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Sound Advice: May 13, 2026

Here’s what you need to know about AI and AI investments:

AI is software that uses computers to do comprehensive research intended to provide favorable results.  But there’s a critical difference between favorable results and most favorable results.  That’s where human judgement comes in.  When seeking answers, people often use Google for information. The typical response is dozens, if not hundreds, of answers.  AI digests these answers and provides a summarized result.  What’s missing is human reasoning to determine the value of that research.

For investing, the most worthwhile AI exposure is usually the “picks and shovels” layer: companies that sell the chips, cloud, networking, and software infrastructure AI depends on.

AI in plain English

Think of AI as a very fast pattern-finding and prediction machine. It learns from lots of examples, then uses that learning to answer questions, recommend actions, automate work or create content.

A simple example: instead of a person reading thousands of customer emails and sorting them by urgency, an AI system can do that in seconds and keep improving as it sees more cases. That is why businesses use AI to save time, cut costs, and scale work.

Worthwhile AI investments

The most durable AI investments are often not the flashiest app names, but the firms supplying the infrastructure behind AI. Recent lists from Morningstar and Fidelity highlight Nvidia, Microsoft, Taiwan Semiconductor, Broadcom, Meta, Oracle, Adobe, IBM, and Tencent among notable AI-related companies.

A practical way to think about AI investing is:

  • Semiconductors: Nvidia, TSMC, Broadcom, Marvell. These benefit from demand for AI chips, packaging, and networking.
  • Cloud and platforms: Microsoft, Oracle, Alphabet, Amazon. These earn from AI services, data centers, and enterprise software adoption.
  • Software applications: Adobe, IBM, Meta. These can turn AI into productivity gains and monetizable products.

How to approach it

If you want simpler risk control, an AI-themed ETF can spread the bet across several companies instead of relying on one winner. Funds such as AIQ, WTAI, IGPT, and ARKQ are examples of AI-focused ETFs, though they can still be concentrated and volatile.

For most investors, the best approach is usually:

  1. Own a broad index fund first.
  2. Add a modest AI sleeve if you want extra growth exposure.
  3. Prefer companies with real earnings, pricing power, and infrastructure advantages over pure story stocks.

 What matters most

AI is a major theme, but not every “AI stock” is a good investment. The key question is whether the company can turn AI into durable profits, not just headlines.

 

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