The thesis is simple: if artificial intelligence can evaluate startups, source deals, and predict winners better than humans, then most venture capitalists are redundant. That’s the argument Wired laid out in a recent piece exploring whether AI could displace the venture capital industry. The short answer is no. The longer answer is more interesting — and more uncomfortable for the thousands of VCs who add little beyond capital.
Let’s start with what’s actually happening.
The Automation of Deal Flow Is Real — and Accelerating
AI-powered tools are already reshaping how firms find and evaluate companies. SignalFire, a San Francisco-based VC firm, has built proprietary systems that track over 650 million data points across hiring patterns, product usage, patent filings, and developer activity to identify promising startups before they even begin fundraising. EQT Ventures uses an AI platform called Motherbrain that has sourced multiple investments the firm wouldn’t have found through traditional networks. These aren’t prototypes. They’re production systems generating real returns.
And they’re getting better fast. Large language models can now parse pitch decks, summarize market analyses, and flag competitive risks in seconds. Tasks that once consumed junior associates’ entire weeks now take minutes. According to CB Insights, over 40% of VC firms with more than $500 million in assets under management have integrated some form of AI tooling into their investment process as of early 2025.
So the displacement of analytical grunt work is already underway. No debate there.
But here’s where the “AI kills VC” narrative breaks down. Venture capital isn’t primarily an information-processing business. It’s a power-brokering business. The best VCs don’t win because they read more pitch decks. They win because founders choose them over other investors offering identical term sheets. That selection happens based on reputation, board experience, recruiting networks, and the ability to get a company into rooms it couldn’t otherwise enter.
No model does that. Not yet. Probably not for a long time.
Marc Andreessen has made this point repeatedly — that the top-tier firms function more like talent agencies than financial analysts. When Stripe chose Sequoia, it wasn’t because Sequoia’s spreadsheet was better. It was because Sequoia’s name on the cap table signaled credibility to enterprise customers, future investors, and potential hires. AI can’t replicate that signal. The brand is the product.
This creates a bifurcation that matters. Elite firms — Sequoia, Andreessen Horowitz, Benchmark, Founders Fund — are largely insulated. Their moats are relational and reputational. But the vast middle tier of venture capital, the hundreds of sub-$200 million funds whose primary value proposition is writing checks and offering “strategic guidance,” faces genuine existential pressure.
The Vulnerable Middle
There are roughly 3,800 active VC firms in the United States, according to the National Venture Capital Association’s 2024 Yearbook. Most of them are small. Most of them underperform public markets. Cambridge Associates data shows that median VC fund returns have trailed the S&P 500 over the last decade. The industry’s aggregate performance is propped up by a handful of outlier funds that generate spectacular returns while the majority destroy value.
This is the segment AI threatens most directly.
Consider what a founder needs from a mid-tier VC today: capital, some introductions, maybe help hiring a VP of Sales. AI agents are increasingly capable of the latter two. Tools from companies like Clay, Apollo, and newer AI-native platforms can automate warm introductions through network mapping. AI recruiting tools from firms like Mercor — which itself raised $32 million in 2024, as reported by TechCrunch — can match candidates to roles with striking accuracy. If the non-capital services a mid-tier VC provides can be replicated by software costing a few thousand dollars a month, the fund’s 2-and-20 fee structure becomes very hard to justify.
Some VCs are already feeling this. Deal volume dropped 30% in 2023 and recovered only modestly in 2024, per PitchBook. Fundraising for new VC funds fell to its lowest level since 2017. Limited partners — the pension funds, endowments, and family offices that back VCs — are consolidating their commitments into fewer, larger managers. The middle is already thinning. AI accelerates that trend.
But acceleration isn’t elimination.
The Wired piece gestures toward a future where AI systems autonomously allocate capital to startups, cutting out human VCs entirely. This undersells the complexity of early-stage investing. Seed and Series A decisions are made with radically incomplete information. The data that matters most — founder resilience, team chemistry, willingness to pivot — doesn’t live in databases. It lives in conversations, reference calls, and gut reads developed over decades of pattern matching.
AI is excellent at structured prediction. Early-stage venture is almost entirely unstructured. A model can tell you that a SaaS company growing 15% month-over-month with 130% net revenue retention is attractive. Any competent investor already knows that. The hard decisions — backing a first-time founder in an unproven category, or doubling down on a company that just lost its CTO — require judgment that current AI systems simply don’t possess.
There’s also a governance problem nobody talks about enough. Venture capital isn’t just about picking winners. It’s about sitting on boards, managing conflicts between co-investors, negotiating down rounds, firing CEOs when necessary. These are adversarial, high-stakes human interactions. Delegating them to an AI agent isn’t a technical challenge. It’s a legal and fiduciary one. LPs won’t accept it. Founders won’t tolerate it.
Where This Actually Lands
The most likely outcome is stratification, not extinction. Top-tier firms adopt AI tools to extend their already considerable advantages — faster sourcing, better portfolio monitoring, more efficient operations. They’ll do more with fewer people. Andreessen Horowitz has already moved aggressively into AI-augmented operations, building internal tools that automate significant portions of portfolio support.
Mid-tier firms that can’t differentiate will struggle to raise new funds. Some will pivot to becoming AI-powered micro-funds with minimal staff and lower fees — essentially quantitative investment vehicles for early-stage companies. Others will simply close. The NVCA data already shows a declining number of first-time fund managers successfully raising capital.
And a new category will emerge: AI-native investment platforms that blend automated sourcing with human decision-making. Y Combinator’s application process already uses AI to screen thousands of applicants. AngelList has built infrastructure that enables rolling funds and syndicates to operate with near-zero overhead. These models point toward a future where capital allocation becomes more efficient but not fully automated.
The founders themselves may benefit most. More transparent evaluation criteria. Faster decisions. Less reliance on warm introductions from the right Stanford classmate. If AI reduces the gatekeeping power of mediocre VCs, that’s a net positive for innovation.
But the idea that AI will “kill” venture capital confuses the elimination of inefficiency with the elimination of an industry. VC has always been a relationship business wrapped in a financial structure. AI will strip away the financial pretensions of firms that were never very good at the financial part. The relationship part — the part that actually generates outlier returns — remains stubbornly human.
The industry won’t die. It’ll just get smaller. And for most of the people currently in it, that distinction won’t matter much.
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