In the tiny kingdom of Bhutan, dozens of data experts perfect artificial intelligence models from offices framed by majestic Himalayan peaks. The employees at iMerit aren’t there to train AI in rudimentary tasks like recognizing "brown cat on a windowsill" in an image. Instead, they’re teaching algorithms the anatomy of the human eye or how to detect changes in geospatial maps.

Backed by three Silicon Valley billionaires, iMerit is part of a growing cohort of companies building a more sophisticated, monetizable and reliable version of AI, an industry on track to add nearly $20 trillion to the global economy by 2030. As models become smarter, big business is increasingly looking to harness their power for highly specialized tasks, spawning dozens of data services startups devoted to customizing applications across sectors like finance, health care and defense.

There’s a lot at stake. Even as AI fervor has swept through Silicon Valley, nagging questions persist about whether the technology will actually prove useful enough for businesses around the world to pay up for it and ensure that AI model developers can turn a profit. Of course, Nvidia has become the most valuable company in the world by selling AI chips. But the firm’s biggest customers, including Microsoft and Alphabet, are still losing money from the immense cost of building more advanced AI systems.