J.P. Morgan Sees $5 Trillion AI Opportunity Shifting Toward Private Markets

J.P. Morgan, the global leader in financial services sees a $3 trillion to $5 trillion opportunity emerging from the next phase of artificial intelligence, arguing that private markets could capture a significant share as investment shifts from foundational models and computing infrastructure toward AI software that automates labor-intensive business services.

The bank calls this third phase of AI development “services as software,” in which functions traditionally performed through human labor — including finance, human resources and customer support — increasingly move onto intelligent software platforms. The thesis could broaden the AI private-market opportunity beyond venture-backed model developers and data centers into vertical software, agentic AI, growth equity and technology-focused buyouts.

AI Investment Moves Beyond Chips and Data Centers

J.P. Morgan divides the development of generative AI into three investment phases.

The first centered on large language models. The second shifted capital toward the semiconductor manufacturers, hyperscale technology companies, data centers and other infrastructure required to train and operate those models.

The emerging phase is more closely tied to applying AI to existing economic activity.

According to the bank’s private-market AI investment thesis, applications are already moving into automated financial underwriting and fraud detection, healthcare diagnostics and drug discovery, predictive industrial maintenance and supply-chain management.

That distinction matters for private capital. Infrastructure investment requires enormous pools of capital, but much of the application layer remains concentrated among privately held companies that can be financed through venture capital, growth equity and eventually private equity.

J.P. Morgan said about 95% of software companies were privately held as of March 2025. It also pointed to companies remaining private for longer: the median company going public was almost 14 years old, compared with less than 11 years a decade earlier.

The extended private-company lifecycle gives alternative managers more time to participate in value creation before businesses reach public markets.

PE NEWSWIRE has already tracked the institutional-capital side of the AI buildout through CPP Investments’ $1.75 billion commitment to EQT’s AI data center expansion. J.P. Morgan’s thesis suggests the next allocation question may increasingly concern the applications running on that infrastructure rather than only the infrastructure itself.

Agentic AI Creates a Venture Capital Opportunity

One of J.P. Morgan’s highest-conviction areas is agentic AI — autonomous systems capable of planning, reasoning and executing tasks with limited human involvement.

Rather than simply generating an answer to a prompt, an AI agent can potentially complete a sequence of actions across a workflow. Applications could include finance, legal services, healthcare, customer support and supply-chain management.

J.P. Morgan cites an estimate that more than half of supply-chain tasks could be performed by AI agents by 2030, including demand forecasting, supplier selection and route optimization.

The investment characteristics of agentic AI make venture capital a natural source of financing, according to the bank. Many companies remain experimental, require lengthy research and development cycles and carry significant product and execution risk.

That combination favors investors capable of tolerating failure rates in exchange for potentially outsized returns from companies that establish defensible platforms.

For venture managers, however, identifying durable businesses may become more difficult as the cost and speed of software development fall. The ability to build an AI application quickly does not necessarily create a sustainable competitive advantage.

Proprietary data, distribution, integration into critical workflows and customer retention are therefore likely to become increasingly important parts of underwriting.

Vertical AI Could Attract Venture and Growth Capital

Vertical AI represents another part of the opportunity.

These companies build applications for particular industries, combining artificial intelligence with proprietary datasets and specialized domain knowledge.

Healthcare is one example. J.P. Morgan cited research indicating that AI could potentially cut drug-development timelines in half by improving productivity from discovery through clinical trials and regulatory processes.

The private-market financing path for these businesses can evolve as companies mature.

Venture capital provides financing while products and markets are being established. Growth equity becomes more relevant when businesses have demonstrated demand but require capital and operational support to expand distribution, professionalize management and enter additional markets.

That progression is important for alternative investment managers because it expands the AI opportunity across multiple stages rather than confining it to early-stage technology funds.

The same trend is visible in cybersecurity, where PE NEWSWIRE reported that AI-focused startups helped keep cybersecurity venture investment near $5 billion in the first quarter of 2026 even as deal counts fell, demonstrating how capital can concentrate around a smaller group of perceived category leaders.

Buyout Firms Could Target Established Software Platforms

J.P. Morgan’s thesis also extends beyond venture capital.

Horizontal software — platforms used across industries for functions such as customer relationship management, collaboration, payroll, financial reporting and marketing — creates a potentially different opportunity for growth-equity and buyout managers.

Many of these companies already have established revenue bases and customer relationships. AI can be incorporated into existing products to automate analysis, enable natural-language interaction, generate recommendations and process data more efficiently.

For private equity investors, that creates both opportunity and disruption risk.

An established software company that successfully incorporates AI may improve customer retention, productivity and margins. A portfolio company that fails to adapt could instead lose market share to AI-native competitors capable of delivering the same function more efficiently.

That means AI increasingly becomes a value-creation and due-diligence issue across existing technology portfolios, rather than simply a standalone sector allocation.

Buyout managers assessing software businesses will need to determine whether AI strengthens the company’s competitive position or threatens the economics that historically justified its valuation.

Industrial AI Extends the Theme Into Physical Assets

J.P. Morgan also connects artificial intelligence with U.S. reindustrialization.

The bank expects industrial companies to allocate 25% to 30% of capital expenditure to automation over the next five years, compared with 15% to 20% during the preceding five-year period. It also cited estimates that the global industrial robotics market could reach approximately $60 billion over the coming decade.

The opportunity reflects several overlapping trends: aging factories, reshoring, geopolitical uncertainty and the need to modernize physical and digital infrastructure.

J.P. Morgan noted that the average U.S. factory is more than 40 years old, while many legacy data centers are 15 to 20 years old and were not designed for the power density and cooling requirements of modern AI computing. U.S. manufacturing construction spending had also more than tripled from 2021 by the time of the bank’s analysis.

For private capital, this widens AI exposure beyond software.

Infrastructure funds can finance data centers and power systems. Private equity can invest in industrial automation and technology-enabled manufacturers. Venture and growth funds can back robotics and specialized software, while private credit can provide financing for capital-intensive expansion.

AI Deal Value Has Accelerated

The capital flowing into the sector was already accelerating when J.P. Morgan published its analysis in August 2025.

Private-market AI dealmaking exceeded $140 billion in 2024, compared with $25 billion a year earlier, according to PitchBook data cited by the bank. Software had represented roughly 40% of private-market deal volume since 2015 and approached 50% in early 2025.

J.P. Morgan also identified improving conditions in venture capital following the correction triggered by higher interest rates in 2022.

Venture distributions were beginning to recover for the first time since 2021, according to the analysis, while buyouts had overtaken IPOs as the dominant U.S. venture exit route. M&A and secondary transactions were providing additional liquidity channels.

Those exit routes are important for limited partners after several years in which weak distributions constrained their ability to recycle capital into new funds.

AI could therefore affect private markets from both sides of the equation: attracting new investment while potentially generating acquisitions and exits that return capital to LPs.

The $3 Trillion-$5 Trillion Estimate Is an Opportunity, Not a Forecast of Returns

The size of J.P. Morgan’s estimated opportunity should not be interpreted as an expectation that private-market investors will capture $3 trillion to $5 trillion of investment profits.

The figure describes the potential economic opportunity associated with the “services as software” transition, based on research cited by the bank from Vista Equity Partners and Bain & Co.

Competition, valuation and technological obsolescence remain significant risks.

AI companies can grow quickly, but rapid technological change can also erode competitive advantages. Businesses financed at aggressive revenue multiples could deliver disappointing investment returns even if their underlying markets expand substantially.

The bank therefore emphasizes diversification and manager selection rather than treating AI as a uniform investment category.

That distinction is particularly relevant for institutional investors. The private-market opportunity spans fundamentally different risk profiles — from early-stage agentic AI companies with uncertain product-market fit to mature software businesses and capital-intensive infrastructure assets with contracted revenues.

Private Markets Become the Battleground for AI’s Application Layer

The most important implication of J.P. Morgan’s thesis is the potential migration of AI value creation.

The initial public-market beneficiaries were concentrated among semiconductor manufacturers and the largest technology companies capable of financing enormous computing infrastructure. The next phase could distribute value across thousands of businesses applying AI to specific industries and workflows.

Many of those companies are likely to remain private through crucial stages of their development.

That creates opportunities for venture capital, growth equity and private equity, but it also raises the importance of manager specialization. Evaluating a data center is fundamentally different from underwriting an early-stage AI agent or determining whether an established software company’s margins can survive AI-driven competition.

For private-market investors, the question is therefore shifting from whether AI will attract capital to where within the AI value chain risk-adjusted returns can still be captured.

If J.P. Morgan’s “services as software” thesis proves correct, the next major private-market AI opportunity may be less about owning the infrastructure that makes artificial intelligence possible and more about financing companies that use it to replace, automate or fundamentally redesign existing business services.