Private equity investors in 2026 will increasingly look to mature industries for outsized returns, according to a new cross-sector outlook from PitchBook's PE sector research team.

The analysts see 2026 defined by AI adoption, data center growth, demographic shifts and geopolitical risk.

To bring those insights into sharper focus, PitchBook analysts were asked a common set of forward-looking questions: Which subsectors would they back first in a new fund? Where is competition overheating? Which struggling areas may offer attractive valuation entry points? And where will mega-themes, from reshoring to aging demographics to AI, create the biggest winners and losers in 2026?

 

In aerospace & defense, the sweet spot is shifting from pricey MRO platforms to commercial aircraft parts and defense electronics. Aging fleets and constrained OEM production mean parts are needed to service older planes, even as rising build rates pull through more components. On the defense side, electronics and AI-enabled systems should capture a disproportionate share of expanding military budgets.

From there, the full report widens out across nine mature industries, each offering its own twist on value creation opportunities and emerging risks. Construction & engineering will benefit from the "power, cooling and data" boom, while consumer bright spots include premium goods and outdoor recreation. In healthcare, outpatient care models and AI-enabled workflows are shifting industry economics, and cost-management platforms are gaining momentum to combat margin pressures.

The outlook also spans medtech, where aging populations and advanced diagnostics present structurally rising demand; software, where sticky enterprise systems continue to dominate PE attention; transportation & logistics, where autonomous trucking and tariff-driven supply chain redesign are setting up major dislocations; and food & beverage CPG, where functional drinks, better-for-you snacks and AI-enhanced forecasting are redefining growth strategies.

This new outlook doesn't just answer those questions, it reveals where consensus is forming, where opportunities lie, and where PE investors may want to look next. Read the full report to see how each of the nine sectors stacks up—and which subsectors could be 2026's biggest surprises.

After a few days of thinking about what to write for this newsletter, the thoughts finally coalesced for me: The way AI can supercharge PitchBook's research team, or put us at risk, is the same way AI will reshape the global economy.

If our research group doesn't innovate with AI, we risk standing still. Whereas when our analysts discuss cutting-edge AI research projects, we think we can add 10x, or even 20x, more value to clients. Make no mistake, we're pursuing the latter.

These extreme levels of opportunity and risk represent the perfect framing for our 2026 AI Outlook.

In our outlook, we asked our tech analysts to help VCs find the top AI subsectors fertile for creating the next decacorn and potentially trillion-dollar company, avoid investing in overheated competition and identify at-risk incumbents.

And they answered. Our team is positive on AI drug discovery, which could double clinical trial success rates; foundation models as they fight to specialize; agentic payments and commerce, as agents transact for us; AI for customer service & support, where industry-specific specialists will create real moats; autonomy/perception software ahead of a 30-year autonomous vehicle supercycle and more. We identify our 15 top AI subsectors and another 40-plus that we like.

 

Feel free to email me (james.ulan@pitchbook.com) for lists of companies in these subsectors.

We also see intense overheating in areas of AI including second-tier AI medical scribes; parts of AI precision medicine (genomics, biomarkers); aerial defense drones; areas of AI gaming content development; parts of code gen; certain parts of AI for marketing; some CFO stack and capital markets software; search as a service; GEO visibility and placement; drone-based crop monitoring; and capital-intensive supply chain ops.

And lastly, we know that many incumbents will cede share to the point of collapse. These categories unveil prime areas for founders to harvest rich deposits of revenue.

Incumbents at greatest at risk include big-budget content production in gaming (AI upstarts compete at a fraction of the cost); legacy ERP, accounting, capital markets software (AI-powered real-time analytics, forecasting, and workflow integration will be sticky); traditional trucking (regulations limit truck-driver hours); traditional healthcare administration (AI is excellent at processing unstructured data); and more.

And so, if we can reinvent how we conduct research with AI, we'll not only avoid backpedaling, we'll deliver sharper, faster and more actionable insight to our clients than ever before—much like the aims of today's AI startups and the incumbents they are trying to disrupt.