Meta spent $14 billion on AI and a year later still hasn't taken off in the race

In the world of technology, having size, money, and resources does not always suffice to win all battles. Meta is proving this in the race for artificial intelligence. Despite having put at least $14.3 billion on the table, the company continues to struggle to position itself as a leading reference in chatbots and advanced models.

The most recent and striking move was the investment in Scale AI, a company specialized in data to train and improve AI systems. Meta acquired almost half of the company and, as a bonus, added its founder, Alexandr Wang, to lead efforts in superintelligence.

This bet was not only for labeled and curated data but also for key talent to accelerate internal development. It came at a complicated time, following the lukewarm reception of Llama 4 and with competitors like Google, OpenAI, and others setting the pace.

The new model and its deployment

A visible result of this stage is Muse Spark, the first model from the new family of Meta Superintelligence Labs. The company has already integrated it into Meta AI and is bringing it to WhatsApp, Instagram, Facebook, Messenger, and even its augmented reality glasses.

The great advantage of Meta is its enormous user base and the ability to distribute innovations directly on platforms that people already use every day. It does not need users to download a new app. However, turning that presence into habitual use and relevance is another story.

Muse Spark shows good results in language and visual comprehension, but falls behind in coding and abstract reasoning compared to market leaders. For now, it does not seem to be changing user habits when they think of a powerful chatbot.

A change in strategy

Unlike the open approach that characterized Llama, Muse Spark takes a more controlled path. It is a closed model, with access through a private preview API for selected partners. This decision marks a shift in how Meta seeks to compete.

The company can integrate AI into mass products, but the battle for public attention takes place in another arena: that of the names people mention first when they need intelligent help. There, ChatGPT, Gemini, Claude, and others continue to dominate the conversation.

Moreover, advertising remains the main revenue driver for Meta, adding pressure for AI investments to generate visible returns.

A year after these major bets, the company's position has not changed drastically. It continues to invest heavily and add pieces, but leadership in the generative AI race still seems distant. Silicon Valley repeatedly demonstrates that size does not guarantee victory when the board suddenly changes.

Meta has the resources and the channels. Now the key is to transform that infrastructure into an experience that truly convinces and retains users in their daily lives.