Investment teams increasingly build and rely on their own AI tools, but the payoff depends on how deliberately a team reinvests the time that AI frees up. Emerging markets portfolio manager Wen Quan Cheong walks through how his team puts believability-weighted decision making into daily practice, and where AI has genuinely enhanced the process. He closes with a tour of the emerging-market themes he is watching most closely, from reshoring and clean-room capacity to physical AI, low-earth-orbit satellites, and businesses winning simply by putting the customer first. Above all, he returns to the idea that AI's real value lies in what a team chooses to do with the time it saves.

Key Takeaways

• The team practices believability-weighted decision making: deferring more to teammates with deeper expertise on a given name, while still doing enough independent work to spot blind spots.
• One of AI's biggest productivity gain so far for the team has been in forensic analysis, running deeper, more consistent checks across longer time periods than a human could alone, freeing up time for higher-value work like idea generation and company research.
• That saved time is meant to be reinvested, not banked: attending more conferences, joining more management calls, and turning insight generation itself into a discipline, described as "learning compression."
• On reshoring, the team sees opportunity less in the household names and more in the infrastructure behind the shift: industrial park developers, port operators, and specialized clean-room engineering firms like Acter Group and CTP.
• Beyond AI and reshoring, the team explores other areas such as physical AI and low-earth-orbit satellites, as well as EM businesses, such as NU Holdings, Bajaj Finance, and HDFC Bank, that win by being more customer-obsessed than entrenched incumbents.

Host: Rob Campbell, CFA Institutional Portfolio Manager Guest: Wen Quan Cheong, CFA Emerging Markets Portfolio Manager

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