A monthly read on who is winning the race for artificial intelligence — scored across the four long-term drivers that decide it: energy, compute, adoption and talent.
Each month this scorecard highlights the most important developments affecting each country’s AI competitiveness — then scores the month, driver by driver. Advances and setbacks are graded per country: green moves that nation forward, red holds it back.
Training and running frontier models consumes enormous power. The nation that builds abundant, affordable and reliable electricity fastest can field the largest AI systems.
Advanced semiconductors, frontier models and data centers are the raw horsepower of AI. Leadership across the compute stack sets the pace for everyone else.
Capability only counts once it is deployed — across businesses, government and allied nations. Widespread use, plus exporting the AI stack abroad, converts research into real advantage.
AI is built and sustained by people: researchers, engineers and the skilled tradespeople who construct and power data centers. A deep talent pipeline protects leadership over the long run.
China made more net progress toward AI leadership in July — launching a 29-nation AI governance bloc, closing the compute gap with competitive open-weight models and a new domestic supercomputer. The United States advanced on energy policy, federal siting and skilled-trades funding, but state and local restrictions kept slowing data-center development.
New executive action requires data-center operators — not ratepayers — to fund the power and infrastructure their AI projects need.
Consumption is projected to climb from roughly 183 to 426 terawatt-hours, with new generation not on pace. PJM, the nation’s largest grid, keeps missing supply targets.
Installed generation capacity hit four billion kilowatts (+10.8% year over year) — nearly double its own demand growth.
The IEA finds China’s 2026 electricity demand is rising three times faster than that of the United States, and supply is meeting it.
Local opposition continues to slow AI-infrastructure buildout nationwide, with some states moving to freeze — or considering freezing — new projects.
Faster siting on federal land — former industrial areas, power-generation facilities and dormant sites — aims to unstick permitting bottlenecks.
CHIPS Act funding for next-generation chip packaging, AI memory and more, aimed at cutting U.S. reliance on foreign suppliers for critical compute.
A coordinated national effort treats domestic AI-chip independence as a mandate, not a business decision.
A coordinated national effort treats domestic AI-chip independence as a mandate, not a business decision.
Multiple Chinese chipmakers showcased large-scale AI systems built entirely on domestic chips, underscoring Beijing’s push to replace U.S. technology across the stack.
Washington countered Beijing’s bloc by rallying 35 partner nations behind its own vision for open, democratic AI adoption.
steep jump from 55 percent a year ago as AI spreads across the broader U.S. economy.
A new Shanghai-based body works to expand Beijing’s influence over global AI standards and adoption, especially across the Global South.
A cross-agency initiative blends federal compute, data and research infrastructure with AI to tackle grid planning, microelectronics and manufacturing.
Meta, Google and BlackRock fund electrician and carpenter pipelines for the data-center boom.
A new policy push channels a record graduating class toward AI-related occupations and continuous learning.
China made more net progress toward AI leadership in July — launching a 29-nation AI governance bloc, closing the compute gap with competitive open-weight models and a new domestic supercomputer. The United States advanced on energy policy, federal siting and skilled-trades funding, but state and local restrictions kept slowing data-center development.
China made more net progress toward AI leadership in July — launching a 29-nation AI governance bloc, closing the compute gap with competitive open-weight models and a new domestic supercomputer. The United States advanced on energy policy, federal siting and skilled-trades funding, but state and local restrictions kept slowing data-center development.
China made more net progress toward AI leadership in July — launching a 29-nation AI governance bloc, closing the compute gap with competitive open-weight models and a new domestic supercomputer. The United States advanced on energy policy, federal siting and skilled-trades funding, but state and local restrictions kept slowing data-center development.
China made more net progress toward AI leadership in July — launching a 29-nation AI governance bloc, closing the compute gap with competitive open-weight models and a new domestic supercomputer. The United States advanced on energy policy, federal siting and skilled-trades funding, but state and local restrictions kept slowing data-center development.