Audience
Designed for department leaders in hospitals, clinics, and health systems, including heads of service, nursing leaders, operations managers, and programme directors.
You lead people and budgets, want to improve patient flow and safety, and need a clear, non-technical understanding of how AI can solve real problems, meet regulatory expectations, and deliver measurable value across your service lines.
Course Description
A concise, practical introduction to AI for healthcare leaders that demystifies concepts, identifies high-value use cases, and equips you to pilot, govern, and scale responsibly.
Benefits
• Faster pathway improvements: spot quick wins in scheduling, triage, capacity planning, and discharge to reduce bottlenecks and waiting lists.
• Productivity at the frontline: free clinical and administrative time by automating repetitive documentation, coding, and reporting tasks.
• Safer care by design: embed risk controls, human oversight, and audit trails to protect patients and staff while meeting governance requirements.
• Stronger business cases: translate clinical and operational pain points into outcomes, costs, and savings with clear success measures.
• Confident leadership: align clinicians, IT, data, and quality teams around a shared roadmap so pilots land smoothly and scale sustainably.
Learning Outcomes
By the end of this course you will be able to:
• Understand key AI concepts and limits, and explain them clearly to clinical and operational stakeholders.
• Identify three to five AI-ready workflows in your department and define outcome, cost, and safety metrics for each.
• Prioritise opportunities using a simple value-risk matrix and select one pilot with an achievable 90-day plan.
• Build trust and transparency with a one-page governance checklist covering data, bias, safety, and human oversight.
• Communicate impact through a concise benefits tracker that reports time saved, error reduction, and patient experience changes.
Estimated Duration: 45 minutes
Format: Self-paced learning with interactive reflections and practical frameworks.
Curriculum
- 4 Sections
- 12 Lessons
- 10 Weeks
- Module 1: Healthcare AI EssentialsEstablish a clear, non-technical foundation for AI in clinical and operational contexts. You will learn core concepts, where AI helps, and where human judgement remains essential.4
- 1.1What AI is (and is not) – Plain-language overview of machine learning, generative AI, and decision support, including strengths, limits, and common myths. .
- 1.2From data to decisions – How data quality, context, and clinical workflows shape results, with practical examples across care settings.
- 1.3Human + AI collaboration – Designing roles so clinicians and staff supervise, verify, and add judgement rather than replace it.
- 1.4Module 1 quiz0 Questions
- Module 2: Finding High-Value Use CasesLearn a practical method to scan your pathways, spot AI-ready work, and prioritise opportunities that will show quick impact with manageable risk.4
- 2.1Identifying AI-ready workflows – A step-by-step method to spot repetitive, rules-based, or prediction-friendly tasks in your service line.
- 2.2Value-risk opportunity matrix – Score opportunities on impact, effort, data readiness, and risk to select viable pilots.
- 2.3Quick exercise: pathway scan – Map one patient pathway and highlight three automation or decision-support moments.
- 2.4Module 2 quiz0 Questions
- Module 3: Safety, Ethics, and TrustBuild confidence and accountability by applying simple guardrails for privacy, bias, clinical safety, and transparent communication with patients and staff.4
- 3.1Responsible automation in healthcare – Core principles for fairness, privacy, security, and clinical safety with simple guardrails.
- 3.2Governance in practice – Build a one-page checklist covering data use, validation, bias monitoring, and escalation routes.
- 3.3Communicating transparency – Craft patient and staff-friendly explanations and set expectations for oversight and incident reporting.
- 3.4Module 3 quiz0 Questions
- Module 4: From Pilot to ImpactModule Overview – Translate ideas into a disciplined 90-day pilot, track measurable outcomes, and prepare the change plan needed to scale responsibly.4
- 4.1Designing a 90-day pilot – Define objectives, minimum viable data, stakeholders, and a clear test plan with go/no-go criteria.
- 4.2Measuring outcomes and ROI – Create a benefits tracker for time saved, error rates, throughput, and patient experience.
- 4.3Change management playbook – Engage clinicians, align IT and procurement, and plan training and handover for scale-up.
- 4.4Module 4 quiz0 Questions
