Designing an Enterprise AI Maturity Platform for Organizations to Measure, Track, and Scale AI Adoption
End-to-end product design of a scalable AI maturity assessment platform, from methodology definition to executive dashboards and enterprise rollout.
Role: Product Designer
Scope: Strategy, UX, UI, Design System, Test Cases
Timeline: 2 month
Collaboration: Product owners, Client participation
The Challenge
Enterprise organizations lacked a structured, actionable way to measure and scale AI maturity across departments and products. Existing frameworks were static, fragmented, and not operationally embedded.
Defining the Framework
We designed the Phoenix Maturity Score, a structured framework based on 7 dimensions covering governance, technical foundations, adoption, and value realization.
The goal was to translate abstract AI maturity concepts into measurable, operational indicators.
UX & Information Architecture
Designed a multi-layered experience allowing users to navigate maturity insights at organization, department, and product levels.
Structured dynamic assessments with section-based progression and role-based visibility.
Executive Dashboard System
Created a modular dashboard system including:
​Focused on clarity, comparability, and decision-making.
01
Global maturity scores
02
Dimensional graphs
03
Historical tracking
04
Progress trends over time
05
Participation & coverage metrics
Scalable UI System
Built a consistent desktop-oriented design system with reusable components, maturity-level states, and data-driven variants to ensure scalability across organization types.
Impact
The result is a scalable AI maturity platform that enables organizations to:
Measure AI capability across units
Identify gaps with precision
Track progress longitudinally
Align AI initiatives with measurable business value
