Meta Captures Employee Keystrokes and Screens to Train Its "AI for Work" Agents

Meta began deploying tracking software on U.S. employee computers in the week of April 21, capturing mouse movements, keystrokes, clicks, and periodic screenshots to feed into its AI training pipeline. The tool is called Model Capability Initiative (MCI), and it runs inside Meta's Agent Transformation Accelerator (ATA) — the company's internal program to build AI agents that can perform knowledge work tasks autonomously. The rationale is straightforward: to train AI agents that are good at work, you need data from actual work being done. Most AI models are trained on internet text and code. Meta believes that data showing how expert humans navigate complex software, make decisions in business tools, and move between apps contains knowledge that internet data doesn't capture. The scope: MCI runs on work-related apps and websites. It does not run on personal apps. Meta disclosed the program to employees via internal memo. The strategic context: Meta CEO Mark Zuckerberg has committed up to $135 billion in capital expenditure for 2026, with AI infrastructure as the primary target. Scale AI, in which Meta holds a 49% stake, is central to the data labeling pipeline. Meta Superintelligence Labs — led by Scale AI's former CEO Alexandr Wang — is the team coordinating the effort. For anyone building enterprise AI products, this is a signal about where the next moat is: proprietary behavioral data from actual workers doing actual tasks. Pure text training is a commodity. Behavioral workflow data is not. Meta is betting that owning this data at scale, before competitors do, is the foundation of the next generation of work AI.