---
title: "Professional services: use this framework to get ready for AI"
date: "2025-06-15"
excerpt: "Find · Win · Deliver · Learn — the four-stage operating model we use to assess AI readiness in professional services firms, and where the quick wins actually sit."
tags: ["AI", "Framework"]
author: "Tom Leyden"
migratedFrom: "https://www.redyellowblue.com.au/blog/professional-services-use-this-framework-to-get-ready-for-ai"
---

Professional services firms ask us a version of the same question: *“Where should we start with AI?”*

The honest answer is rarely the latest model release. It’s a structural question — how the business actually operates and where AI can compress effort or improve quality. We use a four-stage frame to map any professional services firm:

## Find · Win · Deliver · Learn

| Stage | What it covers |
|---|---|
| **Find** | Lead generation, brand, ICP definition, outbound, partnerships |
| **Win** | Proposals, pitching, estimation, scoping, onboarding |
| **Deliver** | Project execution, collaboration, billing, status, quality |
| **Learn** | Retros, IP capture, training, post-mortem analysis |

The premise is simple: every firm runs all four stages, but most have invested unevenly across them. The stage you’ve under-invested in is usually where AI lands biggest.

## Step 1 — Map your current state

For each of the four stages, answer three questions:

1. **What systems do we use today?**
2. **How integrated are they?**
3. **Where does friction live — manual handoffs, duplicated data, missing visibility?**

You’ll usually find the same pattern: the systems are fine in isolation, the *integration* between stages is where time and quality bleed out.

## Step 2 — Pick the AI quick wins

A non-exhaustive list of where we see professional services firms get early payback:

- **Find** — AI-assisted proposal search; ICP-fit scoring; outbound copy drafting
- **Win** — Proposal drafting against a knowledge base; deal scoring against historic outcomes; meeting briefing
- **Deliver** — Meeting intelligence; technical co-pilots in your stack of choice; auto-generated status updates
- **Learn** — Natural-language knowledge base over closed projects; pattern-finding across engagements

The point isn’t that all of these matter to your firm — it’s that you choose one or two based on where your map showed friction in Step 1.

## The trap to avoid

Most firms want AI wins but haven’t mapped where their core systems sit. They buy a tool, integrate it badly into a fragmented stack, and conclude AI doesn’t work for them. It does work — but only after the foundation question is answered.

Map first. Buy second.