Skip to content
Natalie
PROTOTYPEAll pages

Unit titles and outcomes from Skills England (skillsengland.education.gov.uk/apprenticeship-units/AU0009–11), as copied into the old repo; confirm with the awarding body. The mapping to weeks, checks and tasks is invented. Read-only for the provider.

AI Leadership Programme · January 2027 cohort

Skills map · by week

Planned, taught and tested against the three government units.

Planned: all 19 outcomes. Taught so far: two covered, eight under way. Tested so far: nine with a passed multiple-choice test, seven with accepted assignments.

Export this report (CSV · PDF)

Session 1 · Getting started with AI at work

Thursday 7 January · taught · plans to touch 4 outcomes

  • Organisational leadership in setting AI policy and strategy, including business cases detailing implications for the workforce, organisational perception and sustainabilityAU0009.1taught
  • Evaluate opportunities for AI-driven improvement using qualitative and quantitative evidence, including the assessment of riskAU0009.2taught
  • Critically evaluate and monitor the implementation of adaptations, including responses to emerging AI technologies and trendsAU0009.6taught
  • Design and implement human oversight mechanisms for AI systemsAU0010.7taught

Session 2 · Asking well: prompts that work

Thursday 14 January · taught · plans to touch 2 outcomes

  • Evaluate AI solutions and vendors using structured criteria (cost, performance, risk, data readiness)AU0010.1taught
  • Make procurement decisions based on testing, benchmarking and user validationAU0010.2taught

Session 3 · Your inbox and your writing

Thursday 21 January · taught · plans to touch 2 outcomes

  • Embed ethical, legal and regulatory considerations into AI decision-making processesAU0010.5taught
  • Design and implement human oversight mechanisms for AI systemsAU0010.7taught

Session 4 · Meetings, research and briefs

Thursday 28 January · taught · plans to touch 5 outcomes

  • Engage stakeholders to build support for AI strategy and adoption, including non-technical audiencesAU0009.5taught
  • Evaluate AI solutions and vendors using structured criteria (cost, performance, risk, data readiness)AU0010.1taught
  • Assess risks associated with AI acquisition, including vendor lock-in, data, IP and sustainabilityAU0010.3taught
  • Design and implement human oversight mechanisms for AI systemsAU0010.7taught
  • Communicate AI risks and opportunities internally and externally, including with non-technical stakeholders and regulatorsAU0011.6taught

Session 5 · Data, reports and forecasts

Thursday 4 February · this Thursday · plans to touch 4 outcomes

  • Evaluate opportunities for AI-driven improvement using qualitative and quantitative evidence, including the assessment of riskAU0009.2planned
  • Assess viability and risk through AI use cases and pilots, identifying investment areasAU0009.4planned
  • Design and implement human oversight mechanisms for AI systemsAU0010.7planned
  • Monitor performance and risks of deployed AI systems, including bias, drift and security vulnerabilitiesAU0011.5planned

Session 6 · Documents and decks

Thursday 11 February · not yet taught · plans to touch 4 outcomes

  • Engage stakeholders to build support for AI strategy and adoption, including non-technical audiencesAU0009.5planned
  • Define assurance and compliance processes, including documentation, auditability and transparencyAU0010.6planned
  • Implement organisational-level AI risk management, including monitoring, the use of tools, mitigation and escalationAU0011.3planned
  • Communicate AI risks and opportunities internally and externally, including with non-technical stakeholders and regulatorsAU0011.6planned

Session 7 · Your own AI assistant

Thursday 18 February · not yet taught · plans to touch 4 outcomes

  • Assess viability and risk through AI use cases and pilots, identifying investment areasAU0009.4planned
  • Assess risks associated with AI acquisition, including vendor lock-in, data, IP and sustainabilityAU0010.3planned
  • Lead delivery of AI-enabled organisational change, ensuring AI solutions are sustainable and aligned to long-term objectivesAU0011.1planned
  • Monitor performance and risks of deployed AI systems, including bias, drift and security vulnerabilitiesAU0011.5planned

Session 8 · Leading AI safely in your team

Thursday 25 February · not yet taught · plans to touch 11 outcomes

  • Organisational leadership in setting AI policy and strategy, including business cases detailing implications for the workforce, organisational perception and sustainabilityAU0009.1planned
  • Define, document and communicate an AI strategy aligned to organisational goals, values and risk appetiteAU0009.3planned
  • Critically evaluate and monitor the implementation of adaptations, including responses to emerging AI technologies and trendsAU0009.6planned
  • Design and implement AI governance frameworks, including roles, responsibilities and escalation pathwaysAU0010.4planned
  • Embed ethical, legal and regulatory considerations into AI decision-making processesAU0010.5planned
  • Define assurance and compliance processes, including documentation, auditability and transparencyAU0010.6planned
  • Lead delivery of AI-enabled organisational change, ensuring AI solutions are sustainable and aligned to long-term objectivesAU0011.1planned
  • Assess and manage workforce impacts of AI adoption, including reskilling, role redesign and job displacementAU0011.2planned
  • Implement organisational-level AI risk management, including monitoring, the use of tools, mitigation and escalationAU0011.3planned
  • Achieve audit requirements and regulatory compliance, including incident and security response planningAU0011.4planned
  • Communicate AI risks and opportunities internally and externally, including with non-technical stakeholders and regulatorsAU0011.6planned