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    Home»Business»Is the AI era the beginning of the end of VC as we know it?
    Business 7 Mins Read

    Is the AI era the beginning of the end of VC as we know it?

    Business 7 Mins Read
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    Incredibly, when you think about it, US-based venture capital has remained structurally unchanged for half a century. The well known model revolves around the 10-year fund lifecycle, the 2-and-20 fee structure, and the relentless push for growth and outsized returns. Decisions are made in mysterious ways and are known to be full of bias against founders who don’t fit a certain mold.  But even as rivers of investment flow into anything touching AI, there may yet be an ironic twist to come.
    Venture investing involves optionality and power laws. Very few investments will generate any returns at all, but the sector is premised on the idea that within any portfolio there will be just a few startups that will enjoy a spectacular exit, through an initial public offering or by being acquired by a deep-pocketed established firm. VC’s are betting on their ability to sniff out the rare winners amidst a sea of potential startups. But in many ways, it’s a terrible business—by some accounts 95% of the industry’s total returns are generated by less than 5% of its firms.  Nonetheless, venture capital is firmly planted in the economy and in the public consciousness as the way that innovations get funded and businesses grow.

    For many entrepreneurs taking venture capital money is seen as a badge of honor and a financial boost for quick growth. Nonetheless, there are any number of complaints that founders have with regard to their investors, ranging from misguided expectations to unwanted advice to egregiously unfair business practices with respect to the equity and control that the firms extract. So why turn to a venture capitalist?  Mainly because there were issues that no founder could address on their own or with capital that was ready to hand. 

    The logic of venture capital was always premised on scarcity. Capital was scarce. Technical talent was scarce. The infrastructure to build, test, and distribute a technology product was scarce. VCs existed to bridge those gaps—to provide the resources a promising team needed before the market could prove them right. In exchange, they took equity, board seats, and influence over strategy. It was a reasonable bargain, forged in the conditions of the 1970s and refined through the personal computer, internet, and mobile revolutions.

    AI is dismantling every one of those scarcities.

    The collapsing cost of creation

    Consider what it actually costs to start a technology company today. A founder who five years ago needed $2 million and eighteen months to build a minimum viable product can now do it alone in six weeks for the cost of a few cloud subscriptions. Tools like Cursor, Lovable, and Replit, powered by large language models, have compressed the software development cycle so dramatically that technical co-founders—long considered mandatory—are increasingly optional. One solo founder, Maor Shlomo, built an AI startup called Base44 entirely alone, reached 300,000 users and $3.5 million in annual recurring revenue, and sold it to Wix for $80 million in cash—in six months.

    That is not an outlier story. It is an emerging template. Indeed, 80% of companies that go public do so without venture funding. More than half of successful startup exits last year were achieved by solo founders. The minimum viable team for building a significant technology business has dropped to one.

    When the cost of creation falls this far, the fundamental value proposition of a venture capitalist—we will give you the money to build in exchange for a commitment to give us your first born—starts to lose its grip. You do not need the money any more to get to a first product, a real user base, or even meaningful revenue. What you need money for is distribution, sales, and scale. And those needs arrive much later in the company’s life, at which point the founder’s negotiating leverage has increased dramatically.

    Capital at the extremes

    Where investment dollars are flowing in the economy resembles a barbell. At one end, an unprecedented concentration of capital in a handful of AI infrastructure companies—OpenAI, Anthropic, xAI, Databricks—that require the kind of compute investment that resembles project finance more than traditional venture backing. These are not startups in any meaningful sense; they are capital infrastructure projects, and they are absorbing the majority of venture dollars. 41% of all VC money invested in 2025 went to just 10 startups, according to Pitchbook.

    At the other end are thousands of small, capital-efficient AI application businesses that need very little money and generate meaningful returns quickly. Cursor reached $500 million in annual recurring revenue with fewer than 50 employees, and is now up to about $2 billion. Midjourney, the AI image generation company, crossed $200 million in revenue with roughly 40 people and has taken no venture funding at all.  A 28 person startup called Gamma’s founder, Grant Lee, actively rejects invitations from potential VC’s.  These businesses do not need—and in many cases do not want—a VC on their cap table and their board

    The middle is collapsing. The classic venture model of Series A, B, and C rounds funding a startup’s progression from idea to scale is becoming less relevant for a growing category of businesses. AI-powered companies are reaching profitability earlier, growing faster, and requiring less capital at each stage. Industry analysts report that AI startups are reaching $1 million in annual revenue up to four months faster than comparable SaaS companies were reaching the same milestone just a few years ago.

    The gatekeeper premium

    There is a deeper challenge for venture capital, one that goes beyond deal economics. For decades, VCs served as gatekeepers to a network of resources that founders couldn’t access on their own: introductions to enterprise customers, relationships with talent recruiters, connections to co-investors, and the credibility signal of a prominent firm’s backing. That access premium justified the equity cost.

    AI is eroding that premium too. Machine learning tools can now identify potential customers, analyze competitive landscapes, surface talent, and predict market opportunities faster than any junior associate. Founders can use AI to understand their own metrics deeply, identify the right investors for their stage, and run their own due diligence on potential partners. The information asymmetry that once made VCs indispensable—they knew things founders didn’t—is flattening.

    Some prominent investors have acknowledged this openly, arguing that the future of venture will involve smaller teams using better tools rather than massive platforms with armies of analysts and associates. The VC firm of 2030 will look less like a financial intermediary and more like a high-powered advisory network, one that adds value through judgment and relationships in conditions of genuine uncertainty rather than through capital deployment and information advantages.

    What survives

    None of this means venture capital disappears. The frontier AI companies—the ones building and training foundational models—require capital at a scale that no bootstrapped founder can self-fund. Anthropic’s most recent funding round was $30 billion and valued the company at $380 billion. These investments look less like early-stage venture and more like the kind of patient, infrastructure capital that once built railroads and power grids. They will continue to attract large allocations.

    And there will always be categories of business where scale still confers advantage—where network effects, regulatory moats, or capital-intensive physical infrastructure mean that a well-funded incumbent can overwhelm a lean competitor. In those sectors, the traditional venture model retains its logic.

    But the universe of businesses where that logic applies is shrinking. Every year, more categories of valuable economic activity become accessible to small, capital-light teams with AI leverage. Every year, the assumption that you need millions of dollars and a VC’s blessing to build something significant becomes less defensible.

    The last venture capitalists will not be the ones who ran out of money. They will be the ones who ran out of founders who needed them.



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