AI Skills Development and Training
This dimension evaluates how the organization builds AI capabilities within its development workforce.
Sample assessment questions for each level:
- Level -1 (Resistant): “Does the organization discourage developers from learning AI skills?”
- Level 0 (Ad-hoc): “Do developers learn AI skills individually without organizational support?”
- Level 1 (Exploratory): “Has the organization identified AI skill gaps in development teams?”
- Level 2 (Structured): “Are there formalized training programs for basic AI skills in development?”
- Level 3 (Established): “Is there a comprehensive AI skills development strategy for all SDLC roles?”
- Level 4 (Integrated): “Are AI skills integrated into career paths and performance evaluations?”
- Level 5 (Transformative): “Does the organization foster a culture of continuous AI learning with advanced specialization?”
Key metrics to track:
- AI literacy rate: Percentage of developers with foundational AI knowledge
- Specialized AI skills: Distribution of advanced AI skills across development teams
- Training effectiveness: Improvement in AI capabilities after training initiatives
- AI certification completion: Percentage of relevant staff with AI certifications
- Knowledge sharing sessions: Frequency of AI skills exchange between team members
- External expertise leverage: Quality of partnerships with AI specialists and consultants
- Talent retention: Retention rate of AI-skilled employees
