If I had to rank the AI chain today, I would separate it into three buckets:
1. Power & infrastructure (highest conviction, longest runway)
The market spent 2023-2025 obsessing over GPUs. The next bottleneck is increasingly electricity, cooling, transformers, grid upgrades, and data centre infrastructure. Goldman Sachs estimates data centre power demand could rise over 200% by 2030.
Names and themes linked to power, cooling, nuclear, and digital infrastructure may have a more durable runway because AI cannot scale without physical energy and facilities.
2. Memory & storage (strongest momentum)
HBM has become the critical bottleneck in AI servers. New memory-focused ETFs such as DRAM have attracted enormous inflows and delivered explosive gains.
The risk: memory is still a cyclical industry. Today’s pricing power can become tomorrow’s oversupply.
3. Optical networking / photonics (most interesting asymmetric bet)
If GPU clusters keep scaling, bandwidth becomes the next constraint. Silicon photonics and optical interconnects could see a multi-year demand wave as AI clusters expand.
As for stocks vs thematic ETFs, it depends on where you think we are in the cycle.
Early cycle: stock picking often wins because leaders massively outperform.
Mid-to-late cycle: ETFs become more attractive because winners rotate unexpectedly.
Right now, AI feels less like a pure compute story and more like an infrastructure buildout story. My preference would be:
1. Power/infrastructure ETFs
2. Optical/photonics exposure
3. Memory ETFs
4. Data centre REITs
5. Space-related AI themes
Space is the most exciting narrative, but also the most speculative. Power is the least exciting narrative, yet arguably the most unavoidable. In megatrends, the boring bottlenecks often end up generating the most durable returns.
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