The venture capital landscape is currently experiencing a dramatic acceleration in investment strategy, particularly within the burgeoning artificial intelligence sector. A recent exemplar of this trend emerged in early October when DualEntry, an AI enterprise resource planning (ERP) startup barely a year old, announced a substantial $90 million Series A funding round. This significant capital injection, co-led by prominent firms Lightspeed and Khosla Ventures, propelled DualEntry’s valuation to an impressive $415 million. The company’s stated ambition is to revolutionize the ERP market by offering an AI-powered alternative to established legacy software providers like Oracle NetSuite, promising enhanced automation of routine tasks and superior predictive insights for businesses.

While such a massive early-stage funding round typically signals robust revenue growth, the valuation has sparked considerable discussion within the investment community. One venture capitalist, who chose not to participate in the DualEntry deal, informed TechCrunch that the startup’s annual recurring revenue (ARR) was reportedly around $400,000 when the opportunity was reviewed in August. DualEntry co-founder Santiago Nestares has disputed this figure, stating that the company’s revenue was "considerably higher" when the deal officially closed. Regardless of the exact figures, this scenario—where a startup commands an exceptionally high valuation relative to its immediate revenue streams—is fast becoming a hallmark of a distinct investment approach within the AI domain, commonly referred to as "kingmaking."

The Strategic Gambit of "Kingmaking"

"Kingmaking" describes a venture capital strategy where an exceptionally large sum of capital is deployed into a single startup within a highly competitive market category. The primary objective is to equip the chosen company with an overwhelming financial advantage, theoretically enabling it to outspend, out-innovate, and out-market its rivals. This significant capital buffer aims to create an impression of market dominance and inevitable success, making it challenging for competitors to catch up, irrespective of their own technological merits or early traction.

While the concept of backing a potential market leader is intrinsic to venture capital, the timing and scale of this "kingmaking" strategy have undergone a profound shift. Historically, venture capitalists would identify promising companies and gradually scale their investments as these firms demonstrated consistent growth, product-market fit, and increasing revenue. Aggressive capital deployment, often termed "capital as a weapon," was typically reserved for later stages—Series C, D, or even beyond—when companies had already achieved substantial scale and were battling for market share dominance. A canonical example from the 2010s is the fierce competition between ride-sharing giants Uber and Lyft, where massive funding rounds were instrumental in their global expansion and market consolidation efforts, but these capital battles unfolded after both companies had established significant operational footprints.

The AI Revolution and Accelerated Investment Cycles

The current iteration of kingmaking distinguishes itself by its precocity. Investors are now making these decisive, large-scale bets much earlier in a startup’s lifecycle, often at the Series A or B stage, sometimes even pre-revenue or with minimal revenue. Jeremy Kaufmann, a partner at Scale Venture Partners, highlights this shift: "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 accelerated timeline is largely driven by the perceived transformative potential and winner-take-all dynamics of artificial intelligence. The rapid advancements in generative AI and large language models have convinced many investors that the next wave of multi-billion-dollar companies will emerge from this sector. The "power law" — a fundamental principle in venture capital where a small number of investments generate the vast majority of returns — has been deeply internalized by top-tier firms. David Peterson, a partner at Angular Ventures, articulated this sentiment, noting, "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 philosophy fuels the belief that identifying and heavily funding the future "Uber of AI" early on, even at a seemingly inflated valuation, could yield exponential returns that dwarf any initial overpayment.

The Battle for AI ERP Dominance

The AI ERP sector serves as a prime example of this intense, early-stage capital deployment. DualEntry is not alone in receiving substantial backing. Its rivals, Rillet and Campfire AI, have also secured impressive funding rounds in rapid succession. In early August, Rillet closed a $70 million Series B round, led by Andreessen Horowitz and Iconiq, a mere two months after securing a $25 million Series A from Sequoia. Similarly, Campfire AI announced a $65 million Series B in October, shortly after its $35 million Series A led by Accel.

This pattern of back-to-back funding rounds with little time for substantial operational progress between them is becoming increasingly common across various AI application categories. Jaya Gupta, a partner at Foundation Capital, observed this phenomenon on social media, noting that "Series Bs happen 27-60 days after Series As regularly" in categories beyond AI ERP, such as IT service management and SOC compliance. While some startups, like Cursor or Lovable, have reportedly demonstrated extraordinary growth between their rapid funding rounds, many others in these categories, including several AI ERPs, are said to still have annual recurring revenues in the single-digit millions, according to multiple VCs who spoke with TechCrunch. This disparity between valuation and current revenue underscores the speculative nature of these early bets.

Motivations and Strategic Advantages

The motivations behind this aggressive early funding are multifaceted. One significant advantage for well-capitalized startups is the perception of stability and longevity among large enterprise buyers. When investing in critical software infrastructure like ERP systems, large corporations prioritize vendors with a solid financial footing, perceiving them as less risky and more likely to endure and support their products long-term. This perception can act as a self-fulfilling prophecy, making well-funded startups the preferred choice for substantial software purchases. The legal AI startup Harvey, for instance, reportedly leveraged this strategy to attract major law firm clients.

Beyond signaling to customers, a large war chest enables startups to attract and retain top-tier talent, particularly crucial in the highly competitive and specialized field of AI engineering and research. It also allows for aggressive product development, marketing campaigns, and potential acquisitions, all designed to rapidly establish market leadership. The sheer volume of capital can effectively deter potential competitors who might struggle to match the resources and runway of a "king-made" startup.

Risks, Criticisms, and Broader Implications

Despite the strategic rationale, the kingmaking strategy is not without its critics and significant risks. History is replete with examples of richly capitalized companies that ultimately failed to achieve their promised potential. The logistics company Convoy, once a digital freight unicorn, and the scooter company Bird, which underwent bankruptcy reorganization, serve as stark reminders that massive investment alone does not guarantee success or sustained market leadership. These cases highlight the potential for capital misallocation, inefficient spending, or simply betting on the wrong horse in a rapidly evolving market.

Critics also voice concerns about the potential for market distortion. By concentrating immense capital into a select few early-stage companies, this strategy could inadvertently stifle genuine innovation from smaller, less-connected startups that may possess superior technology or more agile business models but lack the initial financial firepower. It risks creating an oligopoly where market access is determined more by investor connections and capital availability than by meritocratic competition. This could lead to a less diverse and potentially less innovative AI ecosystem in the long run.

Moreover, the elevated valuations raise questions about the sustainability of the current AI boom. If many of these heavily funded startups fail to deliver on their ambitious growth projections, or if a broader economic downturn impacts the tech sector, a significant correction in valuations could ensue, leading to substantial losses for investors and potential layoffs within the affected companies. The rapid-fire funding rounds, often conducted without substantial new data or demonstrable progress, could be seen as an indicator of investor exuberance and Fear Of Missing Out (FOMO), rather than purely rational decision-making based on fundamentals.

The implications extend beyond the immediate financial returns for VCs and founders. The concentrated power and resources within a few AI behemoths, shaped by a handful of influential venture firms, could have broader societal consequences. Questions around data privacy, algorithmic bias, market fairness, and the ethical development of powerful AI systems become even more pertinent when control rests with a limited number of dominant players.

Looking Ahead

As the AI revolution continues its trajectory, the kingmaking strategy represents a bold, high-stakes gamble by venture capitalists to secure dominant positions in what they perceive as the next frontier of technological advancement. It is a testament to the lessons learned from past tech booms—the power law, the importance of early market capture, and the exponential growth potential of truly transformative technologies. However, it also carries the inherent risks of speculative investment, market distortion, and the potential for a new cycle of boom and bust. The ultimate success or failure of these "king-made" AI companies will not only shape the future of their respective industries but also offer crucial insights into the evolving dynamics of venture capital in an era defined by unprecedented technological change.