Level 4 AI and Automation Practitioner Apprenticeship

Future Talent Leaders' Programme

From early manager to experienced Talent, HR and L&D professionals, this programme builds practical AI capability alongside human-centred management skills to improve how work gets done across the employee lifecycle.

Level 4
Level 4

AI & Automation Practitioner apprenticeship

Duration
Duration
12 months + end point assessment
Qualification outcomes
Qualification outcomes
  • Level 4 AI & Automation Practitioner Apprenticeship
  • Microsoft Azure AI Fundamentals certification

 

Audience
Audience

Talent, TA, HR, OD professionals responsible for improving workflows, operational performance or service delivery

Funding
Funding

Fully fundable via the Apprenticeship Levy - funding band £18,000 

Time commitment
Time commitment
Approx. 4 hours per week protected learning time

Programme overview

Developing the next generation of talent leaders for an AI-driven world of work. Created in partnership with Chapter 2.

Delivered through the Level 4 AI & Automation Practitioner Apprenticeship, the programme develops applied AI, digital and workflow improvement capability in Talent, HR and L&D professionals, while strengthening stakeholder management, communication and decision-making capability.

Skills and capabilities developed

AI fundamentals for Talent
AI tools and workflows
Responsible AI and governance
Hiring and workforce planning
Learning and performance workflows
Human-centred design
Stakeholder influence
Communication and change adoption
Value-case development
Measurement and impact tracking

Evidence & outcomes

Our programmes deliver measurable improvements in management capability and organisational performance.

FTL-Microsft

Microsoft AI Certification Included

Microsoft Azure AI Fundamentals included

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Ofsted rated "good"

With 53% of participants promoted during or after the programme

award

100%

Participants report improved management capability
award

85%

Distinction rate across programmes, and 100% pass rate

Programme positioning

Who is this
programme for?

Professionals responsible for improving operational performance, services or workflows using digital tools, automation and AI.

This programme is relevant wherever individuals are responsible for efficiency, quality or service

Talent acquisition and hiring roles
• Talent partners
• TA managers
• Recruitment managers
• Hiring and onboarding leads
HR and people roles
• HR managers
• HR business partners
• People partners
• Employee experience leads
Learning and OD roles
• L&D managers
• Learning partners
• OD professionals
• Performance and capability leads
Transformation roles (people-focused)
• Workforce transformation leads
• Talent programme managers
• HR project managers
• Change professionals in people functions

Where this
programme fits

This programme builds AI-enabled Talent capability for organisations that want to improve how people work gets done across hiring, onboarding, learning, performance, engagement and workforce planning.


Core AI capability pathway for Talent functions
Improves employee lifecycle workflows
Builds responsible AI adoption in HR
Strengthens stakeholder influence and communication
Future-proofs Talent and HR capability

Capabilities developed

Our programmes develop applied AI, data and management capability — enabling Talent professionals to improve performance, lead change and deliver measurable organisational impact.


AI-enabled talent capability - automation for talent use cases
Operational capability - Talent workflow improvement
Human capability - Collaboration, communication and influence
Commercial capability - Prioritising automation opportunities with real ROI
Collaboration capability - Working across operational and technical teams
Transformation capability - Embedding adoption and continuous improvement

Organisational outcomes

Organisations typically use this programme to build AI-enabled productivity improvement capability across teams.

Higher-value Talent workflow improvements identified
Safer and more effective AI adoption in HR
Stronger stakeholder alignment and adoption
Improved decision-making and prioritisation
Future Talent leadership capability built

Why this programme?

This is not just another HR or leadership course. It helps Talent professionals move from AI curiosity to real workflow improvements — spotting high-value opportunities, running practical pilots safely, building stakeholder alignment, and embedding adoption with measurable impact.

Levy-funded AI and management capability

AI-enabled learning platform

Supported by Microsoft with AI certification

Transform talent workflows into AI-powered automations

Time-efficient:
learning fits the working week

The real constraint with professional development is rarely funding — it is time.

Our programmes are designed to work with the flow of real work, not compete with it.

Participants typically commit around four hours per week, combining structured learning, coaching and applied missions directly linked to their role.

This ensures development strengthens day-to-day performance while building capability for the future.

 

12 month programme overview

Structured curriculum missions are combined with live workshops and peer learning so participants build capability progressively through real work. It also provides opportunities for real-world networking with peers at talent community events.
For more detail download the programme prospectus.

Curriculum missions

Participants complete monthly applied missions designed to improve real talent, TA and HR workflows in their organisation.
01

Spot the opportunity

Identify high-value Talent opportunities
02

Map the talent workflow

Analyse talent processes, bottlenecks and failure points
03

Feasibility and risk scan

Evaluate data quality, viability and risk
04

Option design

Design improved talent workflows with AI and automation
05

Tool and platform evaluation

Assess automation tools and technology options
06

Solution design workshop

Define talent/HR requirements and agree MVP solution
07

Configure low-code automation

Build talent workflows and pilots
08

Integrate and document

Connect systems and document new workflows
09

Test and iterate

Monitor results and refine automation
10

Adoption and training

Support colleagues / candidates and embed new workflows
11

Governance and assurance

Implement controls, documentation and oversight
12

Measure value and scale

Demonstrate ROI and expand improvements

Live learning events

Live learning workshops allow participants to practise new approaches, discuss real workplace challenges and deepen understanding through guided discussion.
01

Which automations really matter?

Identify high-value automation opportunities with measurable impact.
02

Process mapping for automators

Map talent workflows to identify bottlenecks and automation opportunities.
03

Responsible & ethical AI

Apply governance, ethics and accountability in AI systems.
04

Selecting from the tool landscape

Evaluate automation and AI tools for talent needs.
05

Human-in-the-loop-design

Design talent workflows balancing automation with human oversight.
06

Running a solution design workshop

Facilitate collaborative workshops to define automation solutions.
07

Building reliable workflows

Design dependable automations that handle real-world complexity.
08

Prompt engineering for better outputs

Improve AI performance through structured prompting techniques.
09

Integration basics for non-engineers

Understand APIs, authentication and data connections between systems.
10

Driving adoption of automation

Support talent teams adopting new workflows and automation tools.
11

Governance and audit readiness

Ensure automations meet governance, compliance and audit requirements.
12

Proving value and ROI

Measure productivity improvements and communicate automation impact.
13

Facilitation

Lead structured discussions and collaborative problem solving.
14

Change leadership

Support talent teams adapting to automation and new ways of working.
15

Storytelling

Communicate ideas, insights and improvement outcomes clearly.
16

Relationship building

Build trust and collaboration across talent teams and stakeholders.
17

Leading change

Support teams through change and organisational transformation
18

Collaboration

Work effectively across operational, digital and technical teams.
19

Problem solving

Use structured thinking to diagnose and solve complex talent problems
20

Stakeholder management

Align stakeholders around automation priorities and improvement goals.

Live peer study groups

Monthly coach-facilitated sessions provide a structured space to exchange ideas, share challenges and explore how learning can be applied in real Talent, HR and L&D contexts.
01

Find the use case

Prioritise high-value Talent workflow opportunities
02

Map the workflow

Spot friction, delays and duplication
03

Balance humans and AI

Decide where oversight matters most
04

Design better hiring

Improve hiring and onboarding workflows
05

Improve learning workflows

Apply AI in L&D responsibly
06

Build stakeholder buy-in

Align HR, Talent and business leaders
07

Run safer pilots

Test ideas without creating avoidable risk
08

Manage AI risk

Address privacy, bias and accountability
09

Embed adoption well

Support training, comms and behaviour change
10

Measure what matters

Track ROI, quality and time saved
11

Influence without authority

Build credibility across complex stakeholder groups
12

Lead Talent through AI

Future-proof Talent capability and judgement
13

Managing risk in AI projects

Share approaches to risk mitigation
14

Building AI capability across teams

Explore how organisations scale adoption
15

Measuring productivity improvements

Discuss metrics and impact measurement
16

Continuous improvement with AI

Embed iterative optimisation in workflows

Weekly delivery model

Approx. 4 hours of protected learning time per week One of the most time-efficient delivery models.

Structured learning: approx. 4 hours per week

50%

AI-enabled learning + human coaching + interactive workshops

Participants build capability through a blend of:

• self-paced learning modules
• interactive live workshops
• guided exploration using AI learning tools
• peer study groups and coaching support.

These sessions introduce practical frameworks, tools and approaches that can be applied immediately at work.

Applied learning in the workplace: approx. 4 hours per week

50%

Applied & project-based learning

Participants apply learning directly to real workplace challenges through monthly missions and work-based workflows. Learning strengthens existing work.

This ensures development is:
• immediately relevant
• visible to the organisation with measurable productivity improvements
• embedded in day-to-day performance

The FTL learning experience

Development is designed around how adults learn most effectively at work — through applied practice, reflection, coaching and collaboration.
Find out more

Real workplace challenges drive learning.

Participants apply new skills directly to their role through structured monthly missions linked to real organisational priorities.

FTL-Applied-learning-missions
FTL-Quote-Stephen
To be considered the best in your industry, you don’t need to be the best at any one thing. You need to be good at a variety of complementary and rare skills your industry values and that your competitors lack. ‍Steven Bartlett, The Diary of a CEO‍ & Future Talent Leaders’ Programme Ambassador
FTL-Quote-babcock
FTL’s highly customised programme has become the core of our management development strategy. The FTL team are slick, knowledgeable, responsive and a pleasure to work with. - Nick Dormor, Senior Learning Specialist, Babcock
FTL-Quote-Ofsted
FTL provides top-tier, highly engaging, innovative and effective methods of learning, leading to high success rates and impact that line managers can observe. — Ofsted, Sept 2024

Frequently asked questions about the Level 4 AI & Automation Practitioner apprenticeship

See our full FAQs page for more information or Contact us if you have any questions.
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