About this session

Investor relations has quietly become the most labour-intensive function in a private capital firm. Every LP wants their own cut of the data, in their own template, on their own timetable. Quarterly reporting consumes weeks of senior time that produces nothing proprietary. And the ad-hoc query, the one-line email asking for a look-through exposure figure or a restated IRR, lands without warning and takes three people to answer. This is precisely the shape of work AI is good at, which is why IR is where most firms are seeing their first genuine returns.

This 45-minute session looks at what that means in practice: capital call and distribution notices drafted, checked and issued at a fraction of the effort; quarterly letters assembled from source data instead of copy-and-paste; and LP queries answered on the spot from a system that knows what has already been disclosed. We are equally direct about what has not worked, and the questions that stop IR teams cold: how you keep a model from inventing a number, maintain one version of the truth across bespoke reporting formats, what you tell an LP who asks whether their data has been near an AI model, and where human sign-off must remain absolute. Vendor-neutral, practical, and built for stretched teams.

Agenda

• Why IR broke first. How reporting bespoke-ness and LP service expectations built a workload no headcount plan can fix.

• Workflows worth automating. Onboarding, capital calls and notices, quarterly reporting, and ad-hoc LP queries.

• The answer library. Why the highest-return AI project in IR is usually the approved, source-linked system of record a model draws on.

• Accuracy, disclosure and control. Preventing fabricated figures, keeping an audit trail, handling LP questions about AI use, and what a human must approve.

• What good looks like in twelve months. Faster cycles, fewer errors, and senior IR time back on relationships.

• Live Q&A