The AI-Powered SDLC: A Comprehensive Technical and Cultural Maturity Assessment Framework
In today’s software development landscape, AI isn’t just a feature we ship—it’s becoming central to how we build, test, and deliver software. As organisations race to leverage AI’s potential across the software development lifecycle (SDLC), a critical question emerges: “How do we measure maturity in AI adoption for development teams?”
We’ve thought a lot about how we could measure AI maturity, and we looked at some of the 15-year-old Agile Maturity models. It made me think: Do we need an AI in the SDLC Maturity Assessment Framework to help organisations benchmark their current state and chart a path forward?
Table of Contents
| Introduction | |
|---|---|
| Why Another Maturity Model? | Rationale for creating a new maturity model |
| Framework Overview | The structure and methodology of our assessment framework |
| Technical Dimensions | |
| Technical Overview | Overview of technical dimensions |
| Requirements Engineering | AI in Requirements Engineering |
| System Design | AI in System Design |
| Coding & Development | AI-Assisted Coding & Development |
| Testing & QA | AI-Enabled Testing & Quality Assurance |
| Deployment & Release | AI in Deployment & Release Engineering |
| Monitoring & Incident Response | AI in Monitoring & Incident Response |
| Governance & Compliance | AI Governance & Compliance |
| Collaboration & Communication | AI-Enhanced Collaboration & Communication |
| Continuous Improvement | Continuous Improvement Through AI |
| User Research | AI in User Research |
| Data Management | AI in Data Management |
| Software Architecture | AI in Software Architecture |
| Cultural Dimensions | |
| Cultural Overview | Overview of cultural dimensions |
| Adaptability & Innovation | Adaptability and Innovation Culture |
| Leadership & Vision | Leadership and Vision Alignment |
| Cross-Functional Collaboration | Cross-Functional Collaboration |
| Skills Development | AI Skills Development and Training |
| Value Measurement | AI Value Measurement and ROI |
| Implementation | |
| Scoring & Implementation | How to score and implement the framework |
| Road Ahead | Future directions and evolution of the framework |
