Pivotal Roles in Asset Management
A sector report reading twelve pivotal asset management roles task by task against what AI can take on, with role-level evidence and worked workflows.
Why this report
Asset management runs on structured data: prices, positions, exposures, performance, and the models and reporting built around them. That makes it one of the first functions where the AI question can be answered with evidence. This report reads twelve roles that run an investment firm, from portfolio management and trading through research, quantitative analysis, risk, ESG, and fund operations, task by task against what AI can take on today.
What it shows
Every figure traces back to observed work. Each role is broken into its tasks, and each task assessed against four AI capabilities to produce an automation potential: the share of measured task time open to AI support. The report covers the cohort picture, a ranking of the twelve roles, the five themes of work that cut across them, and worked AI workflows ready for teams to adopt.
The headline
Across the cohort, mean automation potential is 37%, and every role lands in a narrow band between 31 and 41%. No role is untouched and none is close to fully exposed. The function changes as a whole, which makes the response a function-wide redesign rather than a defensive exercise around a few roles.