AI and Automation Practitioner Apprenticeship

Apprentices will build core knowledge of data and AI systems, including how models work, their limitations, and potential biases. They will also develop practical skills in working with generative AI, including prompt and context engineering, learning how to structure, refine, and evaluate interactions to achieve reliable outcomes. Apprentices will explore how modern AI applications are designed and applied in practice, including the use of context-rich approaches such as retrieval-augmented generation (RAG), agent-based workflows, and other emerging patterns. They will learn how to select and apply appropriate tools and approaches based on specific tasks and organisational constraints, considering factors such as usability, data sensitivity, and reliability. This will help them understand how AI-enabled workflows are constructed and evaluated, while equipping them with the skills to critically assess new tools, adapt to evolving technologies, and make informed decisions about the effective use of AI in real-world contexts.

Apprentices will focus on designing, building, and deploying AI and automation solutions using low-code and no-code tools. This includes workflow design, system integration, APIs, connectors, and the configuration of AI-enabled processes within organisational environments. Apprentices will explore common AI solution patterns, including orchestrating multi-step workflows and integrating generative AI into business processes.

They will also develop the skills to work effectively with technical teams and stakeholders, learning how to translate business needs into clear technical requirements and communicate solution designs in a structured and practical way. This includes understanding implementation constraints, usability considerations, and how AI solutions fit within wider organisational systems and processes.

Apprentices will learn how to test, monitor, and optimise solutions, ensuring they are reliable, scalable, and capable of delivering sustained value in real-world organisational settings.

Apprentices will learn how to design and support the human side of change associated with AI and automation. The module takes a human-centred approach to AI adoption, focusing on how organisations can introduce new technologies in ways that support people, collaboration, and sustainable working practices. Apprentices will explore change management techniques including process mapping, stakeholder engagement, communication, training, and user adoption. Particular emphasis is placed on understanding how individuals and teams respond to change, and how inclusive approaches can improve engagement, confidence, and long-term adoption outcomes.

The module also examines the social and organisational impact of AI within workplaces, particularly in small and medium-sized organisations where people, culture, and ways of working are often central to successful implementation. You will develop the skills to work collaboratively with colleagues and support organisations in embedding AI-enabled change effectively and responsibly.

Apprentices will explore how AI and automation create value within organisations, including productivity, strategy, innovation, and competitive advantage. The module focuses on building the strategic case for AI adoption, helping them identify opportunities where AI can improve organisational performance and support long-term business goals.

A strong emphasis is placed on AI governance, responsible AI, risk, compliance, and ethical decision-making, reflecting the growing importance of trustworthy and accountable AI practices within organisations. You will examine how organisations can develop frameworks for managing AI responsibly, while balancing innovation with legal, ethical, and societal considerations. You will also explore organisational readiness for AI transformation, including leadership, culture, and the factors that influence successful strategic adoption.