Owner Pain Points

How Private and PE-Backed Growth Companies Are Using AI to Protect Margins

The average company loses roughly $2M for every $100M in revenue to operational waste that AI can find. For a private or PE-backed business under real margin pressure, that's not an abstraction — it's a number a board will ask about directly.

The businesses I work best with aren't chasing AI because it's trendy. They're feeling real pressure — from a board, from ownership, from a P&L that has to justify every headcount decision — and they're looking for something that actually moves the number, not a talking point for the next board deck.

The pressure is specific, not vague

If you're privately or PE-owned, someone above you feels every dollar directly, and that pressure gets passed down as a specific ask: reduce cost, justify headcount, find the waste that's visible on the P&L and personally uncomfortable to explain. That's a very different starting point than "we want to be more AI-native" — and it's the starting point where AI tends to deliver fast, measurable results, because the target is already defined.

Where the waste actually is

The McKinsey estimate I keep coming back to: the average company loses about $2M per $100M in revenue to operational waste that AI is specifically good at finding — the manual reconciliation, the reports nobody reads, the process that's technically working but quietly bleeding hours every week. For a $50M-revenue portfolio company, that's a real number, not a rounding error.

Why this is a headcount story, not just a technology story

A lot of the real leverage here shows up as headcount efficiency — not necessarily fewer people, but the same team doing meaningfully more without the manual grind eating their week. For a board asking "why does this role need to grow as we scale," that's a direct, credible answer: the manual work that used to require adding headcount now runs itself, and the team's time goes toward the parts of the job that actually require judgment.

What a board-ready starting point looks like

This is exactly the situation where a structured audit pays for itself fastest — a fixed-fee, two-week engagement that identifies specific, dollar-quantified opportunities you can bring back to a board or an ownership group with real numbers attached, rather than a vague sense that "we should look into AI."

Bring real numbers to the table

The AI Opportunity Assessment produces a written, prioritized roadmap with real cost and return estimates — the kind of document that actually works in a board conversation, not just an internal one.

Book a Free 30-Minute Call