"Do Better Things."
AI Diligence for Private Equity

Will AI eat this business?
Know before you sign.

Independent AI and service diligence for private equity. I tell your deal team whether the AI in the deck is real, whether customers feel it, and whether the business survives the next wave of automation.

Talk to me about a live deal Download the Better bets one-pager
1

Looks at disruption risk as well as product quality. A well-built company can still be the next one automated away.

2

Looks at the service from the customer's side. Revenue that depends on a service customers tolerate rather than value is a risk the numbers hide.

3

Written by someone who has shipped AI in regulated services, not only advised on it.

The gap
Every CIM on your desk says AI-powered. Your tech diligence will tell you the code is clean. It won't tell you whether a cheaper model makes the product pointless in eighteen months, or whether the 'AI' is three people in a back office with a spreadsheet. That's the gap I work in.
The questions I answer before you invest

What a code review doesn't cover

Will AI eat this business?

Which parts of the model a foundation model or a competitor's agent could do for a tenth of the price — and when.

Is the AI real, or a slide?

What runs in production, what's a demo, and what's people. The gap between deck and deployment is where deal value leaks.

What do customers actually live through?

The service as customers experience it, set against what the deck claims. Retention risk the NPS score doesn't surface.

Does it own its data?

Whether the data that makes the product work belongs to the company, a client, or a supplier. Moat or mirage.

What's the regulator risk?

Exposure under the EU AI Act, FCA consumer duty, health and data rules — before the regulator finds it on a site visit.

Who's exposed in the workforce?

The roles automation changes, and what that does to cost, culture, and key-person risk. The post-close headache that pre-close diligence ignores.

How we work together

Fixed scope. Fixed fees. No procurement conversation.

Three engagements, the first two at a fixed fee your deal team can approve without a committee. Everything starts with a 30-minute call at no cost — bring the CIM.

Lead offer

Red-flag review

Before LOI  ·  5 working days
  • A 2-page memo covering the three biggest AI and service risks
  • A call with your deal team to walk through the findings
  • A clear view: keep going, re-price, or walk away
Fixed fee  ·  Price on request
Full diligence

IC-ready report

Confirmatory, before IC  ·  3–4 weeks
  • All six questions covered in depth
  • An invest, re-price, or walk view the IC can cite
  • Findings structured for your legal and commercial advisers
Fixed fee  ·  Price on request
Post-close

100 days and beyond

After close  ·  Retainer, 3–6 months
  • A short list of bets instead of use cases
  • Pilots into production with governance that passes audit
  • Exit-readiness work and an AI story a buyer can check
Monthly retainer  ·  Price on request
After the deal

Value in year one, not year three

If you invest, I can stay on for the first 100 days: picking the few bets worth making instead of a long list of use cases, getting pilots into production, and putting governance in place that would pass an audit.

When it's time to sell, I help you build an AI story a buyer's own diligence team can check. That means value tracked in EBITDA terms from day one, not assembled retrospectively when the IM is due.

I work directly with the management team, not through a layer of associates. The operating partner who inherits the company gets someone who was in the diligence, knows where the bodies are, and doesn't need a briefing document.

Before the bet
Red flags, real AI, customer truth, data ownership, regulator exposure, workforce risk. An IC-ready view before you commit.
First 100 days
Short list of bets. Pilots into production. Governance that passes audit. A service blueprint of the business as it actually runs.
Exit prep
Value tracked in EBITDA terms. An AI story a buyer's diligence team can verify. A playbook for the next deal in the portfolio.
The Better Bets Map

Everything a deal team should cover on AI

Before and after the bet. The full picture at a glance.

Before the bet
Will AI eat this business?
Is the AI real, or a slide?
What do customers live through?
Does it own its data?
What's the regulator risk?
Who's exposed in the workforce?
First 100 days
Short list of bets to make
Pilots into production
Service blueprint
Governance that passes audit
Team that stays after we leave
Exit
Value tracked in EBITDA terms
AI story a buyer can check
Playbook for the next deal
Download as a one-pager: get in touch for the PDF
Who you get
Pete Trainor
Pete Trainor
AI strategy, service design, and 30 years building things that work

I've spent 25 years building technology services, from VR in 1996 to AI in banking, health and field service. I've run a healthcare business as CEO, led a department of 60 at Publicis Sapient, and built AI for vulnerable customers at NatWest under FCA scrutiny.

Today I lead AI digital workers at IFS, working at the intersection of enterprise product strategy and hands-on agent design. I've seen what AI looks like in a pitch deck and what it looks like in production, and they're rarely the same thing.

I'm not an AI evangelist. I write books about how automation threatens the things people love. That's a different lens on a CIM than you get from most advisers.

More about Pete

Got a deal in the pipeline
with AI in the story?

Send me the CIM. I'll tell you in a 30-minute call what I'd want to look at, at no cost. No engagement letter, no NDA needed to start the conversation.

Book a call pete@trainor.fyi LinkedIn