AI keeps getting more capable, so why isn't that showing up in the economic data yet? This report explains it through mismatched speeds. Title: The AI economy: Interconnected forces, feedback loops and speeds of change URL: ❓ Why doesn't AI's progress show up in the economy right away? AI capability — measured by the length of tasks models can reliably complete — has been doubling roughly every four months since 2023, but physical infrastructure like data centers expands only about 15% a year, and redesigning how organizations actually work takes even longer. Past general-purpose technologies took about a century (steam), 40 years (electricity), and 25 years (computers and the internet) to reach peak impact on growth — it's too early to know how much AI will compress that timeline. ❓ Where are the bottlenecks showing up? In 2023 it was Nvidia H100 chip packaging capacity, pushing lead times to as long as 11 months. Now it's electricity and data center sites: in Q1 2026 alone, at least 75 US data center projects worth roughly $130 billion were blocked or delayed by community opposition — matching all of 2025 in three months. The next constraints are likely to be applications, workforce skills, and organizational workflows. ❓ Adoption looks high, so why isn't it paying off for most organizations? By 2026, 89% of organizations used AI in at least one business function, but only 46% had moved past pilots, and just 6% qualify as "AI high performers" who've redesigned workflows around it. A big reason: responsibility for AI is fragmented across IT, legal, HR, and risk, with no single owner. 💡 So what should we actually do about it? The authors' advice: business leaders should look beyond efficiency to build new growth, not just cut costs; investors should follow the bottlenecks and expect different growth rates across the system; policymakers should keep regulation adaptive as constraints shift; and individuals should build AI fluency while sharpening the judgment AI can't replace. It's a good reminder of how much a systems view matters when everything is moving at a different speed. #AIEconomy# #SystemsThinking#