Why Meta wants to impose a social AI before making it a useful AI

The launch of the Meta AI autonomous application last night, marks a major strategic inflection for the Mark Zuckerberg group. Far from a simple conversational assistant, the application claims a double ambition: become an omnipresent personal companion and anchor in a social logic, strongly connected to the Meta ecosystem. Behind the technical varnish and the opening of the LLAMA 4 model, it is an attentional capture project that is emerging, based on community engagement before the functional value.

A vocal assistant disguised as a social network

Available on iOS, Android and Desktop, the META AI application offers classic features of an AI assistant (text generation, images, or even short videos) enriched with an interactive vocal mode. But its originality lies in the Discoversa tiktok type interface where users can publish, like, comment or remix creations generated via AI.

Far from a private decision -making or productivity tool, Meta Ai is moving towards public and socialized usewhere AI becomes a pretext to interact, expose themselves, share. Meta here reproduces a well -offed scheme: promoting viral content, collecting interactions, strengthening attachment to its platform. AI is not first thought of as a useful interface, but as a new vector of engagement.

Unprecedented vertical integration

Meta’s strength lies in its vertical integration: the new application dialogues with Ray-Ban Meta connected glasses, takes up the conversation historicals on the web, and relies on Facebook and Instagram profiles to customize the answers. AI is not only vocal or visual: it is contextual, social and on -board in the daily life of users.

But this integration raises questions: some settings activate automatic sharing on networks by default, vocal listening remains active without explicit deactivation control, and system memory, although theoretically deactivated, can be activated manually without the duration of retention being specified.

A make -up catch -up strategy in vision

Faced with Openai (Chatgpt), Google (Gemini) or Xai (Grok), Meta accuses a certain delay in the field of advanced IA uses. Rather than competing head on assistants already anchored in professional or personal workflows, Meta opts for A gentle infiltration strategy : deploy AI where users are already, in a familiar, socialized and visually attractive setting.

The choice of Open Source Model Llama 4 partially mask this discrepancy. If the technology is solid, it is not yet up to the performance or reliability standards required for a high -level assistant. The objective, for Meta, is less to become the most powerful AI than theThe most integrated AIthat which is imposed by continuous presence in the user environment.

A light for light use, not yet essential

In use, the application turns out to be fluid, fast and accessible. The images generated are of good quality, the voices (some of which are celebrities) strengthen the proximity effect, and the application offers a homogeneous experience between mobile, desktop and glasses. But The real utility remains superficial. The conversations are brief, the responses not very contextualized, and the lack of real -time access to the Internet or to documentary bases limits concrete use cases.

The current model is aimed at a consumer audience, a follower of short formats and playful uses. Meta Ai, as it stands, is not Neither a work co -pilot nor an advanced search enginebut a recreational conversational interface, designed to prolong the time spent in the Meta ecosystem.

AI as a media before being a tool

Meta does not try to compete with Chatgpt in the field of performance, but to impose a new form of AI consumption : social, visible, community. AI becomes a full media, and the user, a creator of Disnounceable IA content in the network.

In this model, The usefulness is secondaryas long as the commitment is there. In this, Meta remains faithful to its corporate culture: maximizing retention, measuring interaction, capitalizing on behavioral data. The bet is clear: make AI a vector of social attention before making it a tool for personal or professional transformation.