IT (36%), healthcare (18%) and industrials (16%). Over the long term, managers have allocated 53% of their capital to those three sectors. The biggest driver of the difference was the percentage of capital allocated to IT (historically 24%). In 2025, communication services and financials companies attracted more investment than consumer discretionary businesses, in contrast with the long-term trend.

US venture capital performance insights

Vintage years

As of June 2025, eight vintage years (2015–22) were meaningfully sized and, combined, accounted for 72% of the index’s net asset value. Performance for the key vintages during the first half of the year was mixed, ranging from -2.5% (2015) to 8.6% (2022) (Figure 4). Since its stretch of seven consecutive down quarters from January 2022 to September 2023, the VC index has now posted positive returns in all but one quarter.

The best-performing and least mature key vintage (2022) benefited from gains across sectors, with its largest exposures (IT and healthcare), posting double-digit gains. Results for the worst-performing and oldest key vintage (2015) were the opposite, with negative returns for the same two largest sector exposures, IT and healthcare.

In first half 2025, VC managers called more capital than they distributed ($26.9 billion and $16.1 billion, respectively), and if the pace were to hold for the remainder of the year, 2025 will be a more active year than 2024. Since the beginning of 2022, US VC managers have called 1.6x more capital than they have distributed. In the ten years prior (2012–21), the relationship was flipped, and they distributed 1.3x what they called.

Five vintages (2021–25) accounted for nearly all the capital called during the first six months. Three of those vintages (2022–24) were responsible for almost 70% of the calls ($18 billion). Like PE, distributions were much less concentrated than contributions, and in this period, all vintages from 2012 to 2020 accounted for at least 5% of the distributions. While the 2014 funds distributed the most ($2.7 billion), there were six others that returned more than $1.3 billion to LPs.

Sectors

Figure 5 shows the GICS® sector breakdown of the VC index by market value and a public market counterpart, the Nasdaq Composite Index. The breakdown provides context when comparing the performance of the two indexes. The chart highlights the VC index’s substantially higher exposures to healthcare, industrials, and financials and its lower weightings in communication services and consumer discretionary. The Nasdaq index currently has a higher tilt in IT, largely a product of an extended bull run in public tech companies.

As a group, the four meaningfully sized sectors made up 87% of the VC index, and returns ranged from 0.2% for healthcare to 29.7% for financials. The IT sector’s return was “middle of the pack,” while results for industrials were strong.

During the first six months, VC managers in the index allocated 85% of their invested capital to IT (48%), healthcare (26%), and industrials (11%). Over the long term, those sectors have garnered less than 80% of the capital, with the difference driven by the larger-than-normal allocations to IT and industrials, and lower-than-normal investment in healthcare in 2025. ■

Figure notes

US private equity and venture capital index returns

Private indexes are pooled horizon internal rates of return, net of fees, expenses, and carried interest. Returns are annualized, with the exception of returns less than one year, which are cumulative. Because the US private equity and venture capital indexes are capitalization weighted, the largest vintage years mainly drive the indexes’ performance.

Public index returns are shown as both time-weighted returns (average annual compound returns) and dollar-weighted returns (mPME). The CA Modified Public Market Equivalent replicates private investment performance under public market conditions. The public index’s shares are purchased and sold according to the private fund cash flow schedule, with distributions calculated in the same proportion as the private fund, and mPME net asset value is a function of mPME cash flows and public index returns.

Vintage year returns

Vintage year fund-level returns are net of fees, expenses, and carried interest.

Sector returns

Industry-specific gross company-level returns are before fees, expenses, and carried interest.

GICS® sector comparisons

The Global Industry Classification Standard (GICS®) was developed by and is the exclusive property and a service mark of MSCI Inc. and S&P Global Market Intelligence LLC and is licensed for use by Cambridge Associates LLC.

About the Cambridge Associates LLC indexes

Cambridge Associates derives its US private equity benchmark from the financial information contained in its proprietary database of private equity funds. As of June 30, 2025, the database included 1,700 US buyout and growth equity funds formed from 1983 to 2025, with a value of $1.6 trillion. Ten years ago, as of June 30, 2015, the index included 990 funds whose value was $523 billion.

Cambridge Associates derives its US venture capital benchmark from the financial information contained in its proprietary database of venture capital funds. As of June 30, 2025, the database included 2,699 US venture capital funds formed from 1981 to 2025, with a value of $591 billion. Ten years ago, as of June 30, 2015, the index included 1,593 funds whose value was $188 billion.

The pooled returns represent the net end-to-end rates of return calculated on the aggregate of all cash flows and market values as reported to Cambridge Associates by the funds’ general partners in their quarterly and annual audited financial reports. These returns are net of management fees, expenses, and performance fees that take the form of a carried interest.

About the public indexes

The Nasdaq Composite Index is a broad-based index that measures all securities (more than 3,000) listed on the Nasdaq Stock Market. The Nasdaq Composite is calculated under a market capitalization–weighted methodology. The Russell 2000® Index includes the smallest 2,000 companies of the Russell 3000® Index (which is composed of the largest 3,000 companies by market capitalization). The Standard & Poor’s 500 Composite Stock Price Index is a capitalization-weighted index of 500 stocks intended to be a representative sample of leading companies in leading industries within the US economy. Stocks in the index are chosen for market size, liquidity, and industry group representation.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.

The post US PE/VC Benchmark Commentary: First Half 2025 appeared first on Cambridge Associates.

by Andrea Auerbach

While the last year has been one of recovery for the private markets, the aftershocks of the 2021 era continue to reverberate, with both the distribution drought and concomitant fundraising slowdown expected to extend their four-year runs into 2026. We believe the private markets have now troughed and the recovery phase is underway amid an evolving market structure that demands fresh thinking from institutional investors and sophisticated families.

Let’s start with the secondary market, which we believe will continue to develop in 2026. Why? Because in this extended distribution drought, investors from all sides have been taking liquidity matters into their own hands. Many limited partners (LPs) have entered the secondary market as first-time sellers and general partners (GPs) have expanded the use of continuation vehicles (CVs). In fact, CVs are estimated to represent at least 20% of distributions in 2026 as LPs overwhelmingly opt for the “sell” option rather than roll. Manufacturing liquidity is one reason secondaries transaction activity has hit an all-time high in 2025, and we expect this trend to continue into 2026. Secondaries activity makes up less than 5% of all private market activity, which leaves a lot of room for expansion. With a pattern of earlier distributions and an early return bump, secondaries are likely to become a base layer in private market portfolios to offset unexpected primary fund investment return (and cash flow) volatility like we have recently experienced.

Individual investor capital will continue to replace or augment institutional capital in 2026. The institutional fundraising drought, which troughed in 2025 at a mere one-third of 2021 volumes, may have even been an unwitting accelerant in efforts to open the private markets to individual investors through varying outlets—including fund investment platforms, evergreen funds, interval funds, and defined contribution or similar program inclusion—as managers seek to diversify away from institutional sources of capital. The emerging individual investor class is participating through vehicles that imperfectly overlap with institutional investor structures yet invest in the same securities. Investment outcomes and implications will continue to reveal themselves in the coming year, and institutional investors and sophisticated families could benefit from positioning exposures to benefit from this surge or, at the very least, be somewhat insulated based on where capital is being collected.

The rise of the individual investor is accelerating the market bifurcation we first observed in 2019. Mega-managers, namely those who have expanded, acquired, or partnered to offer a range of private market investment options, are best positioned to capture the flag in the race for retail capital. These mega-managers, many of which are publicly traded, may indeed amass the lion’s share of aggregate investor capital, and, as a consequence, their role in a private investment portfolio will likely morph into something different as they manage multiples more capital than the rest of the market; institutional investors and sophisticated families will need to rethink the megas’ role in portfolios.

By our estimate, the institutional private market is only in its fifth decade, and many of the changes and shifts echo the evolution of other investment markets, with much of the morphing happening in the upper elevations as fund sizes continue to climb. The key in 2026 is to begin to adapt to these changes in market structure. Actively consider the use of secondaries in a portfolio, determine how to invest advantageously around or into the individual investor wave, and tier private market exposure to capitalize on both return and diversification, given the concentration of returns in other markets.

Investors should moderate commitments to seed-focused venture capital strategies in 2026

by Zach Gaucher

Early-stage–oriented venture capital programs have historically delivered the asset class’s best risk-adjusted returns, and we expect that to continue. However, for most investors in 2026, we advocate for limiting new commitments to exceptional pre-seed and seed-stage–focused strategies, given the maturation of the seed asset class, heightened early-stage valuations, and the elevated bar to go public.

As has been clear for some time, venture is no longer a cottage industry. More than 4,200 venture funds have been raised in the United States since 2022, many of which are pre-seed and seed-stage funds with less than $100 million of committed capital, according to Pitchbook. Even as mega funds—those larger than $1.0 billion—make up 40% to 60% of the total commitments raised over the same time period according to Cambridge Associates, there continues to be a proliferation of smaller seed funds.

The growth of seed funds has helped to support a thriving ecosystem resulting in more than 5,000 seed stage rounds each year since 2022. ³ However, this activity—combined with larger, multi-stage firms moving into the ecosystem—has pressured valuations. While valuations are heightened across stages, seed valuations did not reset following the activity in 2020 and 2021 and have marched steadily upward.

The “private for longer” dynamic compounds the challenges facing current seed-stage investors. As average hold periods extend, and the bar to go public or achieve significant M&A becomes more elevated, winners may become rarer and more consequential for the asset class. Of note, in the 21 recent venture-backed technology IPOs we track, these companies had median last 12-month (LTM) revenue of $537 million, LTM revenue growth of 31.4% and scored 32.6% on the Rule of 40. ⁴ Of course, we would be remiss to ignore that the majority of realizations for the asset class have been driven by M&A, but a healthy IPO market is the barometer by which the asset class is often judged.

For a seed manager investing in ten to 20 companies per year, allocating to a company that will reach today’s IPO scale reflects an out of the money option, given the more than 5,000 inception stage rounds that have occurred annually in recent vintages. Even getting to Series A remains an uncertain endeavor—just 15.5% of seed companies funded in first quarter 2023 had raised a Series A as of first quarter 2025.

The industry’s Power Law dynamic, which denotes that a small percentage of outcomes carry the industry’s returns, continues to play out in real time. Indeed, according to Cambridge Associates data, nearly 90% of the asset class’s value has been driven by the top 10% of companies. With these odds, allocators should be judicious in manager selection—pre-revenue, AI-focused seed funds may capture the zeitgeist but may not capture the Power Law. Allocators should commit to only exceptional seed managers and recognize that many new funds have similar profiles, with GPs often having strong operating or founding experience or spinning out of established firms resulting in a highly competitive, if somewhat undifferentiated dynamic.

LPs should be mindful that “missing” the Power Law winners can result in a venture program that underperforms expectations. While we are cautious on seed funds today, they have a role in venture programs. In other words, investors would be best served by thoughtfully committing to funds across the spectrum of stages, particularly when exceptional opportunities exist. Doing that will increase the odds that LPs can capture Power Law winners that slip through the grasp of earlier-stage managers.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.
3. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
4. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.

The post 2026 Outlook: Private Equity & Venture Capital Views appeared first on Cambridge Associates.

Of the $12.2 trillion currently held in Defined Contribution plans, $8.7 trillion is invested in 401(k) plans, a figure poised to grow because of the recent introduction of regulations requiring automatic enrollment alongside a $500 increase in the maximum annual contribution limit. If current 401(k) participants were to allocate just 10% to private investment offerings, nearly $900 billion of fresh capital would be heading for the private markets. This capital would be on top of the surging activity in evergreen and semi-liquid funds, which have been busy accumulating individual investor assets in their own right. By some accounts, the evergreen and semi-liquid markets have already attracted several hundred billion dollars in assets and are also expected to grow at strong clips. A recent survey indicated more than half of all private capital flows are projected to come from individual investors within two years.

By comparison, the institutional private equity and venture capital market has been in a slump, driven by a prolonged distribution drought that has trapped capital, much of which was invested at excessive valuations in 2021–22 that has yet to be productively harvested. This lack of distributions, coupled with short-term underperformance against public markets, has translated into several years of reduced commitments to the private asset classes. With institutional investors essentially on the sidelines, individual investors are an attractive source of capital for managers able to access them through the 401(k) market.

Target date funds (TDFs)—a growing subset of 401(k) strategies that adjust asset allocations as plan participants approach an expected year of retirement—could serve as the best place for private markets capital, given their long time horizons. General partners (GPs) offering private markets exposure to 401(k) participants will face challenges, including providing TDF managers the ability to rebalance, redeem, and access daily valuation information on private investments, which is not easy due to the highly illiquid nature and reporting constructs of private markets. Although their professional management and pooled nature can allow for more effective implementation, TDFs are still subject to all the liquidity and valuation requirements of a broader 401(k) offering. GPs will also have the challenge of delivering historical private investment returns in a structure that could impede the very elements that helped to generate those returns, including the requirement to invest immediately, which can impact entry valuation discipline and therefore returns.

What’s an institutional investor to do? We advocate “following the money,” by observing where it is accumulating because that will be where the pricing and return pressure will be most intense and investing in tiers of the market that stand to benefit from this burgeoning supply. Thankfully, with thousands of GPs in which to invest, the opportunity set for institutional investors extends far beyond those GPs in hot pursuit of the individual investor. Many investors can pursue compelling private investments at any tier of the private economy across a wide range of strategies and styles. Additionally, the current fundraising lull will likely result in less intense competition for portfolio companies that are beyond the reach of private investment funds servicing 401(k) funds over the next few years, potentially creating better opportunities and, therefore, stronger returns for intrepid institutional investors.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.
3. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
4. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.

The post Executive Order Opens the Gates to Private Markets appeared first on Cambridge Associates.

Calendar Year 2024 Highlights

• Returns for the US private equity (PE) index exceeded those of the S&P 500 for periods longer than three years as of December 31, 2024, and outpaced the small-cap index, the Russell 2000®, in all but two time periods analyzed (Figure 1). The US venture capital (VC) benchmark’s performance relative to public indexes has been less consistent, particularly against the tech-heavy Nasdaq.
• At the end of 2024, public companies accounted for a higher percentage of the market value of the VC index than of the PE one (roughly 7% and 5%, respectively). Both exposures represented declines from the prior few years. At the same time, non-US companies represented a bit more than 20% of PE and about 15% of VC.

US Private Equity Performance Insights

In many ways, 2024 was a continuation of 2023, with heightened geopolitical tensions, persistent valuation gaps between buyers and sellers, and a concentrated public market that created challenges for PE fundraising, investment activity, and exits. Growth equity performed better in 2024 than it did in 2023, and it outpaced buyouts. Limited partner (LP) cash flows rebounded somewhat in 2024, but the distribution yield remained shy of historical averages. At year end, nearly half of the index’s net asset value (NAV) resided in three vintages (2019–21), reflecting the outsized fundraising in those years.

According to Pitchbook, seven US PE-backed companies went public in 2024 and they were valued at $25 billion; the number of IPOs was the same as in 2023 and the overall value was up about $6 billion. IPO exits for US PE-backed companies have slowly picked up since nearly coming to a stop in 2022. Among the seven, three were IT or healthcare businesses, two were industrials companies, and there was one each in energy and education. The largest PE-backed IPO was StandardAero Aviation. The number of PE-backed merger & acquisition (M&A) transactions (742) trailed the total completed in 2023, the third consecutive drop in M&A exits. A quarter of the deals (184) had publicly disclosed valuations and based on the data available, the average transaction size among those deals was $1 billion, again less than the 2023 average. The second and fourth quarters in 2024 were slower by M&A number than the first and third, but average values were highest in the second and lowest in the fourth.

Vintage Years

As of December 2024, seven vintage years (2016–22) were meaningfully sized—representing at least 5% of the benchmark’s NAV—and, combined, accounted for 81% of the index’s value. Calendar year returns among the key vintages ranged from 3.2% for 2016 to 16.8% for 2022. The two largest vintages (2019 and 2021) returned 7.5% and 9.6%, respectively (Figure 2).

Part of the variability of returns across the vintage years was due to the performance of the individual strategies within the PE universe—buyouts and growth equity. For example, in the lowest-performing key vintage (2016), the bulk of the capital was raised by buyout funds and those managers earned only 1.2% in 2024, while growth equity returned 11.7%. For the best-performing large vintage (2022), the assets are more tilted to growth equity and both strategies earned strong returns.

From a sector perspective, in both the best- and worst-performing vintages, industrials and IT were the dominant sectors by size (accounting for about 60% of the market value at the end of the year) but the two sectors had different results. As in 2023, industrials were the main driver of the strong returns posted by the top-performing vintage (2022), while losses in this sector dampened results overall in the lowest-returning vintage (2016).

LP Cash Flows

In 2024, LP distributions ($174 billion) outpaced contributions ($143 billion), a reversal from the prior two years. Distributions rose 37% from 2023 and represented the second highest annual total ever, while capital calls decreased for the third straight year, reflecting the industry’s slower investment pace since 2021 (Figure 3). Despite the increase in capital distributed to LPs, the distribution yield—calculated by dividing the distributions by the NAV—remained low for the third consecutive year.

Four vintage years (2021–24) represented 84% ($121 billion) of the capital calls, with each drawing down at least $17 billion during the year; the 2022 vintage called $41 billion, the most of the four. Eight vintages (2014–21) accounted for 83% of the distributions, with amounts ranging from roughly $10 billion (2020 vintage) to nearly $30 billion (2019 vintage).

Sectors

Figure 4 shows the Global Industry Classification Standard (GICS®) sector breakdown by market value of the PE index and a public market counterpart, the Russell 2000® Index. The comparison provides context when comparing the performance of the two indexes. The PE index continued to have a significant overweight to IT and meaningful underweights to financials, energy, and real estate (the latter two are reflected in the “other” category).

As of December 2024, there were six key sectors by size and combined they represented 90% of the index’s market value; IT was by far the largest (36% of the index’s market value). Two of the six large sectors earned double-digit returns for the year (financials and industrials) and among all six, calendar year returns ranged from 4.9% for healthcare to 12.1% for financials.

Three sectors garnered about two-thirds of the capital invested by US PE managers in 2024—IT (31%), industrials (19%), and healthcare (17%). Over the long term, managers have allocated about 53% of their capital to those sectors. The biggest driver of the difference is the percentage of capital allocated to IT, which historically was about 23% of invested capital. Additionally, since inception of the index, consumer discretionary, communications services, and financials all garnered at least 10% of the capital invested by managers. During 2024, the three combined accounted for only 21% of activity.

US Venture Capital Performance Insights

The Cambridge Associates US VC index rebounded in 2024 following two years of negative returns in 2022 and 2023, but to some extent the industry continued to endure a challenging fundraising, investing, and exit environment. Younger vintages outperformed older ones and performance for the largest sectors (IT and healthcare) trailed that of smaller ones.

According to the National Venture Capital Association and Pitchbook, by number, US VC managers completed slightly fewer deals in 2024 than they did in 2023 (14,612 from 14,851), but when measured by value, 2024’s deals were meaningfully higher ($213 billion compared to $163 billion in 2023). Like investments, exits by number in 2024 were similar to those in 2023 (1,186 versus 1,155), but larger by value ($158 billion from $116 billion). Lost in the similarities by total number are the differences within exit types. For example, the number of public listings fell 26% (65 from 88), while the number of M&A and buyouts increased slightly. Values for M&A and public listings were both meaningfully higher in 2024 (44% higher), while the value of buyout exits was only marginally higher than in the previous year.

Vintage Years

As of December 2024, nine vintage years (2014–22) were meaningfully sized and, combined, accounted for 80% of the index’s NAV. Returns across the nine vintages ranged from 0.7% (2018) to 25.3% (2022), a wide dispersion that in part was related to when funds were raised. Those raised prior to 2020 fared much worse than those raised afterwards (Figure 5). For all but one of the large vintages (2017), performance during the second half of the year was better than that of the first half.

For the best-performing vintage (2022), all key sectors earned double-digit returns, and in the worst-performing vintage (2018), all key sectors posted negative or low single-digit results.

LP Cash Flows

US VC LP cash flows were more robust in 2024 than 2023, with capital call and distribution totals increasing by roughly 40% each. Managers called $46 billion from LPs—the second highest for any year on record—and returned $27 billion (Figure 6). Over the last three years (2022–24), managers have called 1.5x as much capital as they have distributed, reflecting the period’s lower-than-average distribution yield (distributions/NAV) for the asset class.

While four vintages (2021–24) accounted for 87% (roughly $40 billion) of the total capital called during the year, 12 vintages (2011–22) made up the same proportion of distributions. Each of the four vintages driving contributions called at least $8 billion. Among the widespread drivers of distributions, each of the 12 vintages returned between $1 billion and $3 billion, with the 2018 cohort at the high end of the range.

Sectors

Figure 7 shows the GICS® sector breakdown of the VC index by market value and a public market counterpart, the Nasdaq Composite Index. The breakdown provides context when comparing the performance of the two indexes. The chart highlights the VC index’s meaningfully higher exposures to healthcare, financials, and industrials. Both indexes are heavily tilted toward IT, and Nasdaq weightings in communication services and consumer discretionary have remained much higher than those of the VC index.

Collectively, the five meaningfully sized sectors made up 91% of the VC index. Performance among the five ranged from 2.1% for communication services to 38.8% for industrials. During the year, VC managers in the index allocated almost 80% of their invested capital to two sectors, IT (47%) and healthcare (32%). Only two other sectors, financials (5%) and industrials (6%), garnered even 5% of capital during the year. Over the long term, two key sectors—IT and healthcare—have attracted more than 70% of managers’ capital, and 2024 totals for financials and industrials were on par with long-term norms.

Figure Notes

US Private Equity and Venture Capital Index Returns
Private indexes are pooled horizon internal rates of return, net of fees, expenses, and carried interest. Returns are annualized, with the exception of returns less than one year, which are cumulative. Because the US private equity and venture capital indexes are capitalization weighted, the largest vintage years mainly drive the indexes’ performance.

Public index returns are shown as both time-weighted returns (average annual compound returns) and dollar-weighted returns (mPME). The CA Modified Public Market Equivalent replicates private investment performance under public market conditions. The public index’s shares are purchased and sold according to the private fund cash flow schedule, with distributions calculated in the same proportion as the private fund, and mPME net asset value is a function of mPME cash flows and public index returns.

Vintage Year Returns
Vintage year fund-level returns are net of fees, expenses, and carried interest.

Sector Returns
Industry-specific gross company-level returns are before fees, expenses, and carried interest.

GICS® Sector Comparisons
The Global Industry Classification Standard (GICS®) was developed by and is the exclusive property and a service mark of MSCI Inc. and S&P Global Market Intelligence LLC and is licensed for use by Cambridge Associates LLC.

About the Cambridge Associates LLC Indexes
Cambridge Associates derives its US private equity benchmark from the financial information contained in its proprietary database of private equity funds. As of December 31, 2024, the database included 1,661 US buyout and growth equity funds formed from 1983 to 2024, with a total value of $1.6 trillion. Ten years earlier, as of December 31, 2014, the index included 958 funds whose total value was $515 billion.

Cambridge Associates derives its US venture capital benchmark from the financial information contained in its proprietary database of venture capital funds. As of December 31, 2024, the database comprised 2,625 US venture capital funds formed from 1981 to 2024, with a value of $536 billion. Ten years prior, as of December 31, 2014, the index included 1,547 funds whose value was $173 billion.

The pooled returns represent the net end-to-end rates of return calculated on the aggregate of all cash flows and market values as reported to Cambridge Associates by the funds’ general partners in their quarterly and annual audited financial reports. These returns are net of management fees, expenses, and performance fees that take the form of a carried interest.

About the Public Indexes
The Nasdaq Composite Index is a broad-based index that measures all securities (more than 3,000) listed on the Nasdaq Stock Market. The Nasdaq Composite is calculated under a market capitalization–weighted methodology. The Russell 2000® Index includes the smallest 2,000 companies of the Russell 3000® Index (which is composed of the largest 3,000 companies by market capitalization). The Standard & Poor’s 500 Composite Stock Price Index is a capitalization-weighted index of 500 stocks intended to be a representative sample of leading companies in leading industries within the US economy. Stocks in the index are chosen for market size, liquidity, and industry group representation.

Footnotes

1. The situation is somewhat flipped in China, where access to the most advanced chips remains a constraint, while electricity is more available. Notably, China controls refinement of most critical material, such as rare earths.
2. For example, SpaceX is expected to raise less than 5% of a targeted $1.75 trillion market cap.
3. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
4. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.
5. Cambridge Associates’ mPME calculation is a private-to-public comparison that seeks to replicate private investment performance under public market conditions.

The post US PE/VC Benchmark Commentary: Calendar Year 2024 appeared first on Cambridge Associates.