VC Has Never Had More Money. The Problem Is Where It’s Going

There is no shortage of money in venture capital right now. Global startup investment reached a record $510 billion in the first half of 2026, already ahead of the $440 billion invested across all of 2025, but that headline masks just how concentrated the market has become, with an extraordinary amount of capital flowing into a relatively small group of companies, particularly in AI.

AI Deserves Capital, But Not Blind Conviction

AI deserves a meaningful share of that capital as it’s changing how companies build products, allocate resources and approach productivity, and I would be far more concerned if investors were ignoring that shift. What concerns me is when conviction in a sector starts doing the work that underwriting should be doing.

Being right about AI does not automatically make you right about an AI investment.

The Biggest Rounds Reveal Where Capital Is Concentrating

The first quarter of 2026 made that clear. OpenAI, Anthropic, xAI and Waymo collectively raised roughly $188 billion, accounting for around 65% of global venture investment during the quarter.

That tells us far more about the state of venture than the headline funding number alone. A founder running a strong cybersecurity, fintech, healthcare or enterprise software business may still be operating in a difficult fundraising environment, even while global venture investment sits at record levels.

Selectivity Is Healthy, Valuation Discipline Matters More

I do not necessarily see that selectivity as a problem. Venture capital should be selective. The risk comes when investors start interpreting the amount of money flowing into a company or sector as evidence that the investment thesis itself is sound, particularly when large rounds and rising valuations create pressure to get exposure before the opportunity appears to disappear.

I have always believed that this is exactly when price discipline matters most. A company can have exceptional technology, a large addressable market and an excellent management team and still be a poor investment if the entry valuation assumes too much of the future has already gone right.

Fear of Missing Out Is Not an Investment Thesis

The concentration of capital is understandable. Investors are navigating uncertainty around rates, geopolitics, growth and public-market valuations, and money naturally gravitates toward companies that appear capable of dominating large markets. AI makes that instinct even stronger because the potential market is enormous and the competitive landscape remains unsettled. Nobody wants to look back in five years and realize they passed on a foundational company because the valuation felt uncomfortable.

But fear of missing an opportunity is not an investment thesis. The job of an investor is to determine whether the return available at today's price adequately compensates for execution risk, competition, capital requirements and the time needed to build the business. Those fundamentals do not disappear simply because the technology is compelling.

Public Markets Are Starting to Demand AI Accountability

We are already seeing public markets apply this discipline. Alibaba recently announced plans to raise $10.2 billion through a share placement to fund AI investment, including chips, infrastructure and models, and investors immediately began asking whether spending at that scale would generate sufficient returns.

I think that is a healthy development.

The market does not need to turn against AI for investors to become more demanding about AI spending. As more capital enters the sector, companies will need to demonstrate a much clearer relationship between investment and revenue, margins, market share and ultimately enterprise value.

Private markets should be applying the same standard.

The Next AI Opportunities May Be Outside the Biggest AI Companies

Some of the strongest opportunities created by AI may sit outside the companies raising the largest amounts of capital. Infrastructure, cybersecurity, data management, energy, robotics, vertical software and specialized applications can all benefit as AI moves deeper into the economy, particularly where the technology solves an expensive and measurable business problem.

When I look at these companies, I want to understand what the technology actually changes economically. Does it reduce costs? Improve margins? Increase output? Allow a company to serve customers faster or operate with fewer resources?

I also want to know what remains defensible as models improve and access to AI becomes cheaper. If another company can reproduce most of the product using the same underlying technology, then there needs to be another source of advantage, whether that is proprietary data, distribution, customer relationships, workflow integration or network effects.

Abundant Capital Should Mean Higher Standards

With this much capital available, investors should be more demanding about the fundamentals.

I would start with real demand and retention, then look closely at margins, customer acquisition costs and how much additional capital is required to sustain growth. Most importantly, I would ask what the company is building today that will still matter when the technology underneath it is cheaper, faster and available to everyone.

The Real Measure of Venture Success

The $510 billion invested in the first half of 2026 reflects enormous confidence in technology and entrepreneurship, but abundant capital can create its own distortions when too much money begins chasing the same narratives.

The companies I would want to own through this cycle are not necessarily those that raise the most money. They are the ones that can take the capital they receive and convert it into durable economic value.

For me, that is still the discipline at the heart of venture investing: what you pay today, what the business can realistically become, and whether the gap between the two leaves enough room for an attractive return.

Editor's note

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