A year after Mark Zuckerberg spent more than $14 billion to bring Alexandr Wang into Meta’s artificial intelligence push, the company has moved from building its flagship AI model to confronting a harder challenge: convincing the market it can turn that technology into a profitable business.

The investment marked the start of a major internal overhaul aimed at strengthening Meta’s position in the global AI race. Wang, together with a team of engineers from Scale AI, was tasked with developing a new foundation model to compete with leading players in the sector, including OpenAI, Google, and Anthropic.

That effort led to the rollout of Muse Spark in April, Meta’s proprietary AI model designed to power its platforms, including Facebook and Instagram, as well as emerging AI-driven products and devices. The launch signaled a shift from the company’s earlier reliance on open-source systems toward more controlled, in-house development.

However, attention has now turned to monetization. Meta remains heavily dependent on advertising, which accounts for about 98 percent of its revenue, prompting questions on how its AI investments will translate into new income streams.

“Meta needs to provide more proof points of both adoption and commercialization,” said Ralph Schackart, an analyst at William Blair who recommends buying the stock. “Investors are looking for Meta to monetize a new AI-first product, beyond the substantial positive impact AI is having on enhancing the advertising models.”

Despite strong overall revenue growth, Meta’s stock has lagged behind other major technology firms over the past year, reflecting investor skepticism over its ability to compete at the highest level of the AI market.

Developer sentiment has also become a key concern. Meta’s earlier Llama open-source strategy initially attracted strong interest but failed to maintain momentum, while its newer proprietary approach has yet to fully rebuild trust within the developer community.

“I think the AI community largely ignores Meta at this point,” said Rob May, chief executive officer of Neurometric.

Krish Subramanian, CEO of KOI AI, noted that competition remains intense across the industry, particularly from companies with stronger developer ecosystems. “The lack of developer trust will come back to hit them if they don’t focus on third-party developers,” he said, warning that a closed ecosystem could limit long-term growth.

Meta has begun introducing subscription-based AI services and plans to expand external access to its models through application programming interfaces, but analysts say the company still faces a steep climb in establishing a clear monetization path.

“There’ll be a lot of these frontier model providers that will fundamentally change in lots of different ways, and Meta needs to have a consistent, reliable proprietary model that they themselves own,” said Thomas Randall, an analyst at the Info-Tech Research Group.

For now, the company’s challenge is no longer about building competitive AI systems, but proving that its multibillion-dollar investment can translate into sustainable earnings in an increasingly crowded artificial intelligence market.