Introduction

 

Apprenticeship units are short flexible training courses designed to support employers to upskill their workforce in critical skill shortage areas. Units are for employed learners aged 19 and over, where their employer has identified that they need to upskill quickly to respond to emerging skills gaps and to support business growth and productivity.

Apprenticeship units are based on relevant knowledge and skills in existing employer-led occupational standards to ensure relevant high-quality, targeted training. Each unit is short, with the length of training ranging from 30 and 140 hours delivered over a period of 1 to 16 weeks. This enables employers to have maximum flexibility to select a unit that meets their specific skill need and to deliver the training in a way that fits around their business.

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Who is it for?

 

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.

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Learning outcomes

 

A learning outcome is a concise statement that describes what an individual should be able to do by the end of their course. It summarises a cluster of knowledge and skills in the course and provides a foundation for assessment.

Learning outcomes

• Lead delivery of AI-enabled organisational change, ensuring AI solutions are sustainable and aligned to long-term organisational objectives.

• Assess and manage workforce impacts of AI adoption, including reskilling, role redesign, anticipating and responding to potential job displacement and workforce reduction. Assess the impact on the organisation’s wider ecosystem, for example, suppliers and digitally excluded groups. 

• Implement organisational level AI risk management, including monitoring, the use of tools, mitigation and escalation. 

• Achieve audit requirements and regulatory compliance, including incident and security response planning.

• Monitor performance and risks of deployed AI systems, including bias, drift and security vulnerabilities.

• Communicate AI risks and opportunities internally and externally, including communication with non-technical stakeholders, and regulators.