In short

The debut Tech Futures Project roundup surveys four developments revealing global divergence on AI: Chinese universities and the public embrace AI far more than Western counterparts (80% enthusiasm vs 38% UK, 25% US); tax systems lag a data-driven digital economy, prompting calls for data and capital taxes; soaring AI fundraising raises bubble fears, though tempered by real revenues; and a METR study finds experienced developers work ~19% slower with AI tools.

The first Tech Futures Project newsletter sets the template: four data points that each puncture a comfortable assumption about AI.

The most counterintuitive is the METR study finding that experienced developers were slower with AI tools on familiar tasks, while being convinced they were faster. That gap between felt and actual productivity is one of the most important under-discussed facts about this moment. Alongside it: the striking enthusiasm gap between China and the West, the mismatch between a data-driven economy and tax systems built for physical goods, and the question of whether sky-high AI fundraising is a bubble (with the important caveat that, unlike 1999, these companies have real revenue).

It closes on energy, and the crucial point that AI’s power demand isn’t spread evenly but concentrated in a handful of places, where it’s already reshaping national grids.

Key takeaways

  • AI enthusiasm diverges sharply by country (China 80%, UK 38%, US 25%), with Chinese universities deploying rather than resisting AI.
  • A METR study found experienced developers were ~19% slower using AI tools on familiar tasks.
  • Data-driven digital economies escape traditional tax frameworks, motivating proposals for data and capital taxes.
  • AI may be a bubble, but unlike the dot-com era major labs generate real revenue and profit.
  • AI's energy demand is geographically concentrated (Ireland ~22% of electricity to data centres vs ~2% UK/France).

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Frequently asked questions

Does AI make software developers more productive?
Not always. A METR study found experienced developers were about 19% slower when using AI tools on tasks they already knew well, despite believing they were faster.
Which countries are most enthusiastic about AI?
Per Stanford's 2025 AI Index, China leads at ~80% enthusiasm, well ahead of the UK (38%) and US (25%).
Is AI in a financial bubble?
There are bubble-like signs in fundraising, but unlike the dot-com boom leading AI labs generate substantial real revenues, which tempers the comparison.

People & ideas in this piece

METRStanford HAI2025 AI Index ReportAmanda ParsonsNathan LambertAI bubbleDeveloper productivityData taxation

Topics: AI & Geopolitics , AI, Work & the Economy