Apprenticeship unit

AI leadership – AI delivery and organisational transformation - Apprenticeship unit (level 5)

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Information about AI leadership – AI delivery and organisational transformation - Apprenticeship unit (level 5)

This apprenticeship unit is for individuals in leadership roles responsible for setting direction and who have oversight of AI use, who, with the support of their employer, need upskilling in the safe and effective delivery of AI-enabled organisational transformation. It is suited to those overseeing implementation of AI and ensuring that AI solutions are integrated effectively into organisational processes and ways of working.

Apprenticeship units are short, flexible training courses based on employer-designed occupational standards.

You can only enrol your existing employees in an apprenticeship unit. Employees who are already doing an apprenticeship cannot do them.

• Knowledge and skills learners will gain:
  View knowledge and skills

  Technical knowledge

  • AI and automation concepts and models that support leadership decision-making, and their limitations. The impact adoption may have on workplace culture and wellbeing.
  • The capabilities, benefits and risks of automation, AI and digital tools, including responsible use, ethical considerations and the potential impact on the workforce.
  • The role of organisational leadership in responsible AI adoption, including setting values, policy, and strategy. The business case for ethical AI adoption, including reputational risk, staff engagement and morale, and long-term sustainability.
  • Understand how to develop and implement organisational AI strategy and plans, including approaches to workforce development, taking and managing risk, monitoring and evaluation, and quality assurance.
  • How to assess the viability of solutions when making acquisition decisions, for example, testing and evaluating solutions, using test data and results, feasibility (time, cost, data quality and process maturity), and user testing.
  • The capabilities, risks and implications of adopting on-premise, cloud-based and third-party solutions.
  • Governance principles to ensure accountability and compliance, including defining roles and responsibilities to identify, escalate and mitigate threats or risks to assets, data and cyber security.
  • Crisis and risk management strategies including accountability and technological implications.
  • Principles of human oversight and human AI collaboration to achieve shared outcomes.
  • Principles for operationalising sustainable AI solutions to support organisational strategies and objectives.
  • Governance principles to ensure accountability and compliance, including methods to identify system vulnerabilities and mitigate threats or risks to assets, data and cyber security.
  • Engagement and training approaches used with non-technical staff to understand their roles, responsibilities, and concerns when AI automation solutions are proposed, in support of strategic AI governance decisions.
  • Principles to support project and change management delivery.
  • Principles and practices of algorithmic impact assessment and workforce equality monitoring, including methods to identify, assess, and mitigate potential disproportionate impacts of automation and AI systems on different workforce groups. Organisational responsibilities under equality and employment law, and methods to evidence fairness and transparency in adoption.
  • Principles and practices for the long-term monitoring of AI and automation solutions, including detection and mitigation of risks such as model drift, emerging bias, degraded performance, and security vulnerabilities.

  Technical skills

  • Identify organisational improvements and opportunities for innovation and growth, using qualitative and quantitative analysis of information and data.
  • Set strategic direction for AI and gain support for it from key stakeholders.
  • Commission analysis to identify if AI adoption is viable. Evaluate assessments of risks and unintended consequences of AI automation projects, such as the impact on job roles.
  • Use evidence to inform governance of AI adoption, outcomes and facilitate improvement.
  • Ensure sustainable and efficient AI and automation solutions.
  • Ensure business needs are aligned with technical capabilities, to ensure solutions are scalable, efficient, and aligned with the organisation’s strategic objectives.
  • Apply principles relating to ethics and values-based leadership and governance, and regulatory compliance.
  • Lead and respond in a crisis situation using risk management techniques.
  • Use project management principles, techniques and tools to support the development of clear, balanced AI communications and briefings, articulating both opportunities and risks.
  • Lead deployment of AI and automation strategies, including measures to deal with the impact of automation, for example, workforce engagement, retraining, redeployment, or upskilling of affected staff.
  • Present and communicate information, including the translation of technical concepts into accessible materials to support clear dialogue with stakeholders.
• Training category (sector): Digital
• Training level: 5; Equal to higher national diploma (HND)
• Delivery hours: 30 delivery hours ; Delivery hours are the minimum amount of time a learner will spend with their instructor while on the course. This does not include coursework or self-paced activities.
• Duration: Exact duration depends on the training provider. Contact them to find out more.
• Maximum funding: £750 ; Maximum government funding for ; apprenticeship unit training and assessment costs.

View more information about AI leadership – AI delivery and organisational transformation - Apprenticeship unit (level 5) from Skills England.