Rupal Agarwal: Gen AI in Asset Management

Asset management is shifting from basic AI productivity enhancements to sophisticated, agentic workflows aimed at generating unique alpha. Following 2025’s inflection point, 2026 marks a transition toward production-scale deployment, where firms prioritize structured AI change programs, robust governance frameworks, and human-in-the-loop controls. Senior Asia Quant Strategist Rupal Agarwal highlights innovative applications, such as using custom GPTs as "behavioral mirrors" to mitigate investor bias or as "Oracles" to synthesize historical investment wisdom. While large language models offer significant potential for analyzing unstructured data and sentiment, practitioners must navigate persistent challenges like look-ahead bias, non-deterministic outputs, and the necessity for auditable, source-grounded research. Ultimately, firms failing to integrate these technologies into their core processes risk significant competitive disadvantage as the industry moves toward a hybrid model of human and machine collaboration.