AI Readiness Assessment: A Scoring Framework for PE Portfolios

When a PE operating partner asks "How AI-ready is this portfolio company?" — they need a number, not a narrative. This framework delivers both.

The Six Dimensions

After assessing dozens of companies for AI readiness, I distilled the evaluation into six dimensions:

1. Data Maturity (Weight: 25%)

• Is data centralized or siloed?
• Are there clean APIs or just CSV exports?
• Is there a data catalog or governance framework?
• Microsoft Fabric makes this dimension actionable — it unifies data estates regardless of where data lives.

2. Process Documentation (Weight: 20%)

• Are core workflows documented?
• Can you map inputs → decisions → outputs for key processes?
• AI needs process clarity. You cannot automate what you cannot describe.

3. Technical Infrastructure (Weight: 20%)

• Cloud adoption level (IaaS / PaaS / SaaS mix)
• API availability across core systems
• Identity and access management maturity
• Azure and Microsoft Entra ID are the baseline here.

4. Talent & Culture (Weight: 15%)

• Is there internal appetite for AI adoption?
• Do teams have data literacy?
• Is there executive sponsorship?
• Copilot adoption rate is a surprisingly good proxy for culture readiness.

5. Use Case Pipeline (Weight: 10%)

• Has the company identified specific AI use cases?
• Are they tied to revenue or cost outcomes?
• Is there a prioritization framework?

6. Governance & Risk (Weight: 10%)

• Data privacy posture
• Regulatory considerations
• Ethical AI framework
• Microsoft Purview handles most of this at the platform level.

The Scoring Rubric

Each dimension is scored 1–5:

• 1 — No capability, major investment needed
• 2 — Early stage, foundational work required
• 3 — Developing, some capability in place
• 4 — Mature, ready for AI augmentation
• 5 — Advanced, already leveraging AI

The weighted total gives you a score out of 5. In my experience:

• Below 2.0 — 12–18 month runway before meaningful AI adoption
• 2.0–3.0 — Ready for targeted pilots
• 3.0–4.0 — Ready for portfolio-wide AI strategy
• Above 4.0 — Already ahead; focus on scaling

Visualizing with Power BI

I build the assessment dashboard in Power BI connected to Microsoft Fabric. Each portfolio company gets a radar chart across the six dimensions, trend tracking over quarters, and benchmark comparisons. The operating partner gets a single dashboard view across the entire portfolio.

Why This Matters

AI readiness is not a technology conversation—it is a value creation conversation. The framework turns a subjective "How ready are we?" into a measurable, trackable metric that the board can act on.