Utility Stocks May Be Safer AI Play Than Nvidia, Analyst Says

An investor is making an unconventional case for profiting from artificial intelligence growth: skip the chipmakers entirely and invest in the utilities that power them.

The argument centers on a fundamental reality of AI infrastructure. While companies like Nvidia currently dominate AI chip production, their market position faces constant competitive pressure. Intel once held similar dominance in semiconductors before being overtaken. But regardless of which chipmaker ultimately prevails, every AI data center requires one constant input: electricity.

The pick-and-shovel approach

The investment thesis draws on a gold rush analogy. During the California gold rush, miners faced uncertain prospects of striking it rich. The merchants selling picks and shovels to those miners, however, had reliable revenue regardless of any individual miner's success.

Applying this logic to AI infrastructure, the investor argues that utility companies represent the picks-and-shovels play. If AI growth continues as projected, electricity demand surges. If the AI boom disappoints, utilities still provide essential services to the broader economy.

The investor holds positions in three utility companies: Brookfield Renewable Partners, Southern Company, and Black Hills. Black Hills qualifies as a Dividend King, having increased its dividend for more than 50 consecutive years. Brookfield Renewable focuses on clean energy sources including wind and solar.

A combined bet on AI power needs

For investors seeking single-stock exposure to AI electricity demand, the investor highlights NextEra Energy as a comprehensive option. The company operates both a large regulated utility business and ranks among the world's largest producers of renewable energy from solar and wind sources.

This structure essentially combines the characteristics of traditional utilities with renewable energy infrastructure in one investment, according to the analysis.

Why it matters

The utility-focused strategy reflects growing recognition that AI's infrastructure requirements extend far beyond semiconductors. Data centers training large language models consume enormous amounts of electricity, creating potential bottlenecks as AI deployment accelerates. Major technology companies are already striking power purchase agreements and exploring dedicated energy sources including nuclear power. For investors uncertain about which AI chipmaker will dominate long-term, utilities offer exposure to AI growth without requiring correct predictions about specific technology winners.

This analysis was originally published by AI Watch on Yahoo Finance.