This module introduces apprentices to artificial intelligence and automation as practical workplace technologies, equipping them with the literacy and analytical skills needed to recognise opportunities for improvement in their own organisations. It covers the core concepts — what AI and automation are, what current tools can and cannot do, and where they typically create value. This gives apprentices the process-mapping techniques to identify genuine opportunities in real workplace settings. As the opening module of the apprenticeship, it deliberately establishes the breadth of subjects that later modules will develop in depth, and instils the professional dispositions of curiosity, evidence-based reasoning and responsible scepticism that an AI and Automation Practitioner needs from day one.
This module equips apprentices with the data literacy and practical handling skills needed to make AI and automation work in real organisations. Most AI projects fail not because the AI is inadequate but because the data feeding it, is messy, ungoverned, or poorly understood. The module covers how to identify, profile and prepare data from realistic workplace sources; how to integrate data between systems using Application Programming Interfaces (APIs) and connectors; and how to handle data ethically and lawfully under UK GDPR and accessibility standards. As the second module of the apprenticeship, it sets up the practical building work that follows in later modules and establishes the data-protection and ethical-handling foundations that are also developed in depth later.
This module provides the practical core of the apprenticeship. Apprentices configure, integrate and ship real working automations using contemporary low-code and no-code tools (Power Automate, Zapier, Make), engineer prompts for generative AI tools, and combine these into AI-powered workflows that solve real workplace problems. The module is hands-on and iterative throughout: apprentices design solutions to their employer's needs, test them with real users, refine them based on feedback, and deploy them into the workplace. As the third module in the apprenticeship, it builds on the data foundations of Module 2 (Data for AI) and runs in parallel with Module 4 (Responsible AI), so that apprentices learn to build with the ethical and governance frameworks rather than separately from them. The module's emphasis on user-centred design, oversight and feedback loops establishes the design discipline that underpins the synoptic Project.
This module equips apprentices with the legal, regulatory, ethical and assurance foundations needed to deploy AI and automation responsibly in UK workplaces. It moves from theoretical frameworks to practical assurance work: apprentices learn to conduct algorithmic impact assessments on real workplace use cases, apply fairness metrics, document assurance and governance evidence, and monitor deployed AI for drift, emerging bias and post-deployment risk. The module is delivered in parallel with Module 3 (Building AI Workflows) so that ethical and governance thinking is built into design and development rather than bolted on afterwards. The professional behaviour of constructive challenge (sharing concerns or alternative perspectives under pressure) is established here and developed across the rest of the course.
This module equips apprentices to be the bridge between AI technology and the people who use it. Evidence on AI adoption is still emerging, but common patterns are visible: projects can fail because staff resist, leaders disengage, training is inadequate, or workforce impacts are mismanaged. Organisations can equally over-adopt AI in contexts where it isn't relevant or sensible or allow generative AI to be used as a way of offloading judgement and accountability rather than genuinely supporting it. The module covers the leadership, change management, communication, training and collaborative working needed to make adoption decisions, including the decision not to adopt, appropriately and responsibly. Apprentices learn to engage with non-technical staff respectfully, design and deliver training adapted to diverse audiences, communicate complex concepts in accessible formats, and support leaders to consider workforce impact alongside organisational gains. The professional behaviours of empathy, confidentiality and respect for individual contributions, balanced advocacy and confidence under pressure are owned and developed here. As the final teaching module, it consolidates the apprentice's professional identity and sets up the synoptic Project.
This is the synoptic assessment module for the apprenticeship. Apprentices consolidate the learning from Modules 1–5 into a substantial work-based Project demonstrating competence across all six Assessment Outcomes in the ST1512 v2.1 Apprenticeship Assessment Plan and complete a Professional Discussion with the contracted Assessment Organisation. The module is the principal vehicle for the apprenticeship outcome (Pass or Distinction) and contributes 20 credits to the LSBU Certificate of Higher Education.
The module is not a teaching module: apprentices have completed their substantive learning in Modules 1–5. This module is a structured 3-month consolidation period in which the apprentice produces, refines and presents their evidence of competence, supported by individual tutorial supervision, structured mock assessments, and Skills reviewer engagement. The module's three-month duration provides the time needed to deliver a substantial workplace artefact, prepare for Professional Discussion, and complete all assessment activity before the apprenticeship certificate is conferred.
