01 · Competitive power
AI labs and Big Tech
An AI lab's power depends on five connected resources: models, talent, capital, compute capacity and distribution.
Open the analysis →Latest related dossierSVC-052 · 09 OCT 2026
Intelligence map · Central entity
Who controls the AI industry
The artificial intelligence industry cannot be understood through isolated launches. Power is divided among those who control models, talent, capital, compute, distribution and political permission.
Analysis by Jose Luis Cases from an executive, technology and product perspective: connecting capital, infrastructure, incentives and outcomes instead of repeating press releases.
Six areas of power01—06
02 · Real metrics vs PR
Economics and capital
AI economics measures how funding, valuations, debt and capex do—or do not—turn into revenue, margin and market power.
Open the analysis →Latest related dossierSVC-041 · 13 JUN 2026
03 · The physical layer
AI infrastructure
AI infrastructure comprises chips, cloud, data centers, energy and manufacturing: the physical layer constraining cost, scale and sovereignty.
Open the analysis →Latest related dossierSVC-053 · 16 OCT 2026
04 · AI as a state asset
Geopolitics and regulation
Frontier AI is no longer distributed by technical capacity or demand alone: governments, defense, export controls and regulation determine who can build and use it.
Open the analysis →Latest related dossierSVC-045 · 12 JUL 2026
05 · Workforce transformation
AI, work and organizations
Enterprise AI adoption changes headcount, tasks, costs and power structures before there is a single reliable measure of productivity.
Open the analysis →Latest related dossierSVC-036 · 10 MAY 2026
06 · From models to the world
Products, agents and robotics
AI products move model capabilities into software, agents, vehicles, devices and robots, where adoption and failures become measurable.
Open the analysis →Latest related dossierSVC-022 · 31 JAN 2026