AI can feel like magic: download an app, type a prompt, and you get an answer that would have sounded like science fiction not long ago. But we don’t invest in “magic” we invest in real businesses with real costs, real supply chains, and real expectations baked into stock prices. That’s why we step back and look at AI through a clearer lens: the full AI value chain, from semiconductors and GPUs to data centers, software, and the companies trying to turn AI into measurable productivity gains.

We walk through the two big compute phases that drive demand, training and inference, and why that matters for chip makers, cloud capacity, and the massive buildout of data center infrastructure. We also talk about why the market can swing so hard around AI-related stocks: new facilities take time to build, models may become more efficient, and investors keep asking whether hundreds of billions in AI spending will earn sufficient returns. Along the way, we connect today’s uncertainty to familiar market history, including dot-com era lessons about valuation, execution, and how long it can take for a new technology to translate into durable profits.

Finally, we bring it back to practical investing. Valuations are not a crystal ball, but they can help us choose an appropriate mix of assets, stay diversified, and keep our focus on long-term financial goals and legacy planning. If you want a smarter way to think about AI investing beyond the headlines, hit play, then subscribe, share the show, and leave a review so more people can find it.

Securities and advisory services offered through LPL Financial, a registered investment advisor. Member FINRA/SIPC.

The opinions voiced in this podcast are for general information only and are not intended to provide specific advice or recommendations for any individual. To determine which strategies or investments may suit you, consult the appropriate qualified professional before deciding.