Understanding AI

Course Introduction

Artificial Intelligence is reshaping how insurance and financial services organisations operate, compete and serve their customers. Beyond individual productivity, AI raises strategic questions about where it creates value, how it should be governed, and how to use it responsibly and ethically in a regulated, customer facing sector.

This course gives professionals and decision makers a clear, non technical understanding of how AI is being applied across the sector, how to think strategically about adoption, and what good governance and ethical use look like. It covers the emerging regulatory and standards landscape, including the EU AI Act, ISO 42001 and the UK’s principles based approach through regulators such as the FCA, alongside the practical frameworks organisations are using to manage AI risk.

The emphasis is on understanding and application rather than technical detail, using real world examples, discussion and case studies relevant to insurance and financial services. No technical background is required.

Who should attend?

This course is suitable for managers, leaders and professionals who need to understand the strategic, governance and ethical implications of AI rather than only its day to day use. This may include:

• Team leaders and managers
• Compliance, risk and governance professionals
• Operations and change leaders
• HR and learning and development leaders
• Project and transformation teams
• Those contributing to AI policy, adoption or oversight

Course objectives

By the end of this course, participants will be able to:

• Understand the main types of AI and how they are being applied across insurance and financial services
• Identify where AI can create genuine value, and the risks of poorly considered adoption
• Think strategically about AI adoption, including build versus buy, use cases and organisational readiness
• Understand the emerging regulatory and standards landscape, including the EU AI Act, ISO 42001 and FCA and wider regulatory expectations
• Understand the core components of AI governance, including accountability, risk management, transparency and human oversight
• Recognise the key ethical considerations, including bias, fairness, explainability and customer outcomes
• Apply practical approaches to using AI responsibly within a regulated environment

Course content

• Module 1: The AI Landscape and How It Is Applied

• • The main types of AI in plain language, including generative AI, machine learning and automation
  • How AI is being applied across insurance and financial services, from underwriting and pricing to claims, service and operations
  • Separating genuine opportunity from hype

• Module 2: AI Strategy and Adoption

• • Identifying and prioritising valuable use cases
  • Build versus buy, data readiness and organisational capability
  • Common barriers to successful adoption and how to manage them
  • Measuring value and managing expectations

• Module 3: AI Governance and the Regulatory Landscape

• • Why AI governance matters, and what good governance looks like
  • The emerging landscape: the EU AI Act, ISO 42001, the NIST AI Risk Management Framework, and FCA and wider regulatory expectations
  • Core components: accountability, risk management, transparency, documentation and human oversight
  • Managing third party and vendor AI risk

• Module 4: Ethics and Responsible AI

• • Key ethical considerations: bias, fairness, explainability and privacy
  • Protecting customer outcomes and meeting expectations such as Consumer Duty
  • Maintaining human judgement and accountability
  • Building a responsible AI culture, with practical application and action planning