Programme-Level AI Literacy Strategy
Original work: "Educators' guide to multimodal learning and Generative AI" — Tünde Varga-Atkins, Samuel Saunders, et al. (2024/25) — CC BY-NC 4.0
Adapted for UK Nursing Education by: Lincoln Gombedza, RN (LD)
Last Updated: December 2025
A coherent programme-wide strategy ensures AI literacy develops progressively across the nursing curriculum, aligning with NMC proficiencies and preparing graduates for AI-enhanced practice.
🌟 Strategic Framework
Vision Statement
"To develop nursing graduates who are AI-literate, critically engaged, and ethically grounded professionals capable of integrating AI responsibly into person-centred care while maintaining professional accountability and clinical excellence."
Strategic Objectives
- Competency Development: Ensure all graduates achieve core AI literacy competencies
- Progressive Integration: Build AI literacy systematically across three years
- NMC Alignment: Map AI competencies to NMC proficiencies
- Quality Assurance: Maintain high standards in AI-enhanced education
- Ethical Practice: Embed responsible AI use throughout curriculum
🗺️ Progressive Curriculum Mapping
We use a scaffolded approach: Foundation (Year 1) → Reference (Year 2) → Mastery (Year 3).
- Year 1: Foundation
- Year 2: Application
- Year 3: Mastery
🟢 Focus: Understanding & Awareness
Core Competencies
- Basic AI concepts and terminology ("What is an LLM?")
- Safe and ethical AI tool use (Privacy first!)
- Critical evaluation of AI outputs (Hallucination checking)
Module Integration Points
- Foundations of Nursing: Introduction to AI in healthcare contexts.
- Academic Skills: Using AI for brainstorming (but not writing) essays.
- Evidence-Based Practice: Distinguishing between AI summaries and primary research.
Key Assessment
- "My First Prompt": A reflective exercise on creating and critiquing a simple patient scenario.
🟡 Focus: Integration & Practice
Core Competencies
- AI-enhanced clinical reasoning (Decision support)
- Evidence-based AI verification (Checking against NICE)
- Patient-centred AI application (Communication skills)
Module Integration Points
- Care Planning: Generating and critiquing complex care plans.
- Pharmacology: Using AI to summarize drug interactions (then verifying in BNF).
- Health Promotion: Creating accessible leaflets for diverse groups.
Key Assessment
- The "Red Pen" Exercise: Students are given a flawed AI-generated care plan and must identify all clinical errors and ethical risks.
🔴 Focus: Leadership & Innovation
Core Competencies
- Advanced AI integration (Workflow optimization)
- Quality improvement with AI Data analysis
- Policy contribution & Advocacy (Leading the change)
Module Integration Points
- Leadership: Managing teams using digital tools.
- Quality Improvement: Analysing audit data patterns.
- Transition to Practice: Understanding the AI tools used in local NHS Trusts.
Key Assessment
- Innovation Project: Design a quality improvement initiative that safely leverages AI to improve patient outcomes.
📋 NMC Proficiency Mapping
How does this align with the Future Nurse Standards (2018)? Click to explore the mapping for each platform.
Platform 1: Being an Accountable Professional
- AI Integration: Understand professional accountability. If AI gives wrong advice, you are accountable, not the algorithm.
- Evidence: Reflective accounts of AI usage demonstrating full disclosure and checking against the Code.
Platform 2: Promoting Health and Preventing Ill Health
- AI Integration: Use AI to draft health promotion materials (e.g., "Summarise this diabetes advice for an 8-Year old").
- Evidence: Verified, clinically accurate patient information leaflets created with AI assistance.
Platform 3: Assessing Needs and Planning Care
- AI Integration: AI-assisted holistic assessment prompts. Critically evaluating AI care plan suggestions for person-centredness.
- Evidence: Care plans that explicitly note where AI was used for brainstorming and where human judgement applied corrections.
Platform 4: Providing and Evaluating Care
- AI Integration: Using AI for decision support (e.g., "List potential differential diagnoses for these symptoms") but evaluating clinically.
- Evidence: Clinical portfolios showing safe use of decision support tools.
Platform 5: Leading and Managing Nursing Care
- AI Integration: Leadership in digital transformation. Teaching junior staff how to use tools safely.
- Evidence: Teaching plan for a "Digital Safety" huddle.
Platform 6: Improving Safety and Quality of Care
- AI Integration: Identifying how AI can reduce error (e.g., double-checking calculations) vs. where it introduces error (hallucination).
- Evidence: Safety incident analysis involving digital tools.
Platform 7: Coordinating Care
- AI Integration: Using tools to summarise complex discharge notes for interdisciplinary teams (while maintaining privacy).
- Evidence: Simulated discharge letters edited for clarity and accuracy.
🚀 Implementation Roadmap
A sample timeline for rolling out this strategy in Year 1:
🤝 Stakeholder Engagement
To succeed, you need everyone on board:
| Stakeholder | Key Message | Support Required |
|---|---|---|
| Students | "AI helps you think, it doesn't think for you." | Clear workspaces, paid tool access (ideally), safety nets. |
| Staff | "You don't need to be a tech wizard, just a safe practitioner." | Time allowance for training, "Sandpits" for experimentation. |
| Practice Partners | "We are training nurses for the digital future of the NHS." | Alignment on what tools are permitted in clinical areas. |
Next: Explore Institutional Framework for university-wide strategy.