Meta and Mark Zuckerberg Train AI Assistant for CEO Functions

Mark Zuckerberg is turning himself into Meta's primary testing ground for AI experiments: the company is training a personal AI assistant that should take on some of the CEO's functions. This is not about a public chatbot for users, but an internal work tool that helps access information faster, consolidate data from different teams, and eliminate routine tasks that consume the time of a leader of a huge company. The project is at an early stage, but its logic is already clear.

The agent is being created as a digital chief of staff level assistant: it should find answers to questions that previously required a long chain of messages, approvals, and forwarding between departments. For Meta with its tens of thousands of employees, this is not a minor optimization, but an attempt to reduce management friction. The less time spent searching for statuses, figures, and context, the faster top management can move to decisions that cannot simply be delegated to an algorithm.

This experiment fits into Meta's broader restructuring around AI. Zuckerberg told investors back in January 2026 that this very year should radically change how work is organized in the company. Inside Meta, AI-native tools are already being deployed, and the organization itself is becoming flatter: the company is betting that individual strong specialists, enhanced by agents, will be able to close tasks that previously required large teams.

Chief Financial Officer Susan Li reported that since the beginning of 2025, output per engineer has grown by approximately 30%, and for the most active users of internal AI tools, annual growth reached about 80%. The scale of the bet is also important. According to Meta's official forecast, capital expenditures in 2026 will be between $115 and $135 billion compared to $72.

2 billion in 2025. This money goes not only to models and products for the external market, but also to internal infrastructure, without which the company cannot make AI a foundational layer of its everyday work. The idea is simple: if Meta wants to compete with more compact AI-native players, it needs not just to release models, but to change the very mechanics of managing a large corporation.

Inside the company, several classes of tools are already being tested for this. Some help find documents, correspondence, and internal knowledge, others act as personal assistants to employees and can interact with each other. Against this background, the CEO agent looks not exotic, but a logical continuation of the strategy: first Meta teaches AI to support regular team work, and then raises the same approach to the level of management.

In parallel, Western media also reported on another project — a more public AI version of Zuckerberg for communication with employees, trained on his manner of speech and public statements. But it is the working assistant for management tasks that looks more practical and closer to real effect. At the same time, it is important not to overestimate the autonomy of such a tool.

So far it is more about a system that accelerates information gathering and context preparation than a machine that makes strategic decisions for the head of the company. The choice between competing priorities, assessment of political risks within the organization, personnel issues, and responsibility to shareholders remain human functions. But even if AI takes only the layer of coordination, fact-finding, and initial analysis, this is already enough to noticeably change the role of middle and upper-level managers.

The key takeaway here is not that Meta is planning to replace the CEO with an algorithm. Much more important is something else: one of the world's largest technology conglomerates is testing whether agentic AI can be embedded directly in the management vertical and remove some of the bureaucracy without losing speed and control. If the experiment works, corporations will have a new standard for executive tools, and with it — pressure on all management that currently relies on status updates, conference calls, and manual context transfer.

If not, the market will sooner see the boundary beyond which even the most expensive AI runs up against human judgment.