AI Fund Closes $190 Million Second Fund as Startup Interest Grows
AI Fund, the venture studio founded by artificial intelligence researcher Andrew Ng, has raised $190 million in its second fund, exceeding its target. The new capital comes amid accelerating demand for early-stage AI ventures, particularly those building software solutions on top of foundation models. This second fund builds on the studio’s original $175 million fund, launched several years earlier.
Instead of functioning as a conventional investor, AI Fund works intimately with founders to inform business concepts and build founding teams. Its method is aimed at optimizing the earliest stages of startup creation — market validation to product design — so that entrepreneurs can get AI-based companies into market more quickly and effectively.
Corporate LPs Signal Sector-Wide Demand
The fund saw investment from a broad base of corporate limited partners, such as HP, AES, Mitsubishi Corporation, Mitsui, and QBE, and well-established venture capital firms such as Sequoia Capital and NEA. The corporate investors are predominantly from Asia, North America, and Europe and operate in industries like energy, technology, financial services, and industrials.
Partners at the fund noted that many of their portfolio ideas emerge directly from collaboration with these firms, who often highlight pressing challenges within their industries. This, they argue, creates an opportunity to launch ventures with both access to proprietary data and a clear path to early commercial traction.
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Focus on Applied AI and Infrastructure
AI Fund will continue to build businesses that sit at the application and infrastructure levels of the AI stack. Some of the most important areas of interest are the future of work, healthcare, logistics, financial technology, and developer tools. The fund is specifically interested in startups applying next-generation AI models, such as those with reasoning, multi-modal input, or autonomous agents.
While advances in recent times, like large language models, have grabbed headlines, the fund is setting itself up to close the space between leading research and practical implementation. It aims to fund startups that can convert AI strength into products with lasting influence, not mere proofs of concept.
