How to scale AI in PE and M&A: new whitepaper
Most firms across private equity and investment banking are already using AI. Claude, ChatGPT, or one of the other frontier models has found its way into the workflow - for drafting, for research, for triage. The productivity gains at an individual level are real.
Scaling those gains across a team, a fund, and a year is proving much harder. From the conversations we are having across the market, most firms are running into the same wall.
Our new whitepaper sets out why, and what to do about it.
The central argument
Scaling AI is not a tooling problem. It is an architecture problem. Getting more value from Claude or ChatGPT does not come from finding a better prompt or switching to a newer model. It comes from building the right system behind the model — one that captures what the model produces, connects it to the firm's data, and makes it available to the whole team rather than disappearing at the end of a session.
What's inside
The paper covers the three layers every scalable AI setup requires, why most firms stall at the individual productivity stage, and what the right architecture costs compared to running AI without structure. We have included real numbers from live workflows.
It also covers model routing — using the right LLM for each task rather than running everything through a single frontier model. This has a significant impact on cost as usage scales, and it is something most firms have not yet addressed.
Who it's for
Deal partners and investment professionals who are getting value from AI today and want to understand what scaling it actually requires. And the CTOs and heads of data building the infrastructure behind them.
Practical rather than promotional. The architecture questions it addresses apply whether you are working with Deal Engine or building something in-house.
Download the whitepaper →
Over the next few weeks we will be publishing a series of posts going deeper on the individual arguments in the paper — starting with the cost of unstructured AI. If you have questions in the meantime, get in touch.
