Mark Zuckerberg Was Early in AI. Now Meta Is Trying to Catch Up.

Meta META -0.29%decrease; red down pointing triangle is doing something Mark Zuckerberg doesn’t like: playing catch up.

A decade ago, the company founder and CEO saw the promise for artificial intelligence and invested large sums of money into its advancement. He hired one of its early visionaries, Yann LeCun, to lead the charge. Now, just months after OpenAI’s ChatGPT burst into the consumer marketplace, Meta is falling behind in the very same technology.

Meta is now scrambling to refocus its resources to generate usable AI products and features, including its own chatbots, after spending years prioritizing academic discoveries and sharing them freely while struggling to capitalize on their commercial potential.

That’s a tall order as many of Meta’s top AI employees have departed and amid the company’s own sets of layoffs in what Zuckerberg has called a “year of efficiency.” About a third of Meta workers who co-authored published AI research related to large language models—the complex systems that power AI systems like ChatGPT—have left in the last year, according to a Wall Street Journal analysis.

Zuckerberg himself and other top executives have taken more control of the company’s AI strategy. They created a new generative AI group that reports directly to Chief Product Officer Chris Cox, one of the longest-serving and most trusted executives at Meta. The group is training generative AI models—which produce content, such as text, images or audio—intended to be infused into “every single one of our products,” Zuckerberg said. He has touted Meta’s flagship AI language model, called LLaMA, which — after its code leaked— spurred the emergence of homegrown tools that could one day compete with the products that Google and OpenAI are trying to sell.

If Meta succeeds in commercializing its AI efforts, it could help boost its user engagement, create a better metaverse and make the company more attractive to the young users who are now proving harder for it to attract. If Meta can’t capitalize on this technology fast enough, it runs the risk of losing relevance as competitors, including a fast-growing crop of scrappy AI startups, leap ahead.