Artificial Intelligence (AI) and Automation Practitioner Apprenticeship, Level 4

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The apprentice should understand organisational objectives, processes and the role of digital technologies in improving efficiency and productivity.

• They will identify opportunities to improve business processes through the use of AI and automation, analysing existing workflows to reduce manual tasks and inefficiencies.
• They will design, build and implement AI-driven and automated solutions using low or no-code tools, integrating systems and improving operational performance.
• They will work with stakeholders across the organisation to understand requirements, communicate solutions and support adoption of new technologies.
• They will ensure the safe, ethical and responsible use of AI, including data protection, bias awareness and compliance with organisational and legal requirements.
• They will test, monitor and evaluate automation solutions, making improvements based on feedback and performance data.
• They will contribute to continuous improvement by identifying further opportunities for automation and innovation across the organisation.
• They will understand how their role supports wider organisational goals, digital transformation and productivity improvements.

Expectations:

• Strong communication and stakeholder engagement skills
• Problem solving and analytical thinking
• Ability to identify opportunities and drive improvement
• Organisation and attention to detail
• Ethical and responsible use of technology
• Adaptability and willingness to learn new digital tools

Study Overview

Artificial Intelligence (AI) and Automation Practitioner apprentices have their course delivered in the workplace. A Work Based Tutor will be assigned to work with the apprentice and employer, delivering 1:1 support and guidance throughout the programme at college.

This occupation is found in a wide range of sectors and organisations that rely on digital tools, online systems and data-driven processes to operate efficiently. Employees in this occupation support improvement wherever digital workflows exist and are typically embedded in operational teams, working in digital support roles or in change delivery functions. They may also be employed by consultancies or service providers helping organisations optimise internal and customer-facing processes.

The broad purpose of the occupation is to enhance productivity, streamline processes and support continuous improvement through the safe and responsible use of automation, integration and AI tools. They understand, select and implement digital solutions to address inefficiencies in existing systems. Their work is focused on solving real-world challenges that slow down business operations such as manual tasks, duplicated data entry, unintegrated tools and inefficient workflows. They play a key role in unlocking time and cost savings supporting organisations to realise the potential for AI, automation and digital solutions to improve efficiency, accuracy or productivity.

In their daily work, an employee in this occupation interacts with internal stakeholders across a variety of teams such as operations, service delivery, customer support or finance, depending on the organisation. They may also engage with external suppliers or digital tool providers to implement new systems or assist with integrations. They report to team leaders, service managers or project owners and work closely with colleagues to analyse and support existing ways of working. They use communication, collaboration and feedback skills to align their automation work with wider organisational goals.

An employee in this occupation will be responsible for identifying opportunities to improve workflow efficiency and productivity using digital tools. They will analyse current systems and processes, make recommendations utilising low-or no-code solutions including AI-driven automations. They will support with user adoption, facilitating the responsible, safe and ethical use of AI, automation and digital solutions, ensuring they align with organisational policies and user needs.

While they are not expected to lead teams, they are responsible for taking ownership of specific projects or tasks that deliver tangible operational value.

Progression and Employment Opportunities

Example progression routes include employment or further study in the following areas:

• Data Engineer
• Data Scientist (intergrated degree)
• AI Data Specialist
• AI Integration Officer
• Business Process Support Executive
• Junior Innovation Consultant