Contrary to sci-fi tropes, AI's most impactful military use is as a bureaucratic technology. It excels at tedious but vital tasks like report generation, sanitizing intelligence for allies, and processing data, freeing up human operators rather than replacing them in combat.

The military's AI use is overwhelmingly focused on non-lethal applications like logistics and processing intelligence data. The 'pointy end' of autonomous weapons represents just one small category within a much broader AI strategy that mirrors corporate use cases.

McKinsey's global managing partner now considers AI agents part of the company's headcount. The firm rapidly scaled from 3,000 to 20,000 agents in just 18 months, viewing them as essential 'employees' that augment their human workforce, and expects to reach a 1:1 human-to-agent ratio by 2026.

The nature of enterprise AI use has fundamentally shifted at high speed. Agentic workflows, which accounted for only 13% of AI work in February, skyrocketed to 64% by June. This rapid 'flippening' shows companies are quickly moving from simple assistance to delegating high-volume, complex tasks to AI.

The initial enterprise AI wave of scattered, small-scale proofs-of-concept is over. Companies are now consolidating efforts around a few high-conviction use cases and deploying them at massive scale across tens of thousands of employees, moving from exploration to production.

The Department of War's secure "GenAI.mil" tool was developed in just 60 days by a tiger team of ex-Big Tech engineers. It achieved massive adoption, reaching one-third of the 3-million-person organization within a month of launch.

A simple framework to estimate AI's current economic impact multiplies three key metrics: the percentage of workers using AI (~40%), their weekly usage intensity (~2 hours), and the average task efficiency gain (15-30%). This calculation reveals a modest but tangible current productivity increase.

A study of 21,000 firms found that companies spending the most on AI actually grew headcount by 10% over two years, with entry-level roles growing even faster. This data directly contradicts the dominant media narrative that AI adoption is currently causing widespread job loss.

The concept of a massive "agentic workforce" is not a distant future scenario but a current reality. Companies are already deploying systems with up to 70,000 AI agents running simultaneously. This rapid, large-scale adoption indicates the transition is happening much faster than commonly perceived, creating urgent infrastructure needs.