In this episode, we sit down with equity analyst Joshua Samuel to explore how artificial intelligence and large language models (LLMs) are fundamentally reshaping the nature of competitive advantages tied to data. Josh presents a comprehensive framework for evaluating data moats in the modern era, breaking down four critical categories that can separate lasting advantages from temporary ones. The conversation examines how companies across sectors—from FinTech to defense—are leveraging data to drive better decision making and outcomes. He also addresses the flip side: where traditional data advantages are being eroded by AI's ability to synthesize information, and why trust and execution remain crucial even amongst data advantages. Key Highlights:

• AI systems now capture and analyze subconscious behavior patterns through clicks and scrolls, potentially knowing users better than they know themselves
• Traditional data moats in legal, medical, and scientific databases face existential threats as LLMs trained on humanity's collective knowledge can synthesize equivalent insights
• General-purpose AI can outperform specialized systems by piecing together disparate information, even without access to proprietary datasets
• In high-stakes B2B environments, established relationships and trust remain powerful defenses against AI disruption, especially where career risk is involved

• Examines Tencent as a rare example of a company that combines all four dimensions of a strong data moat—proprietary, continuously refreshed, high‑dimensional, and closed‑loop data—spanning social, payments, commerce, and mini‑program ecosystems.

Host: Rob Campbell, CFA Portfolio Manager Guest: Joshua Samuel, CFA Equity Analyst

This episode is available for download anywhere you get your podcasts.

Founded in 1974, Mawer Investment Management Ltd. (pronounced "more") is a privately owned independent investment firm managing assets for institutional and individual investors. Mawer employs over 250 people in Canada, U.S., and Singapore.

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