AI Leadership - AI Adoption, Procurement and Governance - Apprenticeship Unit

The AI leadership – AI adoption, procurement and governance apprenticeship unit is a five-day live training programme designed for leaders who influence or make decisions about acquiring, implementing, and governing AI systems within their organisations.

This unit builds the strategic and practical capability required to move from AI ambition to defensible, evidence-based adoption. Learners develop the skills to evaluate AI use cases, assess suppliers and delivery models, manage risk, and design governance frameworks that ensure accountability and transparency across the AI lifecycle.

The programme places strong emphasis on ethical, legal, regulatory, and human-centric considerations. Participants learn how to embed responsible AI principles into procurement, oversight, assurance, and compliance processes, ensuring that AI systems are adopted in a way that supports organisational resilience and public trust.

Funding: This apprenticeship unit is funded through the Government’s Growth and Skills Levy. Levy-paying employers can use their levy funds to cover the cost of training, while non-levy employers typically benefit from government co-investment up to the published funding band.

Find out how your organisation could benefit from the Growth and Skills Levy.

Who is this programme for?

This apprenticeship unit is designed for:

• Senior leaders and managers
• AI sponsors and programme owners
• Heads of function with AI accountability
• Leaders responsible for AI risk, governance, or transformation

No prior technical AI expertise is required. The course is designed for non-technical leaders who need to make informed, evidence-based decisions about AI adoption and oversight.

What you will gain

• Gain confidence in evaluating AI systems and suppliers
• Strengthen their ability to manage AI-related risk and governance
• Improve their understanding of procurement and sourcing decisions for AI
• Develop structured approaches to assurance and compliance
• Enhance their credibility as accountable AI leaders

Throughout the programme, you will develop a holistic view of AI adoption, including:

• Translate AI strategy into structured, evidence-based adoption decisions
• Evaluate AI use cases using data, testing evidence, and feasibility assessment
• Assess technical delivery models and long-term operational risk
• Make defensible infrastructure, sourcing, and commercial decisions
• Evaluate AI suppliers and manage vendor risk
• Design governance and assurance mechanisms for responsible AI adoption
• Strengthen compliance, audit readiness, and oversight capability
• Embed human oversight and review across the AI lifecycle

Module 1: Foundations of Responsible AI Leadership and Governance

This module introduces the leadership responsibilities associated with AI adoption. You will explore the principles of responsible AI leadership, governance, accountability, and organisational decision-making. The module also examines how AI adoption can affect employees, customers, suppliers, and wider stakeholder groups.

You will learn how leaders can balance innovation with responsibility while building trust and confidence in AI initiatives.

Module 2: Embedding Governance, Ethics, and Regulation into AI Decision Making

This module focuses on the frameworks, policies, and governance structures that support responsible AI adoption. You will examine ethical principles, regulatory requirements, governance models, and organisational responsibilities that influence AI decision-making.

The module also explores how leaders can identify and assess AI opportunities using evidence rather than assumptions, ensuring decisions are aligned to organisational objectives and stakeholder expectations.

Module 3: Using Evidence, Risk, and Strategy to Decide How to Proceed with AI

This module develops the practical decision-making skills required to evaluate AI initiatives and determine whether they should progress. You will explore approaches to viability assessment, commissioning, testing, and evidence gathering, alongside methods for assessing business value and organisational readiness.

You will also examine the importance of stakeholder legitimacy, strategic alignment, and leadership sponsorship when deciding how and when to proceed with AI initiatives.

Module 4: Overseeing AI Systems

This module focuses on leadership oversight once AI solutions have been selected or implemented. You will learn how to evaluate technologies, suppliers, and technical approaches while ensuring solutions remain aligned with business requirements.

The module also explores assurance mechanisms, monitoring approaches, governance reviews, and crisis management processes that support effective oversight of AI-enabled systems throughout their lifecycle.

Module 5: Maintaining Good AI Governance

The final module examines how governance arrangements must evolve as AI adoption matures. You will explore approaches to monitoring governance effectiveness, responding to changing risks and regulations, and ensuring AI initiatives continue to operate responsibly over time.

The module emphasises continuous improvement, accountability, and the leadership behaviours required to sustain trust in organisational AI adoption.

Programme outcome

By the end of the programme, you will be able to make evidence-based decisions about AI adoption, procurement, and governance. You will have the confidence to evaluate AI solutions and suppliers, establish effective governance and assurance arrangements, manage risk and compliance requirements, and ensure appropriate human oversight throughout the AI lifecycle.

You will move from understanding AI strategy conceptually to governing AI adoption responsibly and effectively within your organisation.