STRATEGIC OVERVIEW
Why I Built This Framework Most AI maturity models read like vendor checklists. They reward slide decks, not production agents with audit trails.
Why I Built This Framework
Most AI maturity models read like vendor checklists. They reward slide decks, not production agents with audit trails. After running architecture reviews across BFSI, India GCC, and US HQ programs, I needed a scorecard that answers one question: can this org ship agentic workloads safely and prove ROI in 90 days?
This framework is what I actually use in client sessions. It is not academic — every tier maps to artifacts I expect in the room.
The Five Dimensions
| Dimension | Level 1 — Ad Hoc | Level 3 — Managed | Level 5 — Optimized |
|---|---|---|---|
| Strategy | Pilots without sponsor | Executive OKRs tied to AI | Portfolio governance with kill criteria |
| Data | Siloed exports | Catalog + lineage | Real-time features for agents |
| Platform | Notebook prototypes | CI/CD for models + agents | Multi-region, cost-aware orchestration |
| Governance | Policy PDF only | DPDP/GDPR mapping + human-in-loop | Continuous compliance telemetry |
| ROI | Vanity demos | One production metric instrumented | Board-ready ROI with variance |
India + Global Lens
India GCC teams often lead delivery while HQ owns budget and risk. Score both sides:
- India: DPDP consent flows, RBI outsourcing exposure, talent retention on agentic squads
- Global: EU AI Act GPAI obligations, SOC 2 evidence, vendor concentration risk
If India scores Level 4 on platform but HQ is Level 2 on governance, you have a deployment bottleneck — not a technology gap.
How to Run the Assessment (90 Minutes)
- Pre-work (15 min) — List active AI pilots, owners, and last production incident
- Workshop (45 min) — Score each dimension; require evidence (dashboard, ticket, policy link)
- Synthesis (20 min) — Pick top two gaps and one quick win for next sprint
- Readout (10 min) — One-page summary for architecture board
Sample Scoring Prompts
Governance — Level 3 evidence: Documented human-in-loop for financial agent actions; audit log retained 90+ days.
Platform — Level 4 evidence: Agent deployments through CI/CD; rollback tested in last quarter.
ROI — Level 3 evidence: Single KPI (MTTR, cost per ticket, revenue lift) tracked weekly with owner.
Next Steps
Use this with the Board AI Governance ROI Playbook when preparing executive readouts. Need a facilitated review? Book an architecture session.
AI Maturity Scorecard
Explore a purpose-built simulation of the system delivered for this engagement — unique UI, fictional data, no production access.
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Simulation uses fictional data. Controls are for demonstration only and do not connect to production systems.
