For many investors, emerging markets still conjure a reductive caricature: low-income economies, recurring political crises, heavy-handed governments, and returns that haven’t lived up to the hype. While that picture isn’t entirely wrong, it’s materially incomplete. Over the past three decades, the emerging world has shifted from the periphery of the global economy to its fabric: supplying critical components to the AI supply chain, incubating globally competitive consumer platforms, and hosting a growing share of the world’s middle class.

In investing, some ideas age gracefully. The notion that data can be a source of competitive advantage is one of them. But as artificial intelligence (AI) and large language models (LLMs) reshape the landscape, and, in particular, as market sentiment has shifted violently over the past few weeks against asset-light, software-based businesses, it’s worth asking: what does a true “data moat” look like today…and is it still as defensible as it once was?

In this episode, U.S. equity portfolio manager Grayson Witcher explores what it means to invest exclusively in American businesses at a time when the U.S. is becoming more short term, more transactional, and more central to global change. He contrasts a shifting U.S. “extraction” mindset with China’s longer-term industrial strategy and considers how that dynamic is reshaping globalization into a more regional, security-conscious world.