Concerned about AI's potential to displace white-collar jobs, Wilkinson views investing in the underlying infrastructure as a key strategy. He specifically invested in a Bitcoin mining company pivoting to AI data centers, effectively buying into the "toll bridge" of the future to protect his capital.
During the dot-com crash, application-layer companies like Pets.com went to zero, while infrastructure providers like Intel and Cisco survived. The lesson for AI investors is to focus on the underlying "picks and shovels"—compute, chips, and data centers—rather than consumer-facing apps that may become obsolete.
Instead of betting on which AI models or applications will win, Karmel Capital focuses on the infrastructure layer (neocloud companies). This "pick and shovel" strategy provides exposure to the entire ecosystem's growth with lower valuations and less risk, as infrastructure is essential regardless of who wins at the top layers.
The tangible economic effect of the AI boom is currently concentrated in physical capital investment, such as data centers and software, rather than widespread changes in labor productivity or employment. A potential market correction would thus directly threaten this investment-led growth.
Bitcoin miners have inadvertently become a key part of the AI infrastructure boom. Their most valuable asset is not their hardware but their pre-existing, large-scale energy contracts. AI companies need this power, forcing partnerships that make miners a valuable pick-and-shovel play on AI.
Before AI delivers long-term deflationary productivity, it requires a massive, inflationary build-out of physical infrastructure. This makes sectors like utilities, pipelines, and energy infrastructure a timely hedge against inflation and a diversifier away from concentrated tech bets.
In an unpredictable AI-driven job market, the most reliable path to financial security is not a specific skill but owning assets. This allows individuals to participate in the massive wealth generated by the technology itself, providing a hedge against inflation and potential job displacement, and avoiding a future of dependency on government assistance.
Forget what executives say publicly. The massive capital allocation for AI data centers is the real evidence of impending job displacement. This level of investment only makes sense if companies expect significant cost savings from automating human labor, making capital the truest indicator of intent.
The advanced GPUs essential for AI require a fully globalized supply chain. As globalization breaks down, producing these chips may become impossible. Therefore, the current frenzied build-out of AI data centers, while a bubble, strategically installs critical infrastructure before the window of opportunity closes for good.
Michael Saylor’s adoption of Bitcoin for MicroStrategy's treasury wasn't just about inflation; it was a strategic pivot because AI and big tech were rendering his business model obsolete. Bitcoin, as a scarce asset, becomes an attractive safe haven for companies facing inevitable creative destruction from AI.
Permira's AI strategy uses a clear framework: invest in the 'picks and shovels' of compute (data centers) and in applications with unique, proprietary data sets. They deliberately avoid the hyper-competitive model layer, viewing it as a scale game best left to venture capital and strategic giants.