Artificial intelligence has been conversation in quantitative finance for the past two years, but the gap between what people talk about and what people actually use remains wide. At Future Alpha 2026, a panel featuring Wangshu Yang of Goldman Sachs’ QIS Alternatives group, Oliver Faltin-Trager from Wellington Management’s fixed income research team, and Rahul Gupta from DRW’s quantitative research and trading desk.
The members of the panel sat down with moderator Dr. Charles Roberts, Chief Investment Strategist and Head of Private Assets at ARK Invest, to discuss what AI is doing for their investment processes today, where it is not making an impact, and why certain asset classes are more immune to AI disruption.
Where AI stands in finance, honestly
The panel started with a straightforward question: where is AI actually making a difference in finance right now?
The honest answer is that most of the gains are still in workflow. Writing research, cleaning data, sorting through ideas. For most people who manage money, that is where AI lives today. AI-driven signals and autonomous trading are still mostly aspirational.
Faltin-Trager talked about AI helping with bottlenecks. The problem for most discretionary investors is not coming up with ideas. It is sorting through all of them, building enough conviction to size a position, and doing that consistently across a big universe. In credit markets, with thousands of instruments across curves and maturities, covering everything consistently is close to impossible for a human team on its own.
“If you have something that allows an investor to expand their coverage 3x without having to increase headcount, that’s incredibly powerful,” Faltin-Trager said. The tools are not replacing the analyst’s judgment; just letting it scale.
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