Overview
A practical, non-technical course for leaders and decision-makers considering AI adoption. Attendees assess capabilities, tools, opportunities and governance, distinguishing current requirements from emerging developments. Through demonstrations, case discussions and a Design Thinking workshop, they develop a bounded pilot brief with safeguards, success measures and adoption actions.
What you’ll need
- Laptop with Google Chrome or Microsoft Edge
- headphones and microphone and a working webcam
- A word processor or access to the supplied editable pilot-planning template
- Organisation-approved AI account, such as Microsoft Copilot Chat (a paid Microsoft 365 Copilot licence is preferred, but not essential)
Learning outcomes
By the end of the course, attendees will be able to:
- Explain the differences between generative AI, AI assistants and agents, and identify limitations relevant to a business decision
- Assess a current or emerging AI capability, distinguishing demonstrated functionality from announced developments and speculation
- Compare AI tool or supplier options using task suitability, information protection, integration, cost and support criteria
- Prioritise candidate AI use cases using expected value, feasibility and risk, including when a non-AI solution is more appropriate
- Compare the EU and UK regulatory approaches, distinguish current legal obligations from proposals, and identify questions requiring specialist advice
- Specify practical safeguards for a proposed use case, including data handling, human review, accountability and escalation
- Produce a pilot brief stating the user problem, scope, owner, baseline, success measures and criteria for continuing, changing or stopping the pilot
- Outline adoption actions addressing staff involvement, skills, communication and ongoing review
Course topics
AI Capabilities, Limitations and Emerging Developments
- A shared vocabulary: machine learning, generative AI, models, assistants and agents
- Current workplace capabilities: drafting, research, analysis, knowledge retrieval and multi-step tasks
- Demonstrations of practical agent use, including examples from Coding Fury
- Limits that matter to leaders: unreliable answers, bias, data quality and the need to check evidence
- What is coming next: reviewing announced developments and emerging capabilities without treating forecasts as confirmed functionality
Choosing Tools and Prioritising Opportunities
- Comparing Microsoft Copilot, ChatGPT, Gemini, Claude and specialist tools for relevant organisational tasks
- Assessing security, data use, access controls, integration, supplier support and total cost rather than choosing on headline features alone
- Identifying tasks suited to an assistant, an agent, conventional automation or no AI intervention
- Prioritising use cases by value, feasibility, data readiness and risk; considering quality, time saved and implementation costs
Governance, Responsible Use and AI Law
- Privacy, confidentiality, intellectual property, fairness and security considerations, including unapproved AI use
- Comparing the EU AI Act’s risk-based framework with the UK’s regulatory approach and existing legal duties
- Implications for organisations operating across the UK and EU: intended use, organisational responsibilities, human oversight and relevant obligations
- UK plans for AI legislation: distinguishing enacted law, future commencement dates, proposed legislation, consultations and government commitments
- Practical governance: acceptable-use principles, named accountability, review and approval, incident escalation and supplier due diligence
- Case discussion: identify risks, proportionate safeguards and where legal, data-protection or security advice is needed
Design Thinking Workshop: From Problem to AI Pilot
- Understand users and the current workflow; define the problem before selecting technology
- Generate possible solutions, including non-AI alternatives, and select a bounded opportunity
- Sketch how a proposed solution would work and test its assumptions with peers
- Outline a pilot using an organisational challenge or supplied case study: scope, data, resources, owner and human review
- Set a baseline, measurable benefits, quality checks and criteria for continuing, changing or stopping the pilot
Leading Adoption and Next Steps
- Involving staff, addressing concerns and identifying the skills and support needed for adoption
- Assigning ownership for the pilot, information sources and ongoing performance review
- Peer-reviewing pilot briefs for value, feasibility, safeguards and realistic expectations
- Agreeing immediate next steps and the evidence needed before a wider rollout