How AI Diffusion Shapes Economic Competition

This report features an interview with political scientist Jeffrey Ding, who argues that long-term AI leadership will be determined by economic diffusion rather than frontier innovation. Investors are encouraged to monitor skill infrastructure and real-world adoption metrics over model-specific performance.

Key Takeaways

• 1.National AI power is determined by 'diffusion'—how technology spreads to the broader economy—rather than just innovation speed at frontier labs.
• 2.The US holds an advantage in the AI 'diffusion marathon' due to existing infrastructure and institutional linkages, whereas China faces hurdles in enterprise adoption.
• 3.Useful AI metrics include human capital (talent flows) and token usage; survey-based sentiment data should be treated with skepticism.

Table of Contents

• Everything, everywhere, but not all at once
• How should we evaluate a country or company's skill infrastructure?
• What research question most interests you right now?
• Disclaimer