B.5 Documentation Production

2.1 Identify key AI documentation types, requirements, and templates used in routine AI projects, such as model datasheets, user manuals, or compliance checklists.

Assessed by Review of a submitted AI documentation inventory or reference table; quiz or oral questioning on AI documentation types and template purposes; assessed for correctness of identification, completeness, and understanding of documentation roles in routine AI projects.

2.2 Explain the purpose of technical, compliance, and transparency documentation for AI systems, by referring to examples like algorithmic decision logs or fairness assessment reports.

Assessed by Written explanation or short report linking AI documentation types to their purposes; scenario-based questions on transparency or compliance documentation; assessed for clarity, correctness, and relevance of explanations to the given context.

2.3 Produce basic AI technical and compliance documents under guidance, following predefined templates, using standard documentation formats and structured forms.

Assessed by Evaluation of a completed AI datasheet, compliance checklist, or user guide, assessed for accuracy, completeness, adherence to predefined templates, and correct use of standard documentation formats.

2.4 Use document-management tools to store, retrieve, and update AI documentation, in systems that support organised and version-controlled storage.

Assessed by Inspection of a document repository demonstrating correct storage, retrieval, and version control of AI documentation; submission of a log showing updates; assessed for proper use of document management tools and consistency of versioning practices.

2.5 Verify that information in AI documents is accurate, complete, and aligned with organisational standards, by cross-checking against project requirements and regulatory guidelines.

Assessed by Review of annotated AI documents or a verification checklist demonstrating identification and correction of errors; assessed for accuracy of verification, completeness of checks, and alignment with organisational documentation standards.

2.1 Identify key AI documentation types, requirements, and templates used in routine AI projects, such as model datasheets, user manuals, or compliance checklists.

Assessed by Review of submitted AI documentation inventory or reference table, combined with quiz or oral questioning, assessed for correct identification of AI documentation types, requirements, templates, and template purposes in routine AI projects.

2.2 Explain the purpose of technical, compliance, and transparency documentation for AI systems, by referring to examples like algorithmic decision logs or fairness assessment reports.

Assessed by Written explanation or short report linking AI documentation types to purposes, with scenario-based questions, assessed for accurate explanation of technical, compliance, and transparency documentation using examples such as algorithmic decision logs or fairness assessment reports.

2.3 Produce basic AI technical and compliance documents under guidance, following predefined templates, using standard documentation formats and structured forms.

Assessed by Evaluation of completed AI datasheet, compliance checklist, or user guide, assessed for accuracy, completeness, adherence to predefined templates, and correct use of standard documentation formats or structured forms under guidance.

2.4 Use document-management tools to store, retrieve, and update AI documentation, in systems that support organised and version-controlled storage.

Assessed by Inspection of document repository and update log, assessed for correct storage, retrieval, updating, and version-controlled organisation of AI documentation.

2.5 Verify that information in AI documents is accurate, complete, and aligned with organisational standards, by cross-checking against project requirements and regulatory guidelines.

Assessed by Review of annotated AI documents or verification checklist, assessed for evidence of cross- checking against project requirements and regulatory guidelines, correction of errors, and alignment with organizational standards.

1.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, and collaborative workflow evidence, with peer-review of contributions, assessed for independent application of document-management and collaboration practices in AI projects.

1.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, using a grading rubric based on completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

1.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration of information from different AI system elements.

1.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, with submission of compliance verification report assessed for alignment with applicable legal, ethical, and organizational standards.

1.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for adaptability to variable AI project contexts, alignment with project-specific requirements, and accommodation of new system components.

5.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, and collaborative workflow evidence, with peer-review of contributions, assessed for independent application of document-management and collaboration practices in AI projects.

5.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, using a grading rubric based on completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

5.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration of information from different AI system elements.

5.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, with submission of compliance verification report assessed for alignment with applicable legal, ethical, and organizational standards.

5.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for adaptability to variable AI project contexts, alignment with project-specific requirements, and accommodation of new system components.

7.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, and collaborative workflow evidence, with peer-review of contributions, assessed for independent application of document-management and collaboration practices in AI projects.

7.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, using a grading rubric based on completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

7.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration of information from different AI system elements.

7.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, with submission of compliance verification report assessed for alignment with applicable legal, ethical, and organizational standards.

7.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for adaptability to variable AI project contexts, alignment with project-specific requirements, and accommodation of new system components.

5.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, and collaborative workflow evidence, with peer-review of contributions, assessed for independent application of document-management and collaboration practices in AI projects.

5.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, using a grading rubric based on completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

5.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration of information from different AI system elements.

5.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, with submission of compliance verification report assessed for alignment with applicable legal, ethical, and organizational standards.

5.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for adaptability to variable AI project contexts, alignment with project-specific requirements, and accommodation of new system components. DEVELOPMENT & OPERATIONS [2]

3.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, and collaborative workflow evidence, with peer-review of contributions, assessed for independent application of document-management and collaboration practices in AI projects.

3.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, using a grading rubric based on completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

3.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration of information from different AI system elements.

3.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, with submission of compliance verification report assessed for alignment with applicable legal, ethical, and organizational standards.

3.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for adaptability to variable AI project contexts, alignment with project-specific requirements, and accommodation of new system components.

2.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

2.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

2.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

2.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards.

2.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.

3.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

3.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

3.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

3.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards.

3.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.

2.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

2.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

2.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

2.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards.

2.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.

2.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

2.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

2.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

2.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards.

2.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.

2.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

2.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

2.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

2.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards.

2.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.

3.1 Apply document-management and collaboration practices to AI projects independently, using systems that enable coordinated document creation and version control.

Assessed by Evaluation of AI documentation repository for organization, version control, coordinated document creation, collaborative workflow evidence, and peer-review of individual contributions.

3.2 Develop AI-specific technical, compliance, and transparency documentation for multiple system components, such as model specifications, system interfaces, and regulatory reports.

Assessed by Assessment of developed AI technical specifications, compliance records, and transparency reports for multiple system components, graded for completeness, accuracy, and coverage of model specifications, system interfaces, and regulatory reports.

3.3 Integrate information from different AI system elements into cohesive and accessible documentation, by consolidating data from datasets, model outputs, and system logs.

Assessed by Review of consolidated AI documentation integrating datasets, model outputs, and system logs, assessed for clarity, cohesion, accessibility, and accurate integration across AI system elements.

3.4 Ensure that AI documentation meets regulatory, ethical, and stakeholder requirements, in accordance with applicable legal, ethical, and organisational standards.

Assessed by Verification of AI documentation against regulatory, ethical, and stakeholder requirements, supported by a compliance verification report referencing applicable legal, ethical, and organizational standards

3.5 Adapt and modify existing templates or documentation structures to suit variable AI project contexts, by aligning documentation with project-specific requirements or new system components.

Assessed by Evaluation of customized AI documentation templates and modified project documentation, assessed for alignment with project-specific requirements, new system components, and adaptability to variable AI project contexts.