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.

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.

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.

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. ¹ 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. ² 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. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
2. 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. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
2. 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. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
2. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.
3. 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.

The Productivity Puzzle

For much of the postwar era, rising productivity fueled economic expansion. However, since the 2000s, productivity growth has been notably weak across many economies. While the causes of this slowdown are complex and debated, the primary factors include the waning impact of the IT and internet revolution, weak investment and slow diffusion of innovation across firms, and demographic headwinds—particularly aging populations and slower growth in the working-age labor force, which can dampen economic dynamism and slow the adoption of new technologies. Although these are the most significant contributors, other factors, such as regulatory barriers and measurement challenges, have likely also played a role.

Amid these headwinds, AI presents a new avenue for boosting productivity. As highlighted in the first piece in this series, AI adoption rates have matched, or even surpassed, those of previous major technology cycles, underscoring the speed and scale of its integration into the economy. Unlike earlier waves of technological change, AI’s capabilities extend well beyond simple automation, enabling innovation in areas such as data extraction, research synthesis, and complex problem solving. Early evidence from industries like finance, logistics, and healthcare suggests that AI-driven tools are already delivering measurable efficiency gains, though it will likely be at least a couple of years before integration is widespread enough to meaningfully improve productivity growth at the economy-wide level.

These advances, however, are not without challenges. As AI automates a growing range of tasks, concerns about potential job displacement—particularly in routine or highly automatable roles—have come to the fore. While new opportunities are likely to emerge as AI creates demand for new skills and industries, the transition may be disruptive for certain segments of the workforce, highlighting the importance of thoughtful policy responses and workforce reskilling initiatives to ensure broad-based benefits. Against this backdrop, some of the most visible applications of large language models (LLMs) today include:

• Customer Service Chatbots: LLMs power conversational agents that handle customer inquiries, troubleshoot issues, and provide support across digital platforms, reducing wait times and freeing up human agents for more complex tasks.
• Content Generation and Copywriting: Businesses use LLMs to draft and optimize marketing copy, blog posts, and product descriptions, streamlining content creation and enabling rapid experimentation.
• Coding Assistance: LLMs assist software developers by generating code snippets, suggesting improvements, and automating routine coding tasks, accelerating development cycles.
• Document Summarization and Search: LLMs extract key information, summarize lengthy documents, and answer user questions, transforming legal research, contract review, and knowledge management.
• Language Translation and Text Correction: LLMs provide real-time translation and advanced grammar correction, enhancing communication and breaking down language barriers.

The Market’s Reaction

The promise of AI has ignited a surge of investment, with capital flowing into infrastructure, model development, and a wide range of applications. Large US technology companies are leading the way, committing record sums to data centers, specialized hardware, cloud platforms, and the research needed to build increasingly sophisticated models. These investments are essential to support the computational demands of modern AI and enable new applications across industries. The scale of these commitments reflects both the strategic importance of AI and the intense competition for leadership in the next wave of technological innovation. As models become more complex and data-hungry, robust infrastructure and ongoing model development have become defining features of this investment cycle.

This wave of investment is not limited to major technology firms. Venture capital (VC) activity in AI and machine learning (ML) has also reached unprecedented levels. In 2024, VC deal-level investment in AI and ML totaled $143 billion, a dramatic increase from just $59 billion in 2019. This surge is not only a function of larger deal sizes but also a growing number of startups and scale-ups focused on AI-driven solutions across industries. The share of VC dollars allocated to AI and ML deals has risen sharply, from 15% in 2019 to 37% in 2024, underscoring the sector’s growing prominence within the broader innovation landscape. Investors are increasingly viewing AI as a foundational technology with the potential to reshape entire industries, driving a virtuous cycle of capital deployment and technological advancement.

The competitive dynamics of the VC market are also evident in deal terms. Over the past five years, both the median capital investment and median pre-money valuation for AI and ML deals have risen, reflecting heightened investor enthusiasm and the perceived value of AI-driven business models. Notably, these metrics have increased in a comparable manner for all VC deals, suggesting that while AI and ML are attracting premium valuations, the broader VC market has also become more capital-intensive. This environment has enabled AI startups to access the resources needed to scale rapidly, invest in talent, and accelerate product development, further fueling the sector’s momentum.

Geographically, the distribution of AI and ML investment has shifted significantly in recent years. According to PitchBook data, Asia—once a rising destination for VC capital in these fields—saw its share drop to just 11% in 2024, while the United States accounted for a commanding 73%. This change reflects concerns over Chinese state involvement in technology and the impact of Western regulations restricting capital flows into sensitive sectors. As a result, the United States has solidified its role as the global investment destination for AI innovation. However, it is important to note that PitchBook’s data may underrepresent the full scope of Chinese activity, as it is often more comprehensive for fund-based VC investments and may not fully capture direct investments by companies or government-backed initiatives in China. The recent release of advanced Chinese models, such as DeepSeek, underscores that China remains a formidable force in AI research and development, and leadership in the field remains contested.

While recent market attention has centered on tariffs and trade tensions, it is AI innovation and its integration into the economy that may ultimately prove far more transformative in the years ahead. Unprecedented investment by leading technology firms, together with strong VC interest in AI startups, is fueling rapid technological advancement and shaping the next wave of economic growth. While some observers have noted elevated valuations and questioned the durability of current trends, the underlying drivers—namely, the promise of productivity gains and the transformative potential of AI—suggest that investment momentum will persist, even if widespread productivity improvements take time to materialize. In the final piece of this series, we will examine how AI’s transformative potential is reshaping asset allocation opportunities across both private and public markets.

Graham Landrith and Mark Sintetos also contributed to this publication.

Footnotes

1. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
2. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.
3. Cambridge Associates’ mPME calculation is a private-to-public comparison that seeks to replicate private investment performance under public market conditions.

The post Navigating the AI Revolution: Unlocking Productivity with AI Investment appeared first on Cambridge Associates.

Investment Implications Through The Tech Cycle

To navigate the AI investment landscape, it is helpful to segment the market into five archetypes that capture the diverse ways in which companies interact with AI:

1. Creators are the pioneers at the frontier of AI innovation—companies developing foundational models, advanced algorithms, the software development toolchain, and specialized hardware that form the core of the technology.
2. Disruptors create a transformative change that goes beyond integrating technology into an existing process, launching new business models that were unimaginable prior to the technological leap (e.g., Uber or Amazon of the internet era).
3. Enablers provide the essential physical infrastructure that makes AI possible, including semiconductors, data centers, and energy solutions.
4. Adaptors are businesses that integrate AI into their operations, harnessing its power to drive efficiency, unlock new business models, expand their market share, and maintain competitive advantage.
5. Finally, the Disrupted are incumbents whose market share or relevance is threatened by the rise of AI-powered competitors.

Each of these archetypes presents distinct investment opportunities and risks across asset classes.

As discussed in Part 1, where we highlighted past technology cycles, this framework echoes the dynamics of the internet era that launched the information age. During that period, Apple, Google, and Microsoft were among the creators, building the platforms and software that defined the new economy. Amazon emerged as a disrupter, fundamentally changing the retail landscape. With the emergence of cloud computing, software-defined infrastructure was developed to manage or enable compute, storage, and networking through software. Companies like Intel and Cisco served as enablers, providing the chips and networking equipment that powered the digital revolution. Today, as AI ushers in another wave of transformation, understanding where companies sit within this cycle is essential for identifying both risks and opportunities across the investment landscape.

Creators and Disruptors

Venture capital (VC) remains a crucial funding source for innovative start-ups engaged in high-risk research and product development. This dynamic drove previous technology waves, such as the internet, mobile, and cloud computing. However, the AI era presents a different landscape. Unlike the cloud era—where established companies were slow to adapt and start-ups captured early gains—many incumbents are now early AI leaders. These companies are cloud-native and deeply integrated into corporate systems. They leverage their scale and distribution to build AI capabilities internally or accelerate innovation by acquiring or investing in VC-backed AI start-ups. Notable examples include Google’s acquisition of DeepMind (which powered Google Brain and Gemini), Microsoft’s early partnership with OpenAI, and Amazon’s partnership with Anthropic. Hyperscalers’ capital expenditures have been extraordinary and are expected to continue as AI technology advances. Key areas of VC investment include large language models (LLMs), supporting software infrastructure, and “applied AI” applications built on this foundation.

As outlined in Part 2, VC investment in AI has reached record highs, with intense enthusiasm and abundant capital pursuing a limited number of high-quality start-ups. Adoption rates have surged across many companies (see Part 1), but much of the early revenue is “experimental,” reflecting trial phases rather than sustainable businesses. This momentum has spurred a wave of new company formations and AI strategy announcements, creating significant “AI noise” in the market. Interest is also growing in “physical AI,” where AI intersects with industries such as manufacturing, construction, healthcare, and aerospace and defense. However, all this frenzy has led to inflated valuations, intense competition, and overfunded segments given its relative infancy. Although AI-first companies have seen rapid revenue growth, its durability is uncertain due to the experimental nature of adoption and the lack of strong competitive moats—even companies with $50 million–$100 million in revenue can be overtaken whereas in prior cycles that typically signaled victory. While a few leaders have already created significant value, many AI start-ups are likely to fail due to oversaturation, poor management, and rapid sector evolution.

Historically, major technology shifts often result in commoditization, and it is rarely clear at the onset which companies will ultimately succeed. The winners are typically those that either build on existing technology through innovation or leapfrog older products and services entirely. For instance, Dell Technologies initially dominated the PC market, EMC led in on-premises enterprise data storage before the transition to cloud solutions, and Cisco was the leader in network hardware before the rise of software-defined networking. AI is likely to follow similar patterns, with rapid change and innovation making it difficult to identify long-term leaders. As open-source competition and verticalized alternatives have driven SaaS commoditization, so too will these forces and the broader open-source community drive further innovation and disruption in AI. Despite these uncertainties, we expect long-term VC returns in AI to remain attractive.

Who will be the winning investors? We recommend diversifying across the AI value chain and managing risks through careful position sizing. Investors should prioritize general partners (GPs) with deep sector expertise, particularly at the foundational and network infrastructure levels, and a proven track record of business building. This expertise—whether within specialist or generalist firms—enables better deal flow, talent identification, and assessment of technical merit. Select specialists for investments where technology risk is high, and generalists for broader investment strategies, leveraging the strengths of both. As AI becomes more widespread and many start-ups incorporate it into their products, investment decisions will increasingly focus on how AI is applied rather than on the technology itself. This trend mirrors previous technology cycles, where, as markets matured, investment success depended more on careful selection and curation than on technical expertise. Many GPs focused on AI are relatively new and still gaining investment experience, given the technology’s rapid rise in prominence. Large generalist firms have captured many early AI successes, often partnering with specialists to combine strengths. These generalists offer larger capital pools, enabling them to support AI start-ups through multiple funding rounds, provide customer access, and offer business-building expertise. Their broad go-to-market and business development capabilities help start-ups as they scale.

Enablers

Enablers are the backbone of the AI revolution, providing the physical infrastructure that supports AI’s rapid expansion. The primary beneficiaries to date have been semiconductor manufacturers (especially those producing AI chips), hyperscale data center operators, and the power and utility companies that support this ecosystem. However, the scale and speed of investment in these areas have raised concerns about sustainability, valuations, and the risk of overbuilding—reminiscent of the internet era’s fiber optic boom and bust.

The rise of generative AI and LLMs has driven unprecedented demand for high-performance chips, particularly GPUs and custom AI accelerators. Companies like Nvidia, AMD, and emerging players such as Cerebras have seen orders and backlogs soar. Supply constraints and technological leadership have enabled leading chipmakers to command premium pricing and margins. Dominant players, especially Nvidia (through its CUDA platform), are building integrated hardware-software ecosystems, creating high switching costs and network effects, but also raising antitrust concerns. Valuations remain high, with Nvidia trading at a forward price-to-earnings (P/E) ratio of 32.3, as of June 30, 2025. While this is below 2024 peaks, it remains vulnerable to correction if AI adoption slows, or competition intensifies. As such, consider modest tilts away from expensive public equity mega-cap tech stocks to reduce valuation risk and enhance portfolio diversification.

Data centers are also major beneficiaries, driven by AI, ongoing cloud adoption, and rising data usage. McKinsey estimates data center capacity demand will grow at an annual rate of about 20% through 2030, with generative AI data centers accounting for a small, but growing share of new demand. Investors should partner with infrastructure and real estate managers with specialized development and operating expertise that are well-positioned to benefit from this supply/demand imbalance. However, transaction multiples have risen materially, averaging 25x EBITDA over the last four years according to Infralogic, compared to a 13.5x average for private infrastructure more broadly. This makes careful underwriting essential for attractive returns. Like other AI infrastructure assets, data centers face risk of overbuilding, as well as regulatory and environmental concerns and constraints such as local opposition and permitting delays. These risks can be mitigated by focusing on managers who can develop assets at lower multiples (e.g., low double-digit EBITDA) and sell into a strong market, often with long-term contracts from investment-grade hyperscalers (e.g., Microsoft, Amazon) seeking development partners. In contrast, speculative and remotely located data centers with more limited utility face heightened risks. From a portfolio construction perspective, data centers offer lower expected returns than private investments in innovative AI firms but can provide returns competitive with broad equities (e.g., 15%–20% target gross IRR) with diversification benefits.

Other enablers, such as utilities and grid infrastructure, have also seen increased demand and capital inflows driven by electrification and digitization trends. McKinsey expects global data center capacity demand between 2025 and 2030 to drive investment in power (including generation and transmission) to total between $200 billion (constrained momentum) to $600 billion dollars (accelerated demand), with $300 billion as their baseline for continued momentum. US on-grid electricity demand is expected to increase 2%–3% per year through 2030 up from virtually flat growth over the last decade, with faster growth in Asia (from a lower base) and slower growth in Europe. While difficult to estimate, rapid AI adoption and potential onshoring in the United States could further boost energy demand. Although AI energy efficiency is expected to improve, associated cost reductions may spur broader adoption, likely resulting in net energy demand growth. Investment in essential electricity infrastructure with inelastic demand is critical. Data centers require reliable power, necessitating redundant infrastructure such as back-up generators and batteries.

All enabler segments have strong growth potential, with chips and data centers experiencing the fastest expansion, but they also trade at heightened valuations and have the greatest exposure to overbuilding. Scale, technological edge, strong customer relationships, and specialized expertise are critical for managing these risks.

Adaptors and the Disrupted

Building on the productivity themes from Part 2, growth equity and private equity-backed companies are increasingly using AI to boost revenue and improve margins. As private entities, they have more flexibility to integrate and scale AI across operations, though successful implementation requires careful execution. While many companies are still experimenting, some are already seeing early benefits in product enhancements and margin gains.

Private equity investors are actively assessing both the opportunities and risks AI brings to their portfolio companies and industries. They look for cost savings through automation (e.g., customer support, onboarding, coding) and revenue growth from AI-driven products (e.g., sales planning, demand forecasting). At the same time, they remain cautious about risks, such as commoditization (e.g., graphic design, digital marketing) and increased competition from low-cost automation (e.g., auditing, document preparation, call centers). Technology-focused managers have an edge due to sector expertise, but both specialist and generalist firms are hiring AI talent to support investment teams and portfolios. The full impact of AI will unfold over time as new use cases and broader adoption and understanding of AI technologies and their impact continue to emerge.

Similarly, public companies must adapt to AI or risk disruption. Investors should focus on active management to distinguish winners from losers and to assess price risk, selecting managers with deep sector expertise. Employ long/short and fundamental strategies to manage risk and exploit valuation dislocations. Public investors face the challenge of avoiding overvalued AI leaders while not overlooking lower-priced companies that may lag behind. Many leading public companies are cloud-native and well-positioned for AI, but investors should consider the entire spectrum of innovators and disruptors. Public market valuations for AI-enabled companies have dropped from their late 2021 peak; forward P/E ratios relative to the S&P 500 Index hit a nine-year low earlier this year, and have since rebounded, but remain below recent historical spikes. This environment favors long/short managers that can identify mispriced companies amid the current AI hype.

As outlined in Part 1, we recognize that non-technological factors—particularly regulatory and policy uncertainty—are increasingly shaping both the AI investment landscape and broader societal outcomes. The concept of Responsible AI (RAI) is gaining more attention as generative AI models and systems grow in complexity and become more deeply embedded across industries. RAI frameworks address the development and deployment of LLMs and broader AI applications, emphasizing principles such as fairness, transparency and explainability, accountability, privacy, safety, and security. From an investment perspective, effective governance is inherently complex, intersecting regulatory, ethical, technological, and human considerations. This complexity necessitates cross-disciplinary collaboration and often involves navigating trade-offs and misaligned incentives. As AI adoption accelerates, reported incidents of ethical misuse have increased in recent years. A recent survey found that only 14% of businesses have dedicated AI governance roles, yet 42% reported improved operations and 34% noted increased customer trust due to RAI policies and investments. ⁴ Companies should proactively assess, and address financially material risks associated with neglecting RAI practices, such as regulatory actions or erosion of their societal license to operate, which could result in negative commercial consequences. Governments worldwide are trying to address complex issues like data privacy, algorithmic transparency, antitrust, and national security, and new regulations could significantly impact sector competition. Investors must also monitor regulatory developments closely, as evolving rules and policies will likely influence long-term value creation and competitive differentiation in the rapidly evolving AI sector.

The “AI noise” phenomenon extends beyond private investments. Most technology companies now market themselves as AI-focused, and those that do not, risk appearing outdated. Enterprise software incumbents with high switching costs, complex technology, and strong innovation pipelines may continue to thrive, while agile start-ups can exploit weaknesses and expand from niche solutions into strategic adjacencies, potentially displacing incumbents. For example, it is unclear whether established security firms will lead in AI security or whether nimble start-ups will secure the AI/ML software supply chain. ServiceNow, a leading enterprise software provider, has thus far demonstrated successful AI adoption by leveraging its integrated suite and existing customer base to pivot toward AI-driven solutions. Given the rapid pace of change, both long-only and long/short hedge funds can find alpha by capitalizing on short-term disruptions and mispriced companies. Valuation-based and fundamental short strategies remain relevant, though it can be difficult to short declining businesses that retain temporary relevance or to identify companies prematurely dismissed as AI losers. Investors should consider managers with crossover expertise—spanning both public and private markets—as they are well-positioned to capitalize on rapidly evolving AI developments by spotting trends in private markets before they are reflected in public market valuations, and can continue to invest post IPO.

AI-related risks and opportunities are increasingly influencing credit markets. Credit managers are financing core infrastructure—such as GPUs, data centers, and energy projects—while also supporting the broader AI ecosystem. Several large managers are establishing dedicated asset-backed finance teams and raising capital specifically to pursue these opportunities. Direct lenders, in particular, have significant exposure to technology and business services, which will need to adapt in response to AI advancements.

More broadly, credit managers must evaluate the adaptability of their portfolio holdings. Many software companies—particularly those with high leverage and business models vulnerable to AI automation (e.g., HR, legal, accounting, and other back-office SaaS providers)—face considerable disruption risk. The past decade’s low-rate environment led to aggressive leverage and high valuations, leaving some companies with thin interest coverage and little margin for error. These firms are especially vulnerable if AI-driven disruption erodes their revenue base. Should AI agents automate or disintermediate core functions, revenue models may be cannibalized, and even modest declines in topline revenue could threaten debt service capacity.

Some credit managers are proactively encouraging portfolio companies to adopt AI, aiming to drive efficiencies and mitigate disruption risk. Lenders are increasingly evaluating management’s AI strategy as part of their underwriting process. Companies that successfully integrate AI may improve margins and creditworthiness, while laggards risk being left behind. As disruption accelerates, a wave of distressed opportunities may emerge among over-levered incumbents unable to adapt to AI-driven change. However, the timing of this transition is highly uncertain: some companies may be “slow melting ice cubes,” experiencing gradual market decline, while others may yet adapt successfully.

Investors should select credit managers who proactively assess AI-related opportunities and risks, including overbuilding in data centers and other infrastructure, while proactively managing exposure to incumbents in sectors vulnerable to AI disruption, such as highly leveraged back-office SaaS providers. Credit opportunity managers may be best positioned to benefit from distressed cycles arising from AI-driven disruption, as these managers can capitalize on market dislocations.

Investors should question managers on their approach to AI, both in terms of portfolio company adaptation and exposure to AI-related risks and opportunities, as part of ongoing due diligence.

Conclusion

AI is fundamentally reshaping the investment landscape, presenting both extraordinary opportunities and new risks across asset classes. The technology’s reach extends from the innovators building core capabilities, to the enablers providing critical infrastructure, to the adaptors and disrupted incumbents navigating a rapidly changing environment. Although substantial investment has already driven rapid growth in AI and its supporting infrastructure, we remain in the early stages of this technological shift, which is expected to evolve over the next decade and beyond. In previous technology cycles, the initial investments and returns from foundational innovation were ultimately surpassed by the gains generated by disruptive companies. These disruptors leverage the established or rebuilt technology infrastructure and benefit from network effects as commercial adoption accelerates, enabling them to redefine industries or create entirely new markets and business models. Attractively valued companies that can leverage AI to improve their profitability should also benefit meaningfully.

Investors should strategically seek opportunities to incorporate AI Creators, Disruptors, Enablers, and Adaptors within their portfolios, all the while maintaining a careful watch on potential disruption risks and the possibility of inflated valuations and overbuilding. Investment success in this new era will require investors to combine deep sector expertise, rigorous due diligence, and a willingness to adapt as the technology and its applications evolve. Investors that partner with managers that can distinguish between hype and enduring value, anticipate regulatory shifts, and identify the true drivers of sustainable growth will be best positioned to capture the far-reaching potential of AI in shaping asset allocation for years to come.

Grayson Kirk, Graham Landrith, and Archie Levis also contributed to this publication.

Footnotes

1. According to third quarter 2025 Pitchbook data, an average 5,997 seed and pre-seed deals were completed each year between 2022 and 2024.
2. The Rule of 40 is defined as the LTM revenue growth rate plus the LTM EBITDA margin.
3. Cambridge Associates’ mPME calculation is a private-to-public comparison that seeks to replicate private investment performance under public market conditions.
4. Nestor Maslej, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Njenga Kariuki, Emily Capstick, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, Tobi Walsh, Armin Hamrah, Lapo Santarlasci, Julia Betts Lotufo, Alexandra Rome, Andrew Shi, Sukrut Oak. “The AI Index 2025 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2025 and McKinsey & Company survey 2024.

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