Private Equity Advisory

Give the board the AI evidence they need to invest with confidence.

The board wants an AI strategy backed by evidence. You need to understand how 500 people actually work before you can advise on where AI fits.

When to use this

The board wants evidence, not slides

The board wants to know where the company stands on AI - relative to the industry, not just internally. You're delivering workshop findings when they want quantified benchmarks they can compare.

Your team can't interview 500 people

You need to understand how work actually happens across every function before you can advise on AI. Running those interviews manually means one company takes months.

No baseline, no way to measure progress

You deliver an AI readiness report, the company acts on it, but six months later nobody can show the board whether they've closed the gap. Without a scored baseline, there's no way to prove what changed.

How it works
1

Configure around the AI thesis

Set up interviews around AI readiness, adoption barriers, and use case potential. Target the functions where AI is most likely to create value for that company.

2

Deploy across the organisation

Reach stakeholders across operations, IT, data, and frontline teams - in parallel, without scheduling overhead. Capture how work actually happens today.

3

Build a benchmark the board can use

Every response is scored automatically. Build a quantified picture of AI readiness across functions, teams, and use cases - a benchmark the board can track and compare over time.

4

Track transformation over time

Run the same interviews quarterly or post-initiative. Show the board what shifted, where adoption stuck, and where gaps remain - with before-and-after evidence.

Impact
Frontline reality
AI readiness based on what people actually do, not what management presented to the board
Benchmarked from day one
Scored AI readiness across every function - a baseline the board can compare against as transformation progresses
Scalable methodology
Interview hundreds of stakeholders across functions without scaling your team
Proof of progress
Repeat the same benchmark over time and show the board exactly what shifted