The Nth Layer — AI Maturity Index

AI maturity benchmarking purpose-built for private equity

Most AI maturity frameworks are built for generic enterprises. This one is built for private equity — hold-period economics, portco context, and value creation tied to EBITDA.

Six pillar scores, a weighted overall score, a maturity stage, and peer comparisons from 54 sponsor-owned B2B SaaS companies. Plus a 90-day action plan to close the gaps.

What you get

01

Six pillar scores

A weighted overall score, a maturity stage, and a radar profile across Strategy & Leadership, Data & Knowledge Foundation, Use Cases & Value Capture, Talent & Operating Model, Governance & Risk, and Infrastructure & Tooling.

02

Named peer comparisons

Every result is benchmarked against a reference library of 54 sponsor-owned B2B SaaS companies. Every score is supported by public evidence with a clickable source link. The library is unique to Nth Layer.

03

A 90 day roadmap

A prioritised action list and a 90-day execution roadmap with EBITDA uplift modelling — tied to specific value creation levers, not generic AI best practice.

Our approach

Six pillars. Weighted to reflect where EBITDA is created.

The Index synthesises the leading public AI maturity frameworks — Gartner, McKinsey, MIT, BCG, Cisco, Accenture, Deloitte, KPMG — and recalibrates for sponsor-backed value creation.

Strategy & Leadership
20%
Data & Knowledge Foundation
15%
Use Cases, Product & Value Capture Highest weight — most directly tied to EBIT contribution
25%
Talent, Operating Model & Workflow
20%
Governance, Risk & Trust
10%
Infrastructure & Tooling
10%

Methodology

01

Sponsor-controlled

Majority PE ownership at time of scoring. The reference library is built for the hold-period context — not public-company benchmarks.

02

$100M+ ARR

Companies at scale, with enough operational surface area for AI to have meaningful impact on EBITDA, workflows, and product.

03

Public evidence only

Scoring relies entirely on public evidence — sponsor disclosures, audited filings, earnings calls, named case studies, and corroborating trade press. No insider information. Every score has a deep-linked source.

How we score

The 0 to 5 scale runs from Absent to Transformational. Three rules preserve scoring integrity.

Cumulative-stage rule A company cannot score Level N without evidence for Level N minus 1.
Conservative-bias rule Defaults to the lower score when judgement is required.
N/A rule Prefers an absent score to a guessed one.
LEVEL 0
Absent
No evidence of AI activity in this pillar.
LEVEL 1
Aware
Strategy or investment announced. No production output.
LEVEL 2
Operational
AI in production in at least one core workflow with measurable ROI.
LEVEL 3
Systemic
AI across most priority workflows. >2% EBIT impact. Governed agents.
LEVEL 4
Transformational
AI is the operating model. >5% EBIT directly attributable.

How we evaluate evidence

Every score is supported by evidence categorised on a four-tier hierarchy. A sponsor partner, LP, or acquirer can interrogate any cell, click through to the underlying source, and form an independent view.

Tier 1
audited_financial_disclosures
Annual reports, earnings releases, IPO filings. CFO-attested. The strongest form of evidence.
Tier 2
named_customer_references
Sponsor case studies and named references with quantified outcomes. Strong, but not formally audited.
Tier 3
corroborating_trade_press
Independent confirmation of Tier 1 or 2 facts. Useful in support, insufficient in isolation.
Tier 4 — Not credited
generic_marketing_claims
'AI-powered' positioning without quantified outcomes. We do not credit Tier 4 as evidence.