Zack Kanter, a prominent entrepreneur and CEO of Stedi, recently highlighted the paradoxical financial landscape of artificial intelligence companies, noting their "truly incredible" revenue growth often coexists with negative gross margins. Kanter, known for his insights into technology and business, suggested that the industry might require a new financial metric to accurately assess performance beyond traditional profitability measures.
The AI market is indeed experiencing exponential expansion. Projections indicate the global AI market is set to grow at a Compound Annual Growth Rate (CAGR) of 35.9% between 2025 and 2030, with some estimates forecasting a staggering $15.7 trillion in revenue by 2030. Leading AI firms, including OpenAI, Anthropic, and Google DeepMind, have reported over 9x revenue growth in 2023-2024, underscoring the sector's rapid commercialization.
Despite this robust top-line growth, many AI companies operate with negative gross margins, a point Kanter addressed in his tweet. He posited that this situation is "probably not 'selling dollars for 80 cents'," suggesting that these negative margins are likely a function of significant upfront investments in research, development, and infrastructure necessary for long-term growth and market dominance. Valuation models for early-stage AI startups often prioritize revenue multiples over immediate profitability, reflecting this investment-heavy phase.
Given these unique financial characteristics, Kanter proposed a novel metric: "fastest from $1m->$100m in gross profit." This metric aims to capture the efficiency and speed at which AI companies can scale their profitable operations, providing a more relevant indicator of financial health and potential than traditional gross margin analysis alone. Kanter's background as the founder of Stedi, a B2B software company leveraging AI, and an angel investor, lends significant weight to his observations on the evolving economics of the AI sector.
The discussion around AI company financials underscores a broader industry trend where innovation outpaces conventional financial frameworks. As AI continues to integrate across various sectors, the focus remains on capturing market share and building scalable platforms, with profitability often viewed as a longer-term outcome. This dynamic suggests that investors and analysts may increasingly need to adapt their evaluation criteria to fully grasp the economic potential of the rapidly advancing artificial intelligence landscape.