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Amid uncertainty about which AI applications will win, Blackstone's strategy is to invest in the essential infrastructure all AI companies need. This "picks and shovels" approach targets data centers and electricity, guaranteeing exposure to the boom without betting on specific, high-risk application companies.
While AI chips represent the bulk of a data center's cost ($20-25M/MW), the remaining $10 million per megawatt for essentials like powered land, construction, and capital goods is where real bottlenecks lie. This 'picks and shovels' segment faces significant supply shortages and is considered a less speculative investment area with no bubble.
Current M&A activity related to AI isn't targeting AI model creators. Instead, capital is flowing into consolidating the 'picks and shovels' of the AI ecosystem. This includes derivative plays like data centers, semiconductors, software, and even power suppliers, which are seen as more tangible long-term assets.
A safer way to play the AI boom is to invest in companies selling the underlying compute infrastructure rather than the hyperscalers buying it. This strategy captures the upside of the secular trend while avoiding direct exposure to how the massive capital expenditure is funded, which may involve risky credit.
Instead of betting on specific AI models like ChatGPT, a more robust strategy is to invest in the underlying infrastructure that all AI development requires. This 'onion' approach focuses on second-order essentials like semiconductors and data centers, which are poised to grow regardless of which consumer-facing application wins.
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.
By investing billions in both OpenAI and Anthropic, Amazon creates a scenario where it benefits if either becomes the dominant model. If both falter, it still profits immensely from selling AWS compute to the entire ecosystem. This positions AWS as the ultimate "picks and shovels" play in the AI gold rush.
Rather than picking a winning AI or crypto, the smarter investment is in the 'picks and shovels.' This means focusing on the infrastructure every autonomous agent will require to transact—such as wallets, custody services, and blockchain rails—regardless of which specific application succeeds.
To capitalize on the AI boom while mitigating risk, investors should focus on 'enablers'—companies providing essential infrastructure like semiconductors, data centers, and cloud services. This 'picks and shovels' strategy avoids betting on specific application-level winners, which was a losing strategy for many dot-com investors.
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.