AI in Health and Social Care Training Course

This AI in Health and Social Care eLearning Course is designed for workers who need a clear, practical understanding of artificial intelligence and how it is being used in care environments. AI is increasingly influencing documentation, risk identification, administration, monitoring and decision support, so staff need to understand both its potential and its limits.

This free course explains key AI terms, common uses in NHS and adult social care settings, the benefits and risks of AI-supported practice, and the importance of data protection, confidentiality, ethics, professional standards and human oversight.

Why Take This eLearning Course?

AI can support safer, more efficient and more informed care when it is used responsibly. This course helps learners understand how AI tools can assist practice while keeping accountability, professional judgement and person-centred care at the heart of decision-making.

This course will help you to:

• Understand the difference between AI, machine learning and automation
• Recognise how AI is already being used across health and social care
• Identify how AI can support efficiency, accuracy and workload management
• Appreciate the benefits AI may offer to people who use services, carers and professionals
• Recognise risks linked to bias, privacy, data quality and over-reliance
• Understand why human oversight remains essential in care decisions
• Apply key data protection and confidentiality principles to AI use
• Consider ethical issues such as fairness, consent, accountability and transparency
• Build confidence in working alongside AI-supported systems
• Understand why ongoing learning is important as technology develops

Learning Outcomes

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

• Define artificial intelligence, machine learning, automation, training data and AI outputs
• Explain how AI differs from traditional rule-based digital systems
• Describe common AI uses in the NHS and adult social care
• Explain how AI can support decision-making without replacing professional judgement
• Identify practical benefits of AI for service users, carers, staff and organisations
• Recognise key risks, limitations and myths associated with AI
• Describe how personal data and sensitive health data must be protected
• Explain relevant UK data protection principles and confidentiality expectations
• Identify ethical and accountability issues linked to AI-supported care
• Describe the skills, responsibilities and training needed to work safely with AI

AI in Health and Social Care eLearning Course Outline

Module 1: Understanding Artificial Intelligence
Learners will explore the meaning of artificial intelligence, machine learning and automation, including how these terms relate to health and social care practice. This module explains how AI-based systems differ from traditional digital systems, why AI is increasingly being used across services, and why common myths about accuracy, neutrality and replacing human workers need to be challenged.

Module 2: How AI Is Used in Health and Social Care
Learners will examine common areas where AI is used, including clinical imaging, screening, risk prediction, administration, care planning support, population health and service planning. The module also considers examples from NHS pathways and adult social care settings, such as record summarisation, triage support, falls detection, care record prompts, rota planning and assistive technology, with emphasis on AI as a support tool rather than a replacement for staff.

Module 3: Benefits for Practice and Service Delivery
Learners will consider how AI can improve efficiency and accuracy by helping with sorting, searching, drafting, prioritisation and pattern recognition. This module explains how AI can support decision-making through risk scores, alerts and summaries, while reinforcing that staff must consider context, lived experience, safeguarding information, communication needs and the person’s wishes before taking action.

Module 4: Risks, Limitations and Human Oversight
Learners will explore the potential risks of AI in care, including bias, inequality, privacy concerns, inaccurate outputs and unsafe reliance on technology. The module covers limitations linked to data quality, lack of context, model performance, false alerts and opacity, and explains why staff must check outputs, challenge unexpected results, record decisions and maintain professional vigilance.

Module 5: Data Protection, Confidentiality and Security
Learners will build their understanding of personal data, sensitive health data and the way AI systems use data to function. This module covers data collection, preparation, model training, testing, live use and monitoring, alongside key UK GDPR and Data Protection Act 2018 principles such as lawfulness, fairness, transparency, purpose limitation, data minimisation, accuracy, storage limitation, integrity and confidentiality.

Module 6: Ethics, Accountability and Professional Standards
Learners will examine ethical practice in health and social care, including autonomy, beneficence, non-maleficence, justice, dignity, honesty and accountability. The module considers ethical concerns linked to AI, such as bias, unequal impact, reduced transparency, consent, choice and privacy intrusion, as well as organisational and professional accountability when AI influences care decisions.

Module 7: Working Alongside AI
Learners will consider how AI may change job roles by increasing the need for reviewing outputs, monitoring dashboards, supporting data quality and explaining AI-supported processes. This module also covers the skills needed to work safely alongside AI, including digital literacy, critical appraisal, data awareness, communication, escalation, reporting and ethical awareness, as well as the importance of training and digital confidence.

Module 8: Future Developments and Ongoing Learning
Learners will explore emerging trends in AI, including generative AI for documentation, remote monitoring analytics, multimodal models, operational optimisation and explainable AI approaches. The module also considers potential future uses in social care, implementation challenges linked to data, workforce readiness and public trust, and the need for ongoing learning as tools, evidence, policies and risks continue to evolve.

Target Audience

This course is suitable for:

• Health and social care workers who use digital systems in day-to-day practice
• NHS staff who need an introduction to AI-supported tools and workflows
• Adult social care staff, care coordinators and support workers
• Registered professionals who want to understand safe AI use and accountability
• Managers, supervisors and team leaders supporting digital change
• Staff involved in care records, monitoring, administration or service coordination

No previous specialist knowledge is required.

FAQ

Who is this course suitable for?

This course is suitable for health and social care staff who want to understand how AI is used in care settings, what benefits it may offer, and what risks must be managed. It is relevant to frontline staff, registered professionals, supervisors, managers and administrative teams.

Do I need any previous experience?

No previous experience of artificial intelligence is needed. The course starts with key definitions and builds towards practical issues such as decision support, data protection, ethics, accountability and safe use in the workplace.

What will I learn on this AI in Health and Social Care course?

You will learn what AI, machine learning and automation mean, how AI differs from traditional digital systems, where AI is used in the NHS and adult social care, and how staff can use AI-supported outputs responsibly.

Will this course help with day-to-day practice?

Yes. The course focuses on practical understanding, including how to check AI-generated summaries, interpret alerts, avoid over-reliance, protect confidentiality, record decisions and raise concerns when outputs appear inaccurate or unsafe.

Does the course cover practical skills?

Yes. It covers practical skills such as questioning AI outputs, recognising data quality issues, understanding when human judgement is needed, following local policy, protecting confidential information and escalating concerns through appropriate routes.

Does it cover relevant responsibilities or good practice?

Yes. The course covers responsibilities linked to UK data protection principles, confidentiality, professional accountability, ethical practice, governance, human oversight and safe use of approved AI systems in health and social care.

How long does the course take?

The course is self-paced and usually takes around 1 hour to complete.

Will I receive a certificate?

Yes. A certificate is issued after successful completion.

AI is becoming part of modern health and social care, but safe use depends on informed staff, strong governance and clear professional judgement. This course gives learners a practical foundation for understanding AI, recognising its risks and benefits, and using technology in a way that supports responsible, person-centred practice.

Enrol now to build your understanding of AI in health and social care.