Ramp Co-founder Glyman: The Economy is Splitting, AI is the Fault Line
Eric Glyman, co-founder of Ramp, pointed out that the U.S. economy is showing a clear split, with the intensity of AI usage becoming the core dividing line. According to data from the Ramp platform, from November 2022 to November 2025, heavy AI users will see an annualized income growth of 27%, moderate AI users 18%, while businesses with no AI spending will grow only by 3%, close to the nominal GDP growth rate of the U.S.
He emphasized that this gap exceeds 20 percentage points each year and will compound over time, affecting traditional industries such as roofing and construction, not just the tech sector.
Source: Public Information
ABAB AI Insight
Glyman's observations are based on actual spending and revenue data from over 55,000 businesses served by Ramp, revealing the asymmetric productivity effects of AI adoption at the enterprise level. Heavy users achieve faster expansion through automation, decision optimization, and tool integration, while non-adopters essentially follow the overall economic pace. This differentiation is not a short-term cyclical fluctuation but a direct reflection of the efficiency of technological tools in substituting labor and capital. Once traditional industry firms start using AI for estimation or document processing, growth can accelerate significantly.
This split corresponds to long-term structural changes in the industry. Historically, technological waves often amplify advantages first among a few leaders, then force followers to adjust through competitive pressure. At the current stage, AI lowers the barriers for software and process transformation, allowing small and medium-sized entities to capture productivity gains, while simultaneously widening the gap with laggards, accelerating the concentration of wealth and market share among efficient executors rather than uniform diffusion.
From a global financial and distribution perspective, this dynamic reinforces the repricing of capital towards technology-intensive assets. The growth of non-AI businesses close to nominal GDP means that existing businesses face relative contraction, while the compounding effects for leaders will widen the stratification of classes and business sizes. Institutional mechanisms reflect an incentive structure tilted towards innovative adoption, driving the economy from broad expansion to stratified growth in the long term, affecting resource allocation and liquidity across cycles.