D.11 Needs Identification

5.1 Actively engages with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Stakeholder needs report – assessed via a written report of AI stakeholder needs and validation summary; evaluated for completeness of stakeholder identification, clarity of elicited needs, and quality of validation using appropriate techniques (e.g., interviews, workshops).

5.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by Requirement analysis matrix – assessed via a submitted matrix mapping functional, technical, and business requirements to AI solutions; evaluated for correctness of classification, completeness, and logical alignment between requirements and proposed solutions.

5.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI solution options brief – assessed via presentation or report proposing feasible AI solution options; evaluated for relevance, feasibility, and justification of proposed options in relation to stakeholder needs and organisational constraints.

5.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI data analysis summary – assessed via submitted dashboard, data visualisation, or short report analysing data to inform AI solutions; evaluated for accuracy of analysis, appropriate use of tools, and relevance of insights to identified needs.

5.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI ethical & regulatory assessment – assessed via a written document outlining ethical and regulatory considerations in AI solution proposals; evaluated for identification of key issues, alignment with applicable standards, and appropriateness of considerations for the proposed solutions. DATA PROCESSING & ANALYSIS [1]

4.1 Actively engages with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Stakeholder Needs Report – assessed via written report of AI stakeholder needs and validation summary, including evidence from structured interviews, workshops, or observational techniques with internal and external stakeholders.

4.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by Requirement Analysis Matrix – assessed via submitted matrix mapping functional, technical, and business requirements to AI solutions, with traceable differentiation of stakeholder needs using basic requirement-gathering frameworks or tools.

4.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI Solution Options Brief – assessed via presentation or report proposing feasible AI solution options, including justification against validated stakeholder needs, cost, technical feasibility, and organizational priorities.

4.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI Data Analysis Summary – assessed via submitted dashboard, data visualization, or short report analysing data to support identification of needs and evaluation of potential AI solution options.

4.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI Ethical & Regulatory Assessment – assessed via written document outlining ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solution options. DATA PROCESSING & ANALYSIS [1]

6.1 Actively engage with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Stakeholder Needs Report – assessed via written report of AI stakeholder needs and validation summary, including evidence from structured interviews, workshops, or observational techniques with internal and external stakeholders.

6.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by Requirement Analysis Matrix – assessed via submitted matrix mapping functional, technical, and business requirements to AI solutions, with traceable differentiation of stakeholder needs using basic requirement-gathering frameworks or tools.

6.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI Solution Options Brief – assessed via presentation or report proposing feasible AI solution options, including justification against validated stakeholder needs, cost, technical feasibility, and organizational priorities.

6.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI Data Analysis Summary – assessed via submitted dashboard, data visualization, or short report analysing data to support identification of needs and evaluation of potential AI solution options.

6.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI Ethical & Regulatory Assessment – assessed via written document outlining ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solution options.

6.1 Actively engages with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Stakeholder Needs Report – assessed via written report of AI stakeholder needs, evidence from structured interviews, workshops, or observations, and validation summary.

6.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by Requirement Analysis Matrix – assessed via submitted matrix differentiating functional, technical, and business requirements and mapping them to AI solutions using basic requirement-gathering frameworks or tools.

6.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI Solution Options Brief – assessed via presentation or report proposing feasible AI or technology solution options linked to validated stakeholder needs and constraints such as cost, technical feasibility, and organizational priorities.

6.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI Data Analysis Summary – assessed via submitted dashboard, data visualization, or short report using datasets or simple statistical tools to identify needs and evaluate potential AI solution options.

6.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI Ethical & Regulatory Assessment – assessed via written document identifying ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment and showing how these are considered in solution proposals.

3.1 Actively engages with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Stakeholder Needs Report – assessed via written report of AI stakeholder needs, evidence from structured interviews, workshops, or observations, and validation summary.

3.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by Requirement Analysis Matrix – assessed via submitted matrix differentiating functional, technical, and business requirements and mapping them to AI solutions using basic requirement-gathering frameworks or tools.

3.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI Solution Options Brief – assessed via presentation or report proposing feasible AI or technology solution options linked to validated stakeholder needs and constraints such as cost, technical feasibility, and organizational priorities.

3.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI Data Analysis Summary – assessed via submitted dashboard, data visualization, or short report using datasets or simple statistical tools to identify needs and evaluate potential AI solution options.

3.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI Ethical & Regulatory Assessment – assessed via written document identifying ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment and showing how these are considered in solution proposals.

6.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co- creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic stakeholder engagement plan – assessed via a documented engagement plan and workshop/co-creation outputs for AI needs identification; evaluated for stakeholder analysis, appropriateness of engagement methods, quality of elicited requirements, and traceability from stakeholder input to identified AI opportunities.

6.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via a written report analysing AI solutions against strategic, regulatory, ethical, and value alignment criteria; evaluated for analytical depth, justification of alignment decisions, and consideration of trade-offs and constraints.

6.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via a portfolio submission including feasibility studies, comparative analysis, and AI prototyping results; evaluated for methodological rigour, validity of comparisons, integration of evidence, and justification of selected solution approaches.

6.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via a documented implementation roadmap with iterative improvement strategy for AI solutions; evaluated for feasibility, coherence of implementation phases, integration with organisational processes, and robustness of continuous improvement mechanisms.

6.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co- creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs, including evidence of cross-functional team coordination and validation of complex organizational needs.

6.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via written report analysing AI solutions against organizational strategy, regulatory requirements, and long-term value creation objectives using strategic planning frameworks or business model analysis.

6.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or- buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results for a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies.

6.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via documented implementation roadmap and iterative improvement strategy, including use of human-centred design principles, project management tools, or feedback loops.

5.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co- creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs, including evidence of cross-functional team coordination and validation of complex organizational needs.

5.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via written report analysing AI solutions against organizational strategy, regulatory requirements, and long-term value creation objectives using strategic planning frameworks or business model analysis.

5.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or- buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results for a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies.

5.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via documented implementation roadmap and iterative improvement strategy, including use of human-centred design principles, project management tools, or feedback loops. DEVELOPMENT & OPERATIONS [2]

4.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co- creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs showing leadership of cross-functional stakeholder engagement and validation of complex organizational needs.

4.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via written report analysing AI solutions against strategic, regulatory, and value alignment using strategic planning frameworks or business model analysis.

4.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results for make-or-buy, SaaS, cloud, low- code/no-code, and emerging technology options.

4.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via documented implementation roadmap with iterative improvement strategy for AI solutions, including adoption, feedback loops, and human-centred design considerations.

6.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co-creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs showing leadership of cross-functional stakeholder engagement and validation of complex organizational needs.

6.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via written report analysing AI solutions against strategic, regulatory, and value alignment using strategic planning frameworks or business model analysis.

6.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results for make-or-buy, SaaS, cloud, low- code/no-code, and emerging technology options.

6.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via documented implementation roadmap with iterative improvement strategy for AI solutions, including adoption, feedback loops, and human-centred design considerations.

2.1 Lead cross-functional teams in stakeholder engagement by coordinating workshops, co- creation sessions, or advisory meetings to define and validate complex organisational needs.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs showing leadership of cross-functional stakeholder engagement and validation of complex organizational needs.

2.2 Critically assess and ensure that AI-driven solution proposals align with organisational strategy, regulatory requirements, and long-term value creation objectives, using strategic planning frameworks or business model analysis.

Assessed by AI Solution Alignment Report – assessed via written report analysing AI solutions against strategic, regulatory, and value alignment using strategic planning frameworks or business model analysis.

2.3 Evaluate and co-create a comprehensive range of AI solution options, including make-or-buy, SaaS, cloud, low-code/no-code, and other emerging technologies, by applying feasibility studies, prototyping, or comparative analysis.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results for make-or-buy, SaaS, cloud, low- code/no-code, and emerging technology options.

2.4 Ensure the effective implementation, adoption, and iterative enhancement of AI solutions, using human-centred design principles, project management tools, or feedback loops.

Assessed by AI Implementation & Enhancement Plan – assessed via documented implementation roadmap with iterative improvement strategy for AI solutions, including adoption, feedback loops, and human-centred design considerations.

7.1 Actively engages with internal and external stakeholders to elicit and validate their needs, using structured interviews, workshops, or observational techniques.

Assessed by Strategic Stakeholder Engagement Plan – assessed via documented engagement plan and workshop/co-creation outputs showing structured stakeholder engagement and validation of AI-related needs.

7.2 Analyse and articulate stakeholder needs, differentiating between functional, technical, and business requirements, by applying basic requirement-gathering frameworks or tools.

Assessed by AI UX prototype evaluation, practical design assignment, rubric-based assessment

7.3 Translate validated stakeholder needs into feasible AI or technology solution options, considering constraints such as cost, technical feasibility, and organisational priorities.

Assessed by AI Solution Evaluation Portfolio – assessed via portfolio submission including feasibility studies, comparative analysis, and AI prototyping results showing feasible AI or technology options linked to validated stakeholder needs and constraints.

7.4 Apply basic data analysis using datasets, dashboards, or simple statistical tools to support the identification of needs and evaluate potential solution options.

Assessed by AI ethics assessment report, written case analysis, ethical decision reflection

7.5 Recognize and consider ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment when proposing solutions.

Assessed by AI Ethical & Regulatory Assessment – assessed via written document identifying ethical implications and relevant regulatory constraints in AI application scenarios or technology deployment, and explaining how these considerations are addressed in proposed AI or technology solutions.