The Promise and Perils of AI in Institutional Investing

Artificial intelligence and large language models are transforming many industries, and institutional investing is no exception. AI offers tantalizing potential to analyze data, find insights, and create efficiencies in the investment process. However, experienced investors caution that relying too heavily on AI comes with substantial risks.

On the promise side, AI could take over repetitive analytical tasks, freeing up investor time for higher-level thinking and decision-making. As Adrian Ohmer of the Kresge Foundation stated, AI could become “the next Bloomberg” – a ubiquitous analytical tool across the industry. Others see AI accelerating and enhancing data analysis in areas like screening potential investments.

But veterans warn that AI lacks human discernment and nuance. As Carmen Lugo of the Fondo de Ahorro de Panamá put it, “human expertise and judgment will remain essential and cannot be replaced.” Investors emphasize that fiduciary responsibility demands understanding the rationale behind AI system outputs before acting upon them.

Some also worry that over-reliance on AI risks depriving the next generation of investors of the hands-on analytical experience that builds judgment. As John Pearce of the Illinois Municipal Retirement Fund argued, “Being overly eager to embrace generative AI for the foundational exercises of investing risks trading off near-term gains for long-term talent development problems.”

In the end, experienced investors view AI as a powerful tool, but not a substitute for human expertise. While AI will come to play an important role in areas like data analysis, responsibility for complex investment decisions will remain with seasoned professionals using both data and judgment. The message is clear – utilize AI carefully, but don’t hand over the investment reins.

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