Competency Assessment
Restart
This competency self-assessment prototype is aligned to the AI Skills for Business framework and uses a mixed Knowledge, Skill, and Behaviour model.
It is designed as a competency profile, not a traditional exam: responses are mapped to duties and competency evidence to produce strengths, development areas, and practical next steps.
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Competencies
C1 : Identifies where AI operates in daily life and understands its basic functions and limits.C2 : Engages with AI-driven tools and services thoughtfully, understanding both benefits and risks.C3 : Understands user rights, choices and complaint routes when AI affects access, pricing, or critical services and opportunities.C4 : Understands how personal data is collected, processed, and used to train and personalise AI systems.C5 : Takes active steps to protect personal data and manage privacy across AI enabled platforms.C6 : Shares only what is necessary, understands consent choices, and reviews permissions regularly.C7 : Demonstrates awareness of AI-generated material and understands its implications for information integrity. C8 : Critically assesses the reliability and fairness of AI-generated outputs before accepting or sharing them.C9 : Demonstrates awareness of the risks of sharing AI-generated content by pausing, checking context, and adding sources when appropriate.C10 : Detects and avoids harmful or deceptive uses of AI, including fraud, manipulation, or misinformation.C11 : Recognises and responds to instances of unfairness, exclusion, or bias in AI systems and promotes equitable practices.C12 : Knows where and how to report AI-related scams, abuse, or unfair outcomes and helps others do the same. C13 : Contributes to conversations about AI with respect and evidence.C14 : Contributes to AI related discussions by actively listening, sharing perspectives and respecting diverse experience.C15 : Makes space for different experiences and needs so public conversations about AI are fair and inclusive.C16 : Comply with data protection policies and safeguard sensitive information when using AI systems.C17 : Use AI-powered platforms confidently and effectively in everyday work.C18 : Explore and experiment with AI tools responsibly, ensuring alignment with organisational policies.C19 : Demonstrate and promote ethical awareness in everyday AI use by respecting privacy, questioning outputs, and encouraging responsible practices among colleagues.C20 : Use AI safely and inclusively in collaborative settings, promoting transparency and equitable participation, with awareness of potential bias and accessibility limitations.C21 : Be transparent about the role of AI in producing work outputs.C22 : Apply AI tooling into workflows responsibly, ensuring alignment with organisational policies and practices.C23 : Interpret AI-driven outputs critically and apply professional judgement.C24 : Adapt to the changing nature of work through ongoing engagement with AI tools.C25 : Contribute to organisational learning about AI use.C26 : Serve as a local advocate for the effective and ethical use of AI tools and practices within their team or department.C27 : Provide first-line guidance and support to co-workers on appropriate AI use and troubleshooting common issues.C28 : Encourage compliance with organisational AI policies and data governance standards,C29 : Identify areas where AI can support efficiency, innovation, or service improvements, and share recommendations with leadership. C30 : Encourage participation in AI training, sharing resources and best practice examples with colleagues.C31 : Act as a liaison between frontline staff and senior leadership, feeding back on staff needs, adoption challenges, and success stories.C32 : Keep up to date with developments in AI tools and organisational policy, ensuring colleagues are aware of relevant updates and guidance.C33 : Demonstrate effective use of AI by modelling good practice of AI use in day-to-day tasks, showcasing practical and responsible applications that inspire peers.C34 : Demonstrate ownership of personal development and engage in continuous learning activities.C35 : Design and develop data-driven solutions and AI systems.C36 : Test and monitor AI systems to assess performance and accuracy.C37 : Ensure that AI systems are designed and developed in an ethical, safe and responsible way.C38 : Project and change management through delivery of innovative projects.C39 : Apply rigorous methodology to generate, validate and share knowledge that supports responsible AI practices.C40 : Design and maintains data architectures, pipelines, and infrastructure that support reliable, secure, and scalable AI operations.C41 : Evaluate human-AI collaboration and ensure AI systems are aligned with user needs.C42 : Contribute to the design, development and deployment of AI systems in alignment with defined purpose, policy and ethical standards that include safety, robustness and reliability.C43 : Uphold professional standards in data stewardship, model evaluation and stakeholder engagement.C44 : Design AI architectures that align technical, ethical, and organisational objectives.C45 : Effectively select, integrate, and contribute to open-source tools, frameworks, and libraries that support robust and reproducible AI system development.C46 : Engage with open-source communities in ways that uphold ethical, secure, and inclusive practices, promoting responsible participation in the AI ecosystem.C47 : Collect and prepare the required datasets in line with organisation standards, ensuring accuracy, compliance and readiness for AI project use.C48 : Support the application of AI and related technologies in ways that uphold rights, promote trust and deliver value.C49 : Collaborate effectively in multidisciplinary AI development teams.C50 : Implement, customise, and optimise low-code and no-code solutions that address organisational challenges, improve workflows, and enhance efficiency.C51 : Advocate for and ensure automation solutions are implemented responsibly, with fairness, transparency, and consideration for workforce wellbeing.C52 : Develop and apply methods to ensure AI explainability and interpretability to ensure that AI systems are transparent, interpretable, and understandable to appropriate audiences.C53 : Design and operate AI systems with due consideration for environmental and social sustainability.C54 : Apply AI governance and risk management principles to ensure compliance and accountability.C55 : Support the development of AI systems to proactively manage potential workforce impacts.C56 : Support the responsible, ethical and safe adoption of AI.C57 : Ensure responsible governance, security and stewardship of data across the AI lifecycle.C58 : Support documentation and auditability of AI systems and tooling.C59 : Deploy data-driven and AI solutions and integrate them with organisation's systems.C60 : Maintain and continuously improve deployed AI systems.C61 : Ensure the security, robustness, and resilience of AI systems.C62 : Contribute to the ongoing evaluation and refinement of solutions to ensure they remain effective and responsible, and aligned with evolving contexts.C63 : Performance management and continuous improvement.C64 : Engage senior leadership, end-users and relevant stakeholders across all phases of the Data and AI Lifecycle to ensure systems and data-driven solutions are fit for purpose.C65 : Support leadership and advocate for responsible introduction of artificial intelligence solutions.C66 : Communicate effectively with a range of audiences, ensuring clarity, transparency, and timeliness in reporting progress on AI throughout the AI project lifecycle.C67 : Design and develop data-driven and AI solutions that are intuitive and human-centred.C68 : Collaborate across disciplines to identify risks, integrate diverse perspectives and support responsible innovation.C69 : Research, critically evaluate, and apply emerging knowledge to AI automation developments, ensuring practice remains current, ethical, and forward-looking.C70 : Evaluate emerging AI technologies and their potential societal impact.C71 : Support learning, mentorship, and capacity building in responsible and ethical AI practice.C72 : Engage with and/or develop governance processes that enable validation, oversight and escalation.C73 : Evaluate and oversee external AI vendors and third-party tools to ensure technical fitness, compliance, and responsible operation.C74 : Define and communicate a coherent AI strategy that aligns with organisational goals and values.C75 : Balance innovation with practical delivery in AI adoption.C76 : Sponsor governance frameworks that safeguard lawful, ethical and responsible AI use.C77 : Embed ethical principles in AI decision-making and operations.C78 : Select AI vendors and suppliers through fair and evidence-based evaluation.C79 : Select technology platforms that meet organisational needs and mitigate long-term risks.C80 : Plan and manage workforce transformation resulting from AI adoption.C81 : Drive reskilling and learning to prepare staff for AI-enabled roles.C82 : Manage AI risks within the organisation’s broader enterprise risk framework.C83 : Ensure readiness for AI-related audits and incidents.C84 : Create a culture that enables responsible innovation in AI.C85 : Build trust and transparency in organisational AI use.C86 : Act as a credible advocate for the organisation in AI policy and regulatory discussions.C87 : Build trust with the public and external communities on AI use.C88 : Monitor regulatory changes and prepare the organisation for compliance.C89 : Oversee the embedding of regulatory readiness into business processes.C90 : Supports peers and communities to understand and use AI responsibly through clear guidance and examples.C91 : Shares AI knowledge and practices in ways that are understandable to colleagues of different backgrounds.C92 : Helps others understand their data and consumer rights and encourages the use of service settings that prevent unnecessary sharing of user data or contribution of content to model training.