Advancements in generative Artificial Intelligence (“AI”) and large language models are enabling early-stage companies to scale faster than ever before. Venture investors who can identify and access the ultimate category creating companies are benefiting from unprecedented growth and bigger exits.
The artificial intelligence boom is reshaping the technology landscape at a breathtaking pace. More than just a fleeting trend, AI is proving to be a foundational technology that is creating a new generation of dominant companies. Investors are clearly prioritizing AI companies as 64 percent of U.S. venture capital (by dollars invested) went into AI startups in H1 2025, according to Pitchbook. The first wave of AI investment targeted the infrastructure layer - companies building and training the large language models themselves. While mega-cap technology companies are fiercely competing, private technology companies, such as OpenAI and Anthropic, have led this innovation cycle and have been rewarded: OpenAI’s private company valuation surged to $500 billion and Anthropic’s to $183 billion. This competition has resulted in ever-increasing model capabilities and continuously falling model pricing - a dynamic which is benefitting a burgeoning start-up ecosystem.
While infrastructure players remain essential, the real frontier for venture returns is shifting further up the stack to application companies being formed today that are harnessing AI across a broad and diverse number of use cases, sectors, and geographies. McKinsey estimates that 78 percent of enterprises are now using AI, and nearly every public‑company board and C‑suite is rushing to embed AI into their core business models to avoid being outpaced by competitors. This ravenous demand is being met by AI applications with out-of-the-box ROI potential. For example, Abridge, which was founded by a practicing cardiologist, has developed an AI notetaking application which the AMA estimates saves physicians 300+ hours per year in charting notes on patient visits. Law firms using AI for contract review are reporting time savings of up to 80 percent compared to manual review, with higher accuracy rates. These high levels of adoption are leading to unprecedented revenue trajectories for AI application companies. For example, AI coding applications, Lovable and Cursor reportedly each achieved $100 million in annualized revenues, respectively, in their first year of operations. Cursor’s annualized revenue reportedly has doubled every two months, having recently surpassed $500 million and being valued near $30 billion. And it’s not just the best companies scaling quickly. Data compiled by Stripe shows that AI companies collectively are scaling much more quickly than the prior generations of companies. The chart below illustrates that AI companies reached $30 million in annualized revenue in a median of 20 months as compared to 60+ months for SaaS companies. These AI starups are not just scaling faster but also doing so with a fraction of the number of employees as the prior generation.
What does this mean for investors? The opportunity set has clearly never been bigger, but backing the winning company within a category is key to generating outsized returns. The challenge increasingly lies in separating hype from sustainable growth. Users are still trialing different AI tools which means differentiating between “experimental” revenue and durable recurring cash flows is crucial to underwriting. When you get it right, the size of the prize is larger than ever, and increasingly, coming faster than ever. For example, Wiz, a cloud cyber security company, scaled from founding to a $32 billion exit valuation just 5 years later when Google agreed to acquire the company in what, if approved by regulators, will represent the largest venture backed M&A event in history. The state of the AI transition is early, but promising. We encourage investors to take a long-term perspective, as they look to capture exposure to the next crop of category defining companies.
