Unveiling the Inflated ARR Phenomenon in AI Startups
Last month, Scott Stevenson, co-founder and CEO of the legal AI startup Spellbook, publicly challenged a growing concern in the AI startup ecosystem: the inflation of revenue figures, particularly annual recurring revenue (ARR), by companies eager to project outsized growth. Taking to X (formerly Twitter), Stevenson labeled this practice a “huge scam,” pointing out that many AI startups are misrepresenting their financial performance to win investor favor and media attention.
Stevenson’s critique highlights a troubling trend where startups report “revenues” that do not accurately reflect actual money collected or even guaranteed. He noted, “The reason many AI startups are crushing revenue records is because they are using a dishonest metric. The biggest funds in the world are supporting this and misleading journalists for PR coverage.” This claim resonates beyond Stevenson’s voice, as multiple reports and social media discussions have scrutinized the misuse of ARR as a key performance indicator within the AI sector.
His tweet ignited a robust conversation among prominent investors, founders, and industry commentators, sparking over 200 reshares and extensive commentary from well-known figures including Chamath Palihapitiya and Jack Newton. Newton, CEO of legal tech company Clio, affirmed to TechCrunch that Stevenson’s exposure brought vital awareness to the issue, referencing a detailed post by YC’s Garry Tan on correct revenue metrics.
Understanding the ARR and CARR Distinction
ARR has long been a trusted metric in SaaS and cloud computing, representing the normalized annual revenue from active customer contracts. However, the challenge arises with the introduction and frequent misuse of “Contracted ARR” or “Committed ARR” (CARR), a fuzzier figure that includes revenue from signed but not yet fully implemented or paying customers.
Investors and insiders confirm that many startups blur the lines between ARR and CARR, publicly reporting CARR as ARR to inflate perceived growth. One investor told TechCrunch, “For sure they are reporting CARR as ARR. When one startup does it in a category, it is hard not to do it yourself just to keep up.” This practice can be misleading since CARR counts revenue that may never materialize if clients cancel or fail to fully onboard.
Unlike ARR, which focuses on historical or currently collected revenue, CARR projects future income from contracts still in progress—sometimes counting free pilot periods or lengthy implementation phases as revenue. A former employee from a startup that habitually reported CARR as ARR revealed that free, yearlong pilot programs were counted as revenue, with investors and boards fully aware of the practice. This approach risks overstating financial health and growth potential, particularly when churn and downsell are not accurately factored in.
Bessemer Venture Partners outlined in a 2021 blog post that CARR should be adjusted for expected churn and downsell, yet many startups neglect such adjustments. This omission allows for inflated figures that do not align with actual cash flow or customer retention.
The More Problematic Annualized Run-Rate Revenue
Complicating matters, some founders use another metric also abbreviated as ARR: annualized run-rate revenue. This measure extrapolates revenue over the next 12 months based on current earnings from a shorter period, such as a quarter or even a single day. While this can help forecast growth, it becomes problematic in AI companies where usage-based or outcome-based pricing causes revenue to fluctuate unpredictably.
Industry insiders acknowledge that revenue inflation is not new, but the AI boom has intensified the pressure to present explosive growth. Michael Marks, founding managing partner at Celesta Capital, told TechCrunch, “The valuations have gotten higher, and so the incentives are stronger to do it.” Hemant Taneja, CEO of General Catalyst, emphasized the need for hyper-growth in AI startups, stating on the 20VC podcast, “Going from 1 to 3 to 9 to 27 is not interesting. You got to go like 1 to 20 to 100.”
Such expectations have fostered an environment where some venture capitalists tacitly support or overlook inflated ARR reports to help their portfolio companies capture market attention and talent.
Investor Perspectives and Industry Implications
Interviews with over a dozen founders, investors, and financial professionals reveal a complex landscape. Many acknowledge the widespread use of inflated ARR figures but consider it a strategic move within a highly competitive market. One VC candidly said, “Everyone has a company monetizing CARR as ARR.”
Yet, this approach raises concerns about long-term sustainability and trust. Alex Cohen, CEO of health AI startup Hello Patient, commented, “To everyone who’s inside, it just feels fake. You read the headlines and you’re like, ‘I don’t believe it.’”
Others advocate for transparency and caution against inflated metrics. Ross McNairn, CEO of legal AI startup Wordsmith, cautioned, “I think it’s super bad hygiene, and it’s going to come back and bite you.” He emphasized the importance of clean and clear financial reporting, especially as public markets prioritize ARR over CARR.
Jack Newton also highlighted the conflict of interest among investors, noting that many “look the other way” when their companies inflate numbers because it enhances their own reputations and fundraising narratives.
Conclusion: Navigating Growth Narratives in AI Startups
The controversy around inflated ARR metrics within AI startups underscores a broader tension between rapid innovation, investor expectations, and financial transparency. While the desire to showcase rapid growth is understandable in a competitive market, misrepresenting revenue figures risks eroding trust among investors, customers, and the public.
As the AI sector continues to mature, stakeholders—from founders to VCs—must balance ambition with accuracy. Clear definitions, honest reporting, and realistic growth projections will be essential to sustain the industry’s credibility and long-term success.
For more detailed insights, see the original TechCrunch article Here.
