AI Value Measurement and ROI
This dimension assesses how the organisation measures and maximises value from AI in the SDLC.
Sample assessment questions for each level:
- Level -1 (Resistant): “Does the organisation dismiss the need to measure AI value in development?”
- Level 0 (Ad-hoc): “Is AI value measured inconsistently without standard metrics?”
- Level 1 (Exploratory): “Has the team identified potential value metrics for AI in the SDLC?”
- Level 2 (Structured): “Are there basic KPIs established for measuring AI impact in development?”
- Level 3 (Established): “Is there a comprehensive framework for measuring AI value across the SDLC?”
- Level 4 (Integrated): “Are AI value metrics integrated with overall business performance indicators?”
- Level 5 (Transformative): “Does the organisation have a predictive model for AI investment impact on business outcomes?”
Key metrics to track:
- Development velocity improvement: Change in delivery speed with AI implementation
- Cost efficiency: Measured reduction in development costs through AI
- Quality improvement: Defect reduction attributed to AI implementation
- Innovation acceleration: Reduction in time from concept to market with AI assistance
- ROI measurement maturity: Sophistication of AI investment evaluation methods
- Value attribution accuracy: Quality of methods linking AI initiatives to business outcomes
- Strategic alignment: Percentage of AI initiatives tied to strategic business objectives
