The AI Strategy & Opportunity apprenticeship unit (AU0009) helps business leaders develop the skills required to create effective AI strategies, govern AI adoption responsibly, identify high-value AI opportunities and manage organisational risk.
Designed for managers, directors and transformation leaders, the 4-day programme provides practical frameworks for AI governance, responsible AI implementation and AI-driven business transformation.
Whether you're exploring AI adoption for the first time or developing a structured AI strategy, the AI Strategy & Opportunity apprenticeship unit (AU0009) provides the knowledge and frameworks needed to lead confidently in an AI-enabled workplace.
Gain the strategic insight needed to identify AI opportunities, evaluate risks and align AI initiatives with organisational objectives.
Learn how AI can support departmental performance, improve decision-making and enhance operational efficiency across teams.
Develop the skills required to assess AI opportunities, support organisational change and deliver successful AI-enabled transformation programmes.
Understand how AI can streamline processes, improve productivity and support continuous improvement initiatives.
Build expertise in AI strategy, governance and implementation to help drive innovation and digital transformation across the organisation.
Strengthen your ability to evaluate AI technologies, establish governance frameworks and align AI investments with business priorities.
Explore the strategic and organisational considerations required to implement AI responsibly and effectively at scale.
Identify practical AI opportunities that can support growth, improve customer experiences and create competitive advantage.
The AI Strategy and Opportunity Apprenticeship Unit (AU0009) is a Level 5 AI Leadership programme approved by Skills England.
It enables employers to develop senior leaders who can identify AI opportunities, build organisational AI strategies and oversee responsible adoption.
Unlike a full apprenticeship, the unit is a short programme designed to upskill existing employees quickly using Growth and Skills Levy funding.
This programme is particularly valuable for leaders looking to:
Whether you're a senior manager, director, technology leader or business owner, this AI leadership course provides practical skills to help you harness AI opportunities while ensuring responsible and effective implementation.
A full breakdown of how apprenticeship units are funded is available below, specific to both Levy and Non-Levy paying employers.
Levy Employer:
Fully funded directly from your Digital Apprenticeship Service (DAS) account, subject to available funds.
Levy Employer with insufficient funds / co-investment:
95% is funded by government co-investment, you agree to pay a mandatory 5% cash contribution.
Non-Levy Employer:
Fully funded using your reservation made via the Government's apprenticeship service website.
The AI Strategy & Opportunity Apprenticeship Unit is assessed daily through:
Scenario-based group tasks
Facilitated discussion and questioning
Applied mini-assessments
Curriculum Sequencing:
Day 1–2: Build conceptual understanding → leadership strategy
Day 3: Apply analytical and evaluation techniques
Day 4: Embed governance and operational delivery
Core focus: AI concepts, models, and leadership implications and cultural, ethical, and workforce considerations.
Session Breakdown:
1. AI & Automation Fundamentals in Leadership Context
Types of AI (predictive, generative, automation systems)
Strengths vs limitations of AI models (bias, hallucination, data dependency)
Real-world leadership use cases
2. Organisational Impact of AI Adoption
Culture, job redesign, wellbeing implications
Workforce transformation vs displacement
Change management considerations
3. Ethical & Responsible AI
Bias, fairness, transparency, accountability
Regulatory considerations (UK/EU AI governance landscape)
Responsible AI frameworks
4. Horizon Scanning & Emerging Trends
AI trends shaping industries (automation, co-pilots, autonomous systems)
Evaluating vendor claims vs reality
Practical Activity:
Case study: AI implementation failure vs success (root cause analysis)
Group task: Identify ethical risks in a simulated AI rollout
Outputs: Ethical risk log and emerging trends briefing.
Core focus: Leadership responsibility in AI adoption and building organisational AI strategy.
Session Breakdown:
1. Leadership Role in AI Strategy
Setting organisational vision and values for AI
Governance structures and accountability
Aligning AI to business objectives
2. Building the Business Case for AI
ROI vs Risk vs Reputation
Staff engagement and organisational trust
Sustainability and long-term value
3. Developing AI Strategy & Roadmaps
Strategic planning frameworks
Workforce development planning
Risk management approaches
4. Stakeholder Engagement
Gaining buy-in from leadership and operational teams
Communicating AI strategy effectively
Practical Activity:
Develop an AI strategy outline for a chosen organisation
Outputs: Draft AI strategy and stakeholder engagement plan.
Core focus: Feasibility, procurement, and evaluation of AI solutions.
Session Breakdown:
1. Assessing AI Solution Viability
Feasibility analysis: Cost, time, data quality and maturity
Build vs Buy decisions
2. Testing & Evaluation Methodologies
Test environments and test data
Performance metrics and validation
User acceptance testing (UAT)
3. Risk Assessment & Unintended Consequences
Workforce displacement risks
Ethical and operational risks
Scenario planning
4. Data-Driven Decision Making
Using qualitative and quantitative data
Interpreting evaluation outputs
Practical Activity:
Evaluate a mock AI vendor solution
Outputs: AI solution evaluation report and risk assessment matrix.
Core focus: Policies, Governance and Human-AI integration.
Session Breakdown:
1. Data Governance & Security
Policies for AI and data usage
Compliance and regulatory considerations
2. Human Oversight in AI Systems
Human-in-the-loop vs Human-on-the-loop
Accountability frameworks
Decision escalation processes
3. Human-AI Collaboration Models
Augmentation vs Automation
Designing workflows that optimise human + AI performance
4. Continuous Improvement & Monitoring
Performance monitoring frameworks
Feedback loops and optimisation
Practical Activity:
Design a governance framework for AI adoption
Outputs: AI governance framework and Human-AI collaboration model.
If you don't feel this Unit is particular suitable for you, we have other AI Leadership Apprenticeship Units available, fully funded via the Growth & Skills Levy.
Designed to introduce how to set direction, governance and oversight for AI use for existing employees who need upskilling in AI leadership literacy.
Designed for employees responsible for adopting and governing AI systems within their organisation.
Designed for employees who are responsible for overseeing AI-enabled organisational transformation.
AI leadership training helps managers and business leaders understand how to identify, evaluate and implement artificial intelligence opportunities within their organisation.
It focuses on developing the strategic, governance and decision-making skills needed to lead AI adoption, manage risks and align AI initiatives with business goals.
Effective AI leadership training also covers responsible AI practices, organisational change and workforce readiness.
AI governance training teaches leaders how to establish policies, frameworks and controls that ensure artificial intelligence is used responsibly, ethically and in compliance with relevant regulations.
Topics typically include risk management, data governance, transparency, accountability, security and the ethical use of AI technologies.
AI governance training helps organisations build trust in AI systems while minimising operational and regulatory risks.
Managers learn AI strategy by developing an understanding of AI capabilities, identifying opportunities for business improvement and creating plans for successful implementation.
AI strategy training typically covers assessing organisational readiness, prioritising use cases, evaluating risks, measuring return on investment and aligning AI initiatives with broader business objectives.
Practical learning often includes real-world case studies and strategic planning frameworks.
Leading successful AI projects requires a combination of strategic, technical and leadership skills.
Key competencies include AI opportunity assessment, stakeholder management, project governance, risk management, data literacy, change management and effective communication.
Leaders must also understand ethical considerations and be able to guide teams through the adoption of new technologies while maintaining alignment with organisational goals.
The AI Strategy & Opportunity Apprenticeship Unit (AU0009) is for employees in leadership roles responsible for setting direction, governance and oversight for AI use, who need upskilling in AI leadership literacy.
It's particularly relevant for those in organisations at an early or exploratory stage of AI adoption, where there's a need to build a foundational understanding and identify viable opportunities.
No. This unit is not a technical or coding programme.
Learners do not need hands‑on experience building AI systems. Instead, the unit is designed for leaders who:
Influence or approve AI‑related decisions
Sponsor or oversee AI initiatives
Need confidence in AI strategy, governance, ethics and risk
A general familiarity with digital systems, data or organisational change is helpful, but training starts with leadership‑level AI literacy and builds from there.
By completing this Apprenticeship Unit, your employee will learn how to:
Set AI policy and strategy.
Evaluate opportunities for AI-driven improvement using qualitative and quantitative evidence.
Define, document and communicate an AI strategy aligned to organisational goals, values and risk appetite.
Assess viability and risk through AI use cases and pilots.
Engage stakeholders to build support for AI strategy and adoption, including non-technical audiences.
Critically evaluate and monitor.
All learning is applied directly to your own organisational context.
The unit is delivered through:
Facilitated leadership workshops.
Guided application to your organisation.
Structured reflection and portfolio development.
Delivery is remote, allowing employees to apply learning alongside their existing role.
Assessment is through a provider‑led skills test, which includes a portfolio of applied organisational artefacts, such as:
An AI strategy and prioritised use cases
An AI investment or procurement case
A professional discussion to confirm leadership judgement, decision‑making and application
There is no exam.
For employers, a breakdown of the funding requirements is below:
Levy Employer: fully funded directly from your digital Apprenticeship Service (DAS) account, subject to available funds.
Levy Employer with insufficient funds / Co-Investment: 95% is funded by government co-investment; the employer agrees to pay a mandatory 5% cash contribution.
Non-Levy Employer: fully funded using your reservation made via the apprenticeship service.
This Apprenticeship Unit is designed for short, intensive delivery, and is delivered in 4 consecutive days.
Your employee will remain in their role throughout and apply learning directly to live organisational priorities.
Throughout the unit, your employee will receive:
Support from an industry-experienced tutor
Clear guidance on portfolio development and assessment
Ongoing support through to completion
As the employer, you will also provide a workplace sponsor or mentor to support with the application of learning.
On completion, your employee will be better equipped to:
Lead AI strategy and governance within your organisation
Sponsor AI initiatives with confidence and credibility
Reduce ethical, regulatory and reputational risk
Support sustainable, responsible AI adoption
The unit also supports progression to Level 6 digital or data apprenticeships, or further executive‑level AI development.
Organisations can prepare for AI adoption by assessing their current capabilities, identifying high-value use cases and establishing clear governance frameworks.
Preparation should include developing AI skills across leadership teams, reviewing data quality and infrastructure, managing potential risks and creating a roadmap for implementation.
Successful AI adoption also requires employee engagement, change management and ongoing evaluation of outcomes.
Responsible AI governance is the process of ensuring that artificial intelligence systems are developed, deployed and managed in a way that is ethical, transparent, secure and accountable.
It involves establishing policies and controls that address issues such as bias, privacy, fairness and regulatory compliance.
Responsible AI governance helps organisations maximise the benefits of AI while protecting customers, employees and stakeholders.
AI strategy enables business leaders to make informed decisions about where and how artificial intelligence can create value.
A clear AI strategy helps organisations prioritise investment, manage risk, improve operational efficiency and remain competitive in a rapidly evolving market.
Without a defined strategy, AI initiatives can become fragmented, difficult to govern and less likely to deliver measurable business outcomes.
AI leadership training helps organisations build internal capability to identify opportunities, manage risks and implement AI effectively.
Benefits include improved decision-making, stronger governance, increased productivity, better alignment between technology and business goals, and greater confidence in adopting emerging AI technologies.
It also helps leaders prepare their teams for organisational change and future innovation.
From level 0 to 7, we’re here to help. Get in touch to discuss your needs and find the right programme for you.