PE Firms · Buy-and-Build Platforms · Family Offices
Every deck promises AI value creation. Your portfolio can prove it.
LPs now ask the AI question in every annual meeting, and most funds answer with a slide. We give you the operator's answer: a measured AI roadmap across your portfolio companies, engines deployed where they move EBITDA, and evidence — baselines and deltas — that survives diligence at exit. And on the front end of the fund: a deal-sourcing engine that builds proprietary flow in your thesis, so you stop paying auction prices for intermediated deals.
The landscape
The 7% gap is a value-creation thesis.
The 2025–26 research describes the opportunity with unusual precision: 88% of organizations now use AI somewhere (McKinsey, late 2025), corporate AI investment grew 130% to $582B in a single year (Stanford AI Index 2026) — and only 7% of organizations have scaled AI into real results. For most operators that gap is a frustration. For a fund that controls its companies, it's a thesis: the portfolio that closes the gap earns measurable EBITDA the market hasn't priced into entry multiples yet.
The structural advantage sits with lower-middle-market services portfolios — exactly the home services, dental, veterinary, insurance, and accounting platforms PE has spent a decade consolidating. Those businesses leak revenue in documented, fixable places: missed calls, slow lead response, unworked follow-up, manual back offices. We already run vertical playbooks in each of those industries, which means a portfolio deployment isn't a consulting study — it's a rollout of engines that exist, measured against baselines your IC can audit.
The market problem, in published numbers
88%
of organizations now use AI in at least one business function — up ten points in a year
McKinsey, The State of AI (November 2025 global survey) (2025)
7%
of organizations have fully scaled AI across the business — adoption is everywhere, results are rare
McKinsey, The State of AI (November 2025 global survey) (2025)
$582B
global corporate AI investment in 2025 — up 130% in a single year
1 ≈ 2
individuals working with AI matched the performance of two-person teams working without it, in a 776-professional field experiment at Procter & Gamble
Figures are third-party market benchmarks from the cited sources, not Ometz AI client results. We share them so you can size the problem before we ever talk.
Where private equity leak revenue
The LP question
"What's your AI value-creation strategy?" deserves better than a slide with logos.
Value-creation bandwidth
An ops team covering ten portcos can't also be the AI deployment team for each.
Auction-priced deal flow
Intermediated deals mean full price. Proprietary flow takes outbound nobody has time to run.
The pilot graveyard
Every portco is experimenting; almost nothing scales — the 88%-vs-7% gap, multiplied across a fund.
The Private Equity program
The core engines, tuned to your operation.
CLARITY
AI Roadmap for Portfolio Companies
Comparable baselines across every portco, opportunities ranked by EBITDA impact, and reporting your LPs and IC can audit.
What we measure
- — Portcos baselined
- — EBITDA opportunity identified and ranked
- — Initiatives reporting measured ROI
01
Portfolio-wide Radar
Every portco assessed on the same seven dimensions — comparable scores, honest gaps, a ranked deployment queue.
02
Value-creation baselines
Call, lead, conversion, and admin-hour data pulled per portco — the before that makes every after provable.
03
LP & IC reporting
A portfolio AI dashboard: initiatives, baselines, deltas. The annual-meeting answer, maintained quarterly.
GROWTH
The Proprietary Deal Engine
Off-market deal flow as a system: researched, principal-grade outreach to founders inside your thesis — so the conversation starts before the bankers do, at relationship prices instead of auction prices.
What we measure
- — Proprietary (off-market) opportunities per quarter
- — Owner conversations opened pre-process
- — Entry multiple: proprietary vs. intermediated deals
01
Off-market founder origination
Owner lists built to your thesis — size, geography, fragmentation — approached with researched, respectful outreach in your fund's name, before any process exists.
02
Owner cultivation, years ahead
Founders 2–3 years from a decision get a patient, value-adding cadence — so when they're ready, there's no auction. Just you.
03
Aged-target and broken-process revival
Owners who said 'not yet' and processes that fell apart get a systematic, well-timed second conversation — the cheapest proprietary flow there is.
BESPOKE
Portfolio Value-Creation Deployment
The engines rolled out across portcos by one team, on one playbook, with one reporting layer — and exit-ready evidence as the byproduct.
What we measure
- — Measured EBITDA lift per portco
- — Time-to-deploy per company (should fall)
- — Data-room artifacts produced
01
Lighthouse deployment
Front-office, conversion, and back-office engines live in the highest-opportunity portco first — proof before scale.
02
Cross-portfolio rollout
Our vertical playbooks (home services, dental, insurance, accounting and more) redeployed company by company, faster each time.
03
Exit-ready evidence
Documented baselines, deltas, and running systems — an AI story that survives quality-of-earnings scrutiny.
The diagnosis
What we look for in your portfolio.
Every engagement starts by measuring these in your own systems — so the before/after is provable, not promised.
Run the Ometz RadarShare of portcos with an owned, budgeted AI initiative versus scattered experiments
EBITDA exposure to automatable admin across the portfolio
Missed-call and lead-response performance at customer-facing portcos
Sourcing mix: proprietary versus intermediated deal flow, and cost per deal
Value-creation team hours per portco on operational improvement
Whether AI appears in exit narratives as evidence or as adjectives
How an engagement runs
01
Weeks 1–2: Portfolio Radar
We run the Ometz Radar across your portcos — comparable maturity scores, baselined call/lead/admin data, and a ranked view of where AI moves EBITDA fastest.
02
Weeks 2–8: Lighthouse deployments
Engines go live in one or two highest-opportunity portcos, measured against their baselines. The lighthouse becomes the internal proof your operators rally behind.
03
Quarter 2+: Roll the playbook
Deployment replicates across the portfolio on one reporting layer — LP-ready evidence accumulates. The deal-sourcing engine runs for the fund in parallel.
Private Equity FAQ
Bandwidth and repetition. Your team owns strategy and the relationship with management; we're the deployment crew that has already run these engines in the industries you own. They direct; we execute and report.
Next step
Run the Radar on your portfolio.
Fourteen questions, four minutes, and a maturity radar across the seven dimensions of AI readiness, from strategy to culture. Then decide if a conversation is worth your time.