In the dynamic landscape of Silicon Valley, there’s little that excites investors more than an impressive growth in annual recurring revenue (ARR). However, amid the ongoing AI surge, venture capitalists are starting to raise questions about the true meaning of this figure.
Greg Isenberg, CEO of Late Checkout, sparked discussion with a candid remark that went viral, revealing concerns about the misinformation surrounding ARR from VC-backed AI firms. He noted, "The amount of VC-backed AI companies lying about their ARR publicly is absolutely unsettling," highlighting a sentiment that has been commonly speculated but seldom articulated in tech discussions.
Originally popularized during the software boom, ARR was meant to provide a snapshot of a company's expected yearly earnings from customers who pay regularly, serving as a quick reference for investors evaluating a startup's worth. However, insiders who spoke to Business Insider suggest that the term has become increasingly ambiguous, conflating various forms of revenue such as subscribed services, future contracts, hardware sales, and even one-off revenue spikes.
In essence, true recurring revenue is often misrepresented. Shruti Gandhi, a general partner at Array Ventures, referred to the trend as "ARR inflation," expressing that there currently exists a lack of accountability. She has pointed out instances of founders inflating their figures, with the common rebuttal being that such behavior is ubiquitous.
Alexander Niehenke, a partner at Scale Venture Partners, notes that this trend indicates a psychology reminiscent of the peak of the 2021 market, where risk tolerance among investors was elevated. "It feels like we're at the tail end of 2021 again, given some of the behavior I'm seeing in the venture ecosystem," he remarked.
Founders are well aware of the enthusiasm VCs have for ARR. Niehenke compares their tactics to "catnip," exploiting investor excitement for their own advantage. This behavior was exemplified when Roy Lee, CEO of Cluely, admitted to inaccurately reporting his company’s ARR to a TechCrunch journalist—a rare moment of honesty in an otherwise unregulated environment for startups, where revenue claims often go unchecked.
In the wake of these revelations, more startups are turning to run rate as a metric, which extrapolates a single month’s revenue to project annual earnings without implying that the revenue is consistent. This approach emerged as the nature of AI revenue became less predictable. Unlike traditional software-as-a-service (SaaS), where predictable contracts ensure stable ARR, many AI companies base their pricing on variable usage—commonly calculated in tokens—which leads to significant fluctuations in both revenue and costs.
Pocket, known for its AI recording device, recently announced it surpassed a $100 million run rate. Founder Akshay Narisetti prefers this metric since it reflects the unpredictable nature of token-based revenues. He emphasizes avoiding the pitfalls of annualizing revenue spikes from singular high-performing months.
Despite the issues surrounding run rate, it offers a clearer alternative during these uncertain times. For example, major AI entities like OpenAI refer to their subscription sales as ARR but label their new advertising revenue as an annualized run rate. Meanwhile, Anthropic has generally categorized its sales under the run-rate banner.
In contrast, Linear—a unique SaaS startup—recently affirmed its achievement of $100 million in ARR based on the stability of its revenue model, which includes multiyear contracts. Cofounder and CEO Karri Saarinen defended the use of ARR by pointing to Linear's longevity and reliable forecasting capabilities, though he acknowledged that this is not the case for many newer AI-focused startups, which often find themselves in an increasingly foggy revenue landscape.
