Investment Strategy
Jul 17, 2025
Alternative Investments
A new wave of AI-led disruption: The private market opportunity
AI's third phase: 'services as software'—a transformative shift in private market investments
Sitara Sundar, Head of Alternative Investment Strategy & Market Intelligence
Published August 8, 2025
The first phase of the AI evolution saw the emergence of the large-language models that power generative AI. In the second phase, investors focused on the hardware and infrastructure needed to run these models, bringing chipmakers, and the hyperscale tech companies that provide massive cloud and datacenter infrastructure to the fore.
We believe we are now entering the third phase of the AI evolution, characterized by the rise of a phenomenon we’re referring to as “services as a software.” In this phase, traditional business services—such as finance, human resources and customer support—are delivered through intelligent, AI-powered software platforms rather than human-led outsourcing or consulting.
It’s already happening. AI is transforming financial services through automated underwriting and fraud detection. It's reshaping healthcare with its use in diagnostics and drug discovery, and it's optimizing industrial operations through predictive maintenance and intelligent supply chain management.
Services as a software represents a $3 trillion to $5 trillion opportunity1 — and private market assets are the critical vehicles that allow investors to access it.
Let’s take a quick look at how the markets have arrived at this third phase in the AI evolution, the pillars of our investment thesis, and the private investment vehicles best suited to investing in them.
Early days
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Since the public debut of ChatGPT in November 2022, the pace of consumer AI adoption has been extremely brisk, helping the tech-heavy Nasdaq to rally more than 90%.2 But we’re particularly impressed by the growth of AI within enterprises. Currently, about 9.3% of U.S. enterprises use AI in their operations, a figure that has nearly doubled since January, 20243
Because this next phase of the AI evolution is just beginning, the opportunity set is most compelling within private companies.
- This next phase of innovation will be software-led. About 95% of software companies were private4 as of March 2025.
- The speed of innovation in AI is extraordinary, and the ultimate winners of the AI race may not yet exist. Innovation requires patient capital combined with strategic advice, and that exists primarily in the private markets.
- Companies are staying private for longer, in part given the abundance of capital in private markets. Today, the median age of a company that’s going public is almost 14 years. Ten years ago, the median age was less than 11 years.5
Investing in services as a software
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When investing in this third phase of the AI evolution, it’s important to remember that this is not just a tech story. The total addressable market for AI-related applications could surpass that of the cloud and mobile transitions, primarily because the ultimate target is reducing labor costs across industries.
Organizations are at the edge of a significant turning point in AI adoption, as models evolve from probabilistic (those that produce plausible text) to deterministic systems that can reliably think, reason, and take action. This leap in accuracy and consistency will facilitate integration into complex, industry-specific workflows, significantly expanding AI’s utility and accelerating enterprise adoption. As applications are built on top of these models, the impact across sectors is likely to be exponential – not incremental.
Here’s where we see substantial opportunity.
AI and the U.S. reindustrialization
A re-industrialization wave is underway, evidenced by a surge in capital expenditures in industrial automation. AI-driven and robotics-enabled systems stand at the forefront.
U.S. industrial companies are set to allocate 25%–30% of their capital spending to automation over the next five years, up from 15%–20% over the last five years.6. Some estimates show that the global industrial robotics market could grow at low-double digit CAGR over the next decade to reach ~$60B in market value.7
The aging of the U.S. industrial base, at the same time that companies are reshoring in the face of geopolitical uncertainty and tariff risks, makes investment both imperative and urgent. The average factory is more than 40 years old, and many legacy data centers are 15 to 20 years old, lacking the power density and cooling infrastructure needed to support modern AI workloads. On reshoring, total manufacturing construction spending in the US has more than tripled from 2021.8
Together, these factors point to a rebuild of core industrial assets—creating durable opportunities for capex-backed investment in automation, AI-enabled physical production, and modernized digital infrastructure.
Agentic AI
Agentic AI refers to autonomous systems capable of reasoning, planning, and taking actions to accomplish goals with minimal human input—essentially functioning like digital employees or co-pilots. We believe agentic AI has the potential to radically reshape workflows in knowledge-based sectors such as legal, finance, healthcare and customer service by automating complex, multi-step tasks.
Agentic AI can increase productivity, reduce labor costs, and enable new forms of intelligent software that continuously learn and adapt. As infrastructure and models mature, the next wave of value will accrue to the organizations that can productively harness this autonomy.
For example, supply chains are ripe for modernization through agentic AI. In fact, according to Gartner, over half of supply chain tasks could be taken over by AI agents by 2030. This includes areas like demand forecasting, supplier selection, and route optimization.
Agentic AI is still in an experimental and fast-evolving phase, requiring patient capital, long R&D cycles, and risk-tolerant backing, which makes these companies best-suited to venture capital.
Vertical AI software
Vertical AI software refers to purpose-built AI solutions tailored for specific industries that can unlock productivity increases by leveraging proprietary data, domain knowledge, and targeted model training.
This software is poised to capture economic value by redefining workflows, improving accuracy and speed of operations. As adoption scales, many of these platforms could reduce labor needs and enhance productivity across industries.
For example, within healthcare, early studies indicate that AI could cut drug development timelines in half (typically takes 15+ years) by improving productivity from drug discovery to clinical trials to regulatory processes.9
We believe both venture capital and growth equity managers will play a critical role in this space. They are essential for supporting early-stage innovation, especially where product-market fit and distribution are still being tested. Growth equity also plays a critical role in helping proven companies scale, professionalize and find customers, offering strong return potential while the company’s growth accelerates.
AI-enabled horizontal software
Horizontal software supports core business functions that are common across industries—such as customer relationship management, team collaboration, and financial operations. It can help sales and marketing teams track leads, manage client interactions, and automate outreach. Collaboration tools enable real-time communication and project management, reducing silos and increasing responsiveness. Financial software can streamline invoicing, payroll, and reporting, improving accuracy and reducing manual effort. By digitizing and standardizing these essential workflows, horizontal software boosts operational efficiency and enables scalable, organization-wide transformation.
The integration of AI into profitable businesses will drive stickier customer relationships by offering personalized experiences, expanding competitive advantages and increasing the potential for revenue growth. By leveraging AI, companies can enhance customer engagement and loyalty, leading to sustained business success and increased profitability.
These platforms are becoming significantly more powerful and efficient, supporting automated insights, natural language queries, intelligent recommendations, and faster data processing.
Growth equity and buyout investors provide the operational expertise, capital and strategic discipline to help AI-enabled software platforms scale efficiently.
Signs of revitalization in Venture Capital / Growth
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Acknowledging that a large part of the growth in ‘services as a software’ are accessed through private markets – particularly venture and growth, we take a look at the industry fundamentals. After the market correction experienced after the 2022 rate shock, the venture and growth landscape are showing early signs of renewed momentum.
- AI is compressing the time to profitability, with median time to $10M revenue collapsing from 10 years to just 12 months10, driving stronger unit economics and clearer profitability profiles for next‑generation companies.
- Distributions in venture capital are improving for the first time since 2021 as exit optionality broadens — buyouts now outpace IPOs as the dominant VC exit route in the U.S., M&A continues to be a consistent exit path, and the secondary market is growing.
- Sector‑specific dealmaking is surging, led by AI. Private market dealmaking related to AI exceeded $140B in 2024 (vs. $25B the year prior). Software has consistently accounted for ~40% of deal volume since 2015, peaking near 50% in early 202511.
This revitalization comes at a time where there is still capital scarcity across venture capital and growth equity, setting the stage for measured yet meaningful capital deployment against cleared paths to scale and liquidity.
Venture Capital demand/supply ratio by quarter
Venture capital is in high demand
Source: Pitchbook, 1Q25 (latest available as of June 2025).
Short-term buzz; long-term opportunity
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Throughout this next stage of AI evolution, investors must remember to stay diversified and choose the managers with a proven track record. Moreover, despite near-term enthusiasm, it’s important to remain aware of the underlying risks associated with the various pillars of investing in the next stage of AI. AI may indeed be the foundational platform of the future, but this is an opportunity that will unfold not over quarters but over years, and not all opportunities are made the same.
We can help
If you’re interested in learning more about alternative investments and the opportunity presented by AI, speak with your J.P. Morgan team.
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1Vista Equity Partners, Bain & Company, 2024.
2Bloomberg Finance, November 30, 2022 – July 16, 2025.
3Haver Analytics, Census Bureau, June 29, 2025
4Vista, Equity Partners, S&P Global Market Intelligence; S&P Capital IQ Fundamentals, March 2025.
5J.R. Ritter, “IPO Data,” 2024, University of Florida Warrington College of Business, https://site.warrington.ufl.edu/ritter/ipo-data/.
63 Ajewole, F., Kelkar, A., Moore, D., Shao, E., & Thirtha, M. (2023). Unlocking the industrial potential of robotics and automation. McKinsey & Company.
7Industrial Robotics Market Research Report, Global Market Insights, March 2025.
8U.S. Census Bureau, FRED, July 2025.
9 “Harnessing AI to Accelerate Innovation in the Biopharmaceutical Industry”, Information Technology & Innovation Foundation, November 15, 2024.
10 Coatue 2025 East Meets West Keynote Deck, June 2025
11 Pitchbook, June 2025.
Key Risks
Investment in alternative investment strategies is speculative, often involves a greater degree of risk than traditional investments including limited liquidity and limited transparency, among other factors and should only be considered by sophisticated investors with the financial capability to accept the loss of all or part of the assets devoted to such strategies.
Private credit securities may be illiquid, present significant risks, and may be sold or redeemed at more or less than the original amount invested. There may be a heightened risk that private credit issuers and counterparties will not make payments on securities, repurchase agreements or other investments. Such defaults could result in losses to the strategy. In addition, the credit quality of securities held by the strategy may be lowered if an issuer’s financial condition changes. Lower credit quality may lead to greater volatility in the price of a security and in shares of the strategy. Lower credit quality also may affect liquidity and make it difficult for the strategy to sell the security. Private credit securities may be rated in the lowest investment grade category or not rated. Such securities are considered to have speculative characteristics similar to high yield securities, and issuers of such securities are more vulnerable to changes in economic conditions than issuers of higher-grade securities.
Real estate, hedge funds, and other private investments may not be suitable for all individual investors, may present significant risks, and may be sold or redeemed at more or less than the original amount invested. Private investments are offered only by offering memoranda, which more fully describe the possible risks. There are no assurances that the stated investment objectives of any investment product will be met. Hedge funds (or funds of hedge funds): often engage in leveraging and other speculative investment practices that may increase the risk of investment loss; can be highly illiquid; are not required to provide periodic pricing or valuation information to investors; may involve complex tax structures and delays in distributing important tax information; are not subject to the same regulatory requirements as mutual funds; and often charge high fees. Further, any number of conflicts of interest may exist in the context of the management and/or operation of any hedge fund.
