AI in investment management: 5 lessons from the front lines
By integrating AI alongside human oversight, adopting a critical thinking mode, and adapting to regulations, investors can benefit from its huge potential
ARTIFICIAL intelligence (AI) is reshaping many traditional processes and decision-making frameworks in investment management. Here’s a look at the technology’s transformative impact on the industry, focusing on its applications, limitations and implications for professional investors.
Lesson #1: Augmentation, not automation
AI’s primary value in investment management lies in augmenting human capabilities rather than replacing them. According to a 2025 European Securities and Markets Authority report, only 0.01 per cent of 44,000 UCITS – Undertakings for Collective Investment in Transferable Securities – funds in the European Union explicitly incorporate AI or machine learning (ML) in their formal investment strategies.
Despite this marginal adoption, AI tools, particularly large language models (LLMs), are increasingly used behind the scenes to support research, productivity and decision-making. For instance, generative AI assists in synthesising vast datasets, enabling faster analysis of market trends, regulatory documents or ESG metrics.
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