As the revenue infrastructure provider for thousands of AI companies, including 88% of the 2026 Forbes AI 50, Stripe data offers a unique view of the AI economy. Our data shows that AI companies are growing their global footprints quickly: the 100 largest by revenue reached 120 markets on average by their third year of operation. But where is market demand actually strongest? Who’s on the other side of the AI growth engine, and what’s the best way to convert their demand to revenue?
To understand, we looked at the transaction data for all AI companies on Stripe and mapped the landscape. We looked beyond simple market size: the countries spending the most on AI on Stripe largely corresponded to high-GDP countries that would make good expansion candidates for any kind of company. More interesting markets emerged when we considered additional signals, like countries with growing AI spending, or AI spending that was disproportionate to their overall payment volume on Stripe.
While it’s easier than ever to sell globally, presence alone doesn’t always translate to revenue. To build a truly international revenue base—like the 100 largest AI companies on Stripe, which collectively draw 48% of their revenue from outside their home markets—it’s often necessary to localize the product and offering. This geographical analysis shows where companies might prioritize launches and investments in local marketing, translations, payment methods, and more. Here’s what we found.
1. Outsized AI spend puts new markets in the spotlight
Unsurprisingly, the 10 markets on Stripe with the highest AI spend—in orange and black on the chart above—are also some of the largest markets on Stripe for general online spending, and generally represent high-GDP countries with high connectivity to global trade.
To identify less obvious high-momentum markets, we looked for atypical spending patterns, identifying the countries with the greatest share of AI spend compared to their overall spend on Stripe. By this metric, India, Mexico, Poland, and the United Arab Emirates all emerged as top markets (in purple). Brazil, Japan, and South Korea were revealed as countries where AI spend is both high in the absolute sense, and high in relation to other online spending on Stripe.
2. Overall market growth is high, with the highest rates found in a mix of small and more established markets
AI spend is growing rapidly in every market we examined on Stripe. Even after limiting our analysis to the 35 markets that had already achieved meaningful AI spend (over $20 million) by 2024, we saw median year-over-year growth of nearly 100%. This means that while many of the largest markets on Stripe grew more slowly than the median, their absolute growth was still quite high: the United States sat at 91% year over year, and Australia at 61%.
Above-median growth was naturally concentrated in already smaller markets, as shown below, but was also found in markets with already considerable spend that show no sign of slowing down.
Canada, Germany, and the United Kingdom all sustained high rates of growth. South Korea emerged as a triple threat: a large market with a high growth rate (134%) and AI spending disproportionate to the country’s overall spend on Stripe. This could reflect a combination of national policies (like the 2026 “Basic Act,” promoting growth amid safety guardrails), a government-supported startup scene, and a population that reports the lowest rate of being “more concerned than excited” about the rise of AI in daily life.
Mexico was the overall standout growth market, with 264% year-over-year growth of AI spend on Stripe. It’s also a market that disproportionately spends on AI, potentially benefiting from its proximity to the US and major investments from US companies. As an expansion target, it offers an opportunity to establish a foothold in a market less crowded than the more established high-growth countries.
3. Launching globally is the first step, while localization drives long-term growth
For many companies, global customer demand drives rapid expansion and growth. At the high end is a company like Manus, which started accepting payments from more than 200 countries and territories just a month after its AI agent platform went viral in early 2025, and achieved a $90 million run rate just four months later.
But we see evidence in our data that localization is needed to sustain high growth and capture meaningful revenue outside a company’s home market. The fastest-growing AI companies on Stripe already use 2x more local payment methods on average than the broader cohort, and previous analyses have shown that surfacing relevant local payment methods can have a significant impact on conversion (up 7.4% on average) and revenue (up 12% on average).
For Gamma, the AI-powered design platform, LPMs have been especially key to success. When Gamma switched on UPI, India’s real-time payment system and protocol, its in-country revenue increased by 22%. Overall, more than half of the company’s revenue currently comes from outside its home market, the United States.
We’ve also seen that offering payment in local currency improves both initial conversion and lifetime subscription value for AI businesses with recurring revenue. In a previous analysis, subscription businesses using Stripe’s Adaptive Pricing feature saw a 4.7% boost on average to initial conversion, and a 5.4% boost on average to lifetime subscription value.
Some AI companies can experience even greater uplift: Runway saw up to 17.7% more lifetime value per subscription after introducing Adaptive Pricing.
What’s next
As AI companies reach the ceiling of global expansion (there are only so many countries in the world), sustaining growth will require laying roots in the places they’ve launched. To plan your global growth strategy and to discover the right infrastructure to support it, get in touch.
Facts Only
* Stripe data covers transaction information for AI companies.
* The 100 largest AI companies on Stripe draw 48% of their revenue from outside their home markets.
* The 10 markets with the highest AI spend on Stripe are also among the largest markets for general online spending and represent high-GDP countries.
* India, Mexico, Poland, and the United Arab Emirates emerged as top markets based on the share of AI spend relative to overall Stripe spending.
* Brazil, Japan, and South Korea showed high absolute AI spend and high relative spend on Stripe.
* Median year-over-year growth for AI spend across 35 markets with meaningful AI spend (over $20 million by 2024) was nearly 100%.
* The United States showed 91% year-over-year growth in AI spending.
* Canada, Germany, and the United Kingdom sustained high rates of growth.
* South Korea exhibited 134% year-over-year growth and disproportionate AI spending relative to overall Stripe spend.
* Mexico experienced 264% year-over-year growth in AI spend on Stripe.
* Local payment methods increased in-country revenue by 22% for a company in India upon switching to UPI.
* Stripe's Adaptive Pricing feature correlated with average increases of 4.7% in initial conversion and 5.4% in lifetime subscription value for subscription businesses.
Executive Summary
Full Take
The narrative pivots on the tension between global expansion velocity and localized revenue capture, suggesting that mere market presence is insufficient for sustainable success in the AI sector. The data highlights a pattern where high-growth momentum often resides in markets with favorable regulatory or socio-economic conditions, exemplified by South Korea’s combination of rapid growth and disproportionate spending relative to other activity. This suggests that growth rates alone do not define opportunity; contextual factors—such as national policy alignment (e.g., the 2026 “Basic Act”), government support for startups, or public attitudes towards AI adoption—are crucial determinants of momentum.
The critical insight is the mechanism linking localization to monetization: simply selling globally establishes access, but local payment methods and currency adjustments are the levers that unlock revenue translation. The observation that local payment integration boosts conversion and lifetime value implies that the infrastructural friction is not just a logistical hurdle but an economic barrier that needs targeted mitigation. This suggests that success in scaling AI beyond home markets depends less on universal product quality and more on embedding operational fluency within local financial ecosystems. The future of global AI expansion likely involves a layered strategy: using broad market growth for initial traction, followed by deep localization to secure long-term revenue stability and maximize capital capture from the fragmented global demand landscape.
Bridge Questions: If localization is the key multiplier for revenue, what are the specific investment benchmarks needed to justify the operational cost of creating localized payment stacks versus relying on centralized international solutions? How do national regulatory differences, which influence growth rates (like in South Korea), map onto a universal model for identifying high-potential expansion corridors rather than just high-growth metrics? What infrastructure requirements exist for AI companies to efficiently manage diverse localization efforts simultaneously across multiple jurisdictions?