Analyst Warns of Infrastructure Bottlenecks Amid AI's $8 Trillion Growth
AI's $8 Trillion Buildout Is Not A Bubble – It's A Bottleneck, Analyst Says

Image: Benzinga
Jordi Visser, head of AI Macro Nexus Research at 22V Research, argues that the AI sector faces significant infrastructure bottlenecks, with only 12% to 18% of an $8 trillion buildout completed. He emphasizes that this is a physical-world capital expenditure cycle rather than a software boom, warning investors to respect the associated risks.
- 01Only 12% to 18% of the projected $8 trillion AI infrastructure buildout has been completed.
- 02Bottlenecks are evident in high-bandwidth memory chips, cooling systems, and power infrastructure.
- 03Visser notes that AI spending is now dependent on physical construction and energy systems, similar to a 1970s industrial cycle.
- 04Despite risks, major players like Nvidia Corporation maintain strong market positions.
- 05Visser suggests focusing on platform companies and energy infrastructure rather than memory trades.
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Jordi Visser, head of AI Macro Nexus Research at 22V Research, warns that the artificial intelligence sector is not running out of funding but is facing critical infrastructure bottlenecks. He estimates that only 12% to 18% of the anticipated $8 trillion infrastructure buildout has been completed, with supply chain stresses already visible. Key components such as high-bandwidth memory chips and power infrastructure are in short supply. Visser highlights that the current AI investment cycle resembles a 1970s industrial cycle, driven by physical construction and energy demands rather than purely software advancements. He notes that while the S&P 500 remains strong, there are concerning signs of divergence in semiconductor and industrial markets, particularly in Japan and South Korea. Despite these challenges, Visser believes that the AI trade is not collapsing, as spending is backed by major companies with substantial cash flows. He advises investors to focus on platform and connectivity firms, as well as independent power producers, while being cautious of speculative trends in memory-related trades.
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The infrastructure bottlenecks may lead to delays in AI product deliveries, affecting companies reliant on timely supply chains.
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