VCs Crown AI Winners Early with 'Kingmaking' Strategy

Venture Capital (VC) firms are increasingly employing an aggressive "kingmaking" strategy, particularly within the burgeoning AI sector. This approach involves injecting substantial capital into early-stage AI startups, aiming to establish them as dominant market leaders from their inception. While VCs have long used large investments to back potential category winners, this tactic is now being deployed with unprecedented speed and scale, often before startups demonstrate significant revenue.

Early Funding, High Valuations, and Revenue Discrepancies

A prime example surfaced in early October when DualEntry, an AI enterprise resource planning (ERP) startup, announced a $90 million Series A round. Led by Lightspeed and Khosla Ventures, this funding valued the one-year-old company at an impressive $415 million. DualEntry aims to disrupt legacy software like Oracle NetSuite by automating routine tasks and offering predictive insights. Such a massive investment from top-tier VCs typically signals phenomenal revenue growth.

However, one VC, who opted not to invest, told TechCrunch that DualEntry's annual recurring revenue (ARR) was merely around $400,000 when he reviewed the deal in August. DualEntry's co-founder denies this figure, stating revenue was "considerably higher" when the deal closed.

Defining the "Kingmaking" Strategy

Regardless of the exact figures, an exceptionally high valuation relative to revenue is becoming a hallmark of this "kingmaking" investment strategy. This tactic involves pouring immense funding into a single startup within a competitive category. The goal is to overwhelm rivals by granting the chosen company such a significant financial advantage that it creates the perception, and potentially the reality, of market dominance.

A Dramatic Shift in Investment Timing

While "kingmaking" isn't entirely new, its timing has dramatically shifted. Jeremy Kaufmann, a partner at Scale Venture Partners, notes, "Venture capitalists have always evaluated a set of competitors and then made a bet on who they think the winner is going to be in a category. What's different is that it's happening much earlier."

This aggressive early funding contrasts sharply with previous investment cycles. David Peterson, a partner at Angular Ventures, recalls the 2010s version as "capital as a weapon," citing the massive funding into Uber and Lyft. However, he points out that this capital weaponization for ridesharing companies typically began at their Series C or D rounds, not at the nascent Series A stage.

The Rapid Funding Race in AI ERP

The AI ERP sector exemplifies this accelerated funding trend. Investors in DualEntry's competitors, Rillet and Campfire AI, are equally eager to see their bets succeed with substantial capital. In early August, Rillet secured a $70 million Series B round led by a16z and Iconiq, just two months after the company closed a $25 million Series A led by Sequoia.

Similarly, Campfire AI received back-to-back funding. In October, it grabbed a $65 million Series B, only a couple of months after announcing a $35 million Series A round led by Accel.

Jaya Gupta, a partner at Foundation Capital, highlighted this rapid succession on X (formerly Twitter) last month, noting, "There's no new data between rounds. Series Bs happen 27-60 days after Series As regularly." She observes this pattern not only in AI ERP but also in categories like IT service management and SOC compliance. While some startups, such as Cursor or Lovable, have reportedly achieved breakneck growth between rounds, several VCs indicate this isn't universally true. Many AI ERPs and other rapidly funded startups from 2025 still report ARRs in the single-digit millions.

Rationale and Risks of High-Stakes Funding

Despite the skepticism, VCs have reasons for deploying large capital sums early, even with modest burn rates. Well-funded startups are often perceived as more stable and likely to survive by large enterprise buyers, making them preferred vendors for significant software purchases. This strategy, for instance, helped legal AI startup Harvey attract major law firm clients.

However, historical precedents demonstrate that massive capitalization offers no guarantee of success. Notable failures include the logistics company Convoy, which shut down, and the scooter company Bird, which underwent bankruptcy reorganization.

These past failures don't deter major VC firms. They are keen to bet on categories ripe for AI disruption and prefer to invest early. As Peterson explains, "Everybody has fully internalized the lesson of the power law. In the 2010s, companies could grow faster and be bigger than almost anybody had realized. You couldn't have overpaid if you were an early Uber investor." This belief in the potential for exponential growth fuels the current high-stakes "kingmaking" in the AI startup ecosystem.