D.9 Personnel Development

4.1 Analyse AI competence data to identify skill gaps, trends, and development opportunities across individuals and teams using organisational assessment tools and performance metrics.

Assessed by Assessment of AI competence analysis report, evaluating documented AI skill gaps, trends, and development opportunities using organisational assessment tools and performance metrics.

4.2 Evaluate the relevance of AI skills for organisational objectives and diverse work contexts in current projects and operational settings.

Assessed by Review of AI skills evaluation matrix, graded for relevance of AI skills to organisational objectives, diverse work contexts, current projects, and operational settings.

4.3 Design role-specific AI learning pathways and interventions using organisational resources, learning platforms, and professional development frameworks.

Assessed by Evaluation of role-specific AI learning pathway plan, assessed with a rubric for clarity, feasibility, use of organisational resources, learning platforms, and professional development frameworks.

4.4 Implement AI learning programmes that enable team members to apply AI responsibly and effectively in workplace tasks and collaborative projects.

Assessed by Assessment of implemented AI learning program documentation, including evidence that team members apply AI responsibly and effectively in workplace tasks and collaborative projects.

4.5 Coach peers to apply AI in decision-making, problem-solving, and team collaboration through mentoring sessions, workshops, or team-based exercises.

Assessed by Review of peer AI coaching portfolio and observation of mentoring sessions, workshops, or team-based exercises demonstrating AI application in decision-making, problem-solving, and team collaboration.

4.6 Apply AI insights to enhance team-level collaboration, decision-making, and problem-solving processes by integrating data-driven tools and analytic techniques.

Assessed by Assessment of team-level AI insights report, evaluating use of data-driven tools and analytic techniques and recommendations for improving collaboration, decision-making, and problem-solving.

4.7 Demonstrate responsible and context-aware use of AI tools such as AI-assisted analytics, automation tools, or knowledge management systems in organisational activities

Assessed by Grading of applied AI case study or portfolio, assessed for responsible and context-aware use of AI-assisted analytics, automation tools, or knowledge management systems in organisational activities.

5.1 Analyse AI competence data to identify skill gaps, trends, and development opportunities across individuals and teams using organisational assessment tools and performance metrics.

Assessed by Assessment of AI competence analysis report, evaluating documented AI skill gaps, trends, and development opportunities using organisational assessment tools and performance metrics.

5.2 Evaluate the relevance of AI skills for organisational objectives and diverse work contexts in current projects and operational settings.

Assessed by Review of AI skills evaluation matrix, graded for relevance of AI skills to organisational objectives, diverse work contexts, current projects, and operational settings.

5.3 Design role-specific AI learning pathways and interventions using organisational resources, learning platforms, and professional development frameworks.

Assessed by Evaluation of role-specific AI learning pathway plan, assessed with a rubric for clarity, feasibility, use of organisational resources, learning platforms, and professional development frameworks.

5.4 Implement AI learning programmes that enable team members to apply AI responsibly and effectively in workplace tasks and collaborative projects.

Assessed by Assessment of implemented AI learning program documentation, including evidence that team members apply AI responsibly and effectively in workplace tasks and collaborative projects.

5.5 Coach peers to apply AI in decision-making, problem-solving, and team collaboration through mentoring sessions, workshops, or team-based exercises.

Assessed by Review of peer AI coaching portfolio and observation of mentoring sessions, workshops, or team-based exercises demonstrating AI application in decision-making, problem-solving, and team collaboration.

5.6 Apply AI insights to enhance team-level collaboration, decision-making, and problem-solving processes by integrating data-driven tools and analytic techniques.

Assessed by Assessment of team-level AI insights report, evaluating use of data-driven tools and analytic techniques and recommendations for improving collaboration, decision-making, and problem-solving.

5.7 Demonstrate responsible and context-aware use of AI tools such as AI-assisted analytics, automation tools, or knowledge management systems in organisational activities.

Assessed by Grading of applied AI case study or portfolio, assessed for responsible and context-aware use of AI-assisted analytics, automation tools, or knowledge management systems in organisational activities.

1.1 Evaluate organisational AI competence needs considering technical, ethical, and human–AI collaboration aspects using workforce assessments, performance analytics, and organisational surveys.

Assessed by Evaluation of organisational AI competence assessment report, assessed for use of workforce assessments, performance analytics, and organisational surveys to analyse technical, ethical, and human–AI collaboration competence needs.

1.2 Integrate multiple AI-related knowledge domains to develop coherent and strategic learning approaches in alignment with organisational objectives and team requirements.

Assessed by Review of integrated AI knowledge framework, assessed for coherence, strategic alignment with organisational objectives, and fit with team requirements.

1.3 Formulate strategic AI competence development plans aligned with organisational objectives and workforce needs by combining workforce skill analysis with business priorities.

Assessed by Grading of strategic AI competence development plan, assessed for alignment with organisational objectives, workforce needs, workforce skill analysis, and business priorities.

1.4 Design advanced AI learning initiatives to address skill gaps at individual, team, and organisational levels using blended learning approaches, professional development frameworks, or experiential learning projects.

Assessed by Assessment of advanced AI learning initiative design dossier, assessed for quality, feasibility, and coverage of individual, team, and organisational skill gaps using blended, professional development, or experiential approaches.

1.5 Implement AI learning programmes and mentoring processes to systematically develop competence across the workforce in organisational training, coaching, and collaborative initiatives.

Assessed by Evaluation of implemented AI programme portfolio, assessed for evidence of training, coaching, mentoring, collaborative initiatives, and workforce-wide AI competence development.

1.6 Establish and sustain a continuous AI learning culture that embeds ethical practices and supports workforce-wide capability development by introducing structured learning processes, communities of practice, and feedback mechanisms.

Assessed by Review of continuous AI learning culture report, assessed for structured learning processes, communities of practice, feedback mechanisms, ethical embedding, and workforce-wide capability development.

1.7 Assess the impact of AI learning initiatives on organisational performance and capability development using evaluation metrics, progress dashboards, and organisational performance indicators.

Assessed by Assessment of AI learning impact report, assessed for use of evaluation metrics, progress dashboards, and organisational performance indicators to analyse performance improvements and capability development.

1.8 Design and refine organisational processes that ensure ongoing identification, development, and evaluation of AI competences across all workforce levels in HR and learning & development procedures, organisational policies, or process audits.

Assessed by Evaluation of organisational AI competence process documentation, assessed for process design and refinement supporting ongoing identification, development, and evaluation of AI competences across all workforce levels.