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Everyone wants a piece of the AI boom. But picking the next big AI winner is harder than it looks. Models change, startups rise and fall, and today's leader can become tomorrow's afterthought.
That's where the "picks and shovels" strategy comes in. The name comes from the California Gold Rush, where merchants selling tools often made more money than the miners themselves. The same logic applies to AI. Instead of betting on which chatbot or software company will dominate, you invest in the infrastructure that powers all of them.
In this guide, we'll break down how this approach works and what types of companies fit the strategy.
The picks and shovels approach focuses on companies that enable an industry rather than compete within it. During the Gold Rush, the real fortunes were made by those selling equipment to miners, not the miners themselves.
Applied to AI, this means investing in the companies building chips, running data centers, generating power, and manufacturing cooling systems. These businesses have guaranteed demand because every AI company needs their products.
Bottom Line: You don't need to predict which AI company will win. You just need to recognize that all of them need infrastructure.
Investing directly in AI software companies or model developers carries significant uncertainty. The technology evolves quickly, competition is fierce, and profitability remains unclear for many players.
Infrastructure companies face less of this uncertainty. They sign long-term contracts, serve multiple customers, and generate revenue today rather than betting on future adoption. Whether OpenAI, Google, or a startup you've never heard of ends up dominating, they all need chips, servers, and electricity.
Check out Navigating the AI Landscape: Perspectives on the Potential Risks and Benefits to learn more about evaluating AI investments.
No AI system runs without chips. Graphics processing units (GPUs) and custom accelerators handle the massive computational demands of training and running AI models. This makes semiconductor companies the most direct picks and shovels play.
The opportunity extends beyond chipmakers themselves. Equipment manufacturers that build the machines used to produce advanced chips occupy a unique position. Without their tools, cutting-edge chips simply cannot be made. Foundries that fabricate chips for multiple companies also benefit regardless of which designs succeed.
Key areas to watch include GPU and accelerator manufacturers, chip fabrication equipment companies, and semiconductor foundries.
AI data centers consume enormous amounts of power. Training large models requires sustained computational effort across thousands of chips, and the energy demands keep growing. This has turned power generation into an unexpected AI investment theme.
Utilities with reliable baseload generation, particularly nuclear power, have become attractive to hyperscale data center operators. Some tech companies are signing long-term power purchase agreements directly with energy providers to secure capacity. Explore How to Identify a High Growth Sector to learn how to spot emerging opportunities like this one.
Bottom Line: The AI boom is also an energy boom. Companies that can deliver reliable, large-scale power stand to benefit for years.
All that computing generates heat. Lots of it. Traditional air cooling systems struggle to handle the thermal output of dense AI server clusters. This has created strong demand for advanced cooling solutions, particularly liquid cooling technology.
Companies specializing in thermal management for data centers have seen their order books fill up. As chip density increases and AI workloads intensify, cooling becomes an even more critical bottleneck.
AI workloads need physical homes. Data centers house the servers, storage, and networking equipment that make AI possible. The major cloud providers are spending heavily to expand capacity, and specialized data center operators are benefiting from this buildout.
Networking equipment also plays a crucial role. AI training requires moving massive amounts of data between chips and servers at high speeds. Companies building high-performance switches, routers, and interconnects enable this data flow.
Direct bets on AI software, model developers, or application companies offer higher potential upside if you pick the right winner. But they also carry more risk. The competitive landscape shifts quickly, and profitability for many AI companies remains unproven.
Infrastructure plays typically offer more stable returns with lower volatility. These companies have established business models, recurring revenue, and less dependence on any single AI outcome. The tradeoff is that you may miss the explosive gains that come from identifying the next dominant AI platform.
Most investors benefit from a balanced approach. Infrastructure provides stability while selective direct exposure can capture additional upside.
Not all infrastructure plays are created equal. Before investing, consider the company's competitive position and whether it faces meaningful competition. Evaluate customer concentration and how reliant the business is on a small number of buyers. Examine valuation to determine if growth expectations are already priced in. Look at contract visibility to see if the company has long-term agreements that provide revenue certainty.
The best picks and shovels investments combine strong market positions with reasonable valuations and diversified customer bases. Check out Deep Research in Investing to learn how thorough analysis can improve your investment decisions.
If you believe AI will continue growing but don't want to bet on individual winners, infrastructure investing offers a compelling alternative. You gain exposure to the AI megatrend while reducing the risk of picking the wrong horse.
This approach works best for investors who want AI exposure without excessive volatility, prefer companies with proven revenue over speculative bets, and have a long-term investment horizon.
Start by understanding the different infrastructure categories and identifying companies with durable competitive advantages. From there, you can build a diversified portfolio that benefits from AI growth without requiring you to predict which specific companies will dominate. Get the Prospero.ai app today and make smarter trading decisions with data-backed insights.
What does "picks and shovels" mean in investing?
It refers to investing in companies that supply tools or infrastructure to an industry rather than competing directly within it. The term comes from the Gold Rush, where equipment sellers often profited more than miners.
What types of companies count as AI picks and shovels?
Semiconductor manufacturers, chip equipment makers, power utilities, cooling system providers, data center operators, and networking equipment companies all qualify as AI infrastructure plays.
Is this strategy less risky than investing directly in AI companies?
Generally yes. Infrastructure companies have more predictable revenue, serve multiple customers, and don't depend on winning the AI software race. However, valuation risk still exists if expectations get too high.
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