A firm doesn't choose make or buy — it runs a mix, and the mix depends on its size, its turnover and what its own people are too busy to learn. Watch the ratio, the price at every tier, and the released experts who come back as AI-native rivals.
| Service line | In-house ↔ bought | In-house | Blended £ |
|---|
| Provider | Income /yr | Profit /yr | Margin | Status |
|---|
The mix, not the switch. Each service line runs at an in-house fraction the firm moves slowly (there's a cost to change it — redundancy one way, ramp-up the other). The baseline mix depends on size: a small firm keeps most things in-house and minimises churn; a mid firm has enough turnover that offloading the churn to a supplier pays, and buys in the new skills its own people are too busy on legacy tech to learn; an enterprise decides by spreadsheet — but all three keep their core value work in-house.
The make-threat. Keeping a credible in-house capability disciplines your suppliers. As a firm approaches fully-outsourced, it loses that threat — no internal benchmark, a captured customer — and its outsourcing unit cost rises. Being all-bought is not the cheap corner it looks like.
The tide. When AI collapses the cost of knowledge work, the firm insources what it can and sheds the rest — into expert pools by domain, which depress that domain's wage. Some of those experts don't wait to be re-hired: they found AI-native firms in the field they came from. Those entrants first undercut the incumbent firms and suppliers, then compete each other toward the cost of compute. Each incumbent's P&L — income, cost, unit price, margin — is on the table; when a margin can't be held, the provider retires from the market.
All figures are illustrative defaults, editable live. The instrument is for moving them and watching the logic — and the livelihoods — shift.