AI knowledge repository A - Z of resources

Search A-Z

A buyer's guide to artificial intelligence in health and care

1 April 2020: The Buyer’s Guide to AI in Health and Care sets out the important questions you need to consider in order to undertake robust procurement exercises and make well-informed buying decisions about AI products

A Framework for the safe, efficient and effective implementation, use and maintenance of AI in health and care in London

An overview of the agreed way of implementing and monitoring Artificial Intelligence (AI) products in the London health and care system.

A Horizon Scan of Algorithms Used in the Development of Artificial Intelligence (AI)-Enabled Healthcare Technologies

This report provides a comprehensive review of algorithms used within AI-based healthcare technologies. We have explored the use of specific algorithms used within these technologies, and provide insights regarding their use in the diagnoses, treatment, and management of specific health conditions.

AI Airlock webinar

Webinar from 19 June 2025, including an introduction to the AI Airlock programme and brief evaluation of phase 1 presented by the Medicines and Healthcare products Regulatory Agency (MHRA).

AI Barometer 2020

The CDEI has published its AI Barometer, a major analysis of the most pressing opportunities, risks, and governance challenges associated with AI and data use in the UK, initially across five sectors. Published 2020.

AI Companions for Health and Mental Wellbeing: Opportunities, Risks and Policy Implications

The risks and benefits of Social AI for health and healthcare, as well as mental health and wellbeing are highlighted in the report, followed by a summary of policy recommendations put forward by the experts.

AI deployment fundamentals for medical imaging

RCR's minimum standards for providers to deploy artificial intelligence (AI) solutions in radiology.

AI deployment fundamentals for medical imaging

2024: The AI deployment fundamentals for medical imaging guidance was developed by an expert panel who identified minimum standards for providers to deploy artificial intelligence (AI) solutions in radiology and focuses on the period between the algorithm achieving regulatory approval and its business-as-usual deployment.

AI Digital Regulations Service

Learn what regulations to follow and how to evaluate effectiveness, whether you're a 'developer' of AI and digital technology or an 'adopter' who will buy or use them in health and social care.

AI Digital Regulations Service: Guidance for Adopters

Understand what regulations and best practice principles to follow when adopting your digital health technology.

AI guides by University Hospitals Plymouth NHS Trust

These guides are part of a developing series produced by University Hospitals Plymouth NHS Trust which introduce the fundamental concepts of AI considerations when planning to utilise technologies.

AI in health care: what do the public and NHS staff think?

To help understand public and and staff attitudes towards the use of AI in health care, the Health Foundation commissioned a survey, conducted in June and July 2024, of 7,201 nationally representative members of the public (aged 16 years and older) and 1,292 NHS staff members.

AI in London healthcare: The reality behind the hype

The report examines how AI is currently being used, identifies key challenges, and outlines the collaborative approach needed for responsible and scalable AI adoption across the NHS.

AI Insights series

A series of articles which is intended to complement the AI Playbook which explains technical concepts with practical guidance designed specifically with the public sector in mind. New content in the series is scheduled to be published every 2 months. Originally published 10 February 2025.

AI Opportunities Action Plan

Department for Science, Innovation and Technology commissioned an independent AI Opportunities Action Plan which set out recommendations for Government and AI adoption across the economy to boost growth whilst improving products and services. The Plan set out 50 policy recommendations across three broad headings of: Laying the Foundations to Enable AI, Changing Lives by Embracing AI and Securing our Future with Homegrown AI and Securing our Future with Homegrown AI.

AI Playbook for the UK Government

The playbook offers guidance on using AI safely, effectively and securely for civil servants and people working in government organisations

An Investigation into the Development of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) - Enabled Healthcare Technologies

This report provides a comprehensive overview of the current state of AI-based healthcare technologies in development, those that have recently gained approval for use in the healthcare industry. It also provides insights into the key factors driving the development of these AI-based healthcare technologies.

Artificial intelligence (AI) and machine learning

Published in 2023 and updated in April 2025 this guidance includes examples from the NHS AI awards winners and tips for implementation including planning AI in general practice.

Artificial Intelligence (AI) in Pharmacy

Royal Pharmaceutical Society policy to outline the opportunities, challenges and potential applications of artificial intelligence (AI) within pharmacy now and in the future.

A dedicated guidance resource for social care providers using AI and digital technologies in including adult social care

Artificial intelligence and innovative technologies

A General Medical Council (GMC) resource which answers questions on the use of innovative technologies in healthcare and how GMC professional standards should apply when using them. Published 6 January 2026.

Artificial Intelligence Education and Skills within NHS Wales Landscape review

An evaluation of the current state of Artificial Intelligence (AI) education in AI skills and literacy across the healthcare workforce. Published 6 January 2026.

Auto-contouring in radiotherapy

RCR guidance developed to aid all healthcare professionals involved in the use of auto-contouring systems for radiotherapy treatment and explains the different stages of selection, implementation and ongoing monitoring of an auto-contouring system to support the safe clinical use of this new technology.

Blueprinting FutureNHS Workspace

The Blueprinting programme was established to help NHS organisations deliver quicker and more cost-effective digitisation. You will need a FutureNHS account to login.

Council of Deans of Health (UK) – Principles for the Use of Generative AI in Healthcare Education (Feb 2026)

A report outlining eight high level principles for integrating AI into healthcare education, recognising its potential to enhance teaching, learning, and student support.

Data and AI Ethics Framework

Guidance for public sector organisations on how to use data and data-driven technologies responsibly. Published 18 December 2025.

Data Lens: a fast-access data search in multiple languages

25 March 2021: A pilot project for the NHS AI Lab Skunkworks team, Data Lens brings together information about multiple databases, providing a fast-access search in multiple languages.

Developing healthcare workers’ confidence in artificial intelligence (AI)

1 April 2023. This report explores how confidence in artificial intelligence (AI) among healthcare workers can be developed through education and training. This report follows on from a previous report which outlined a conceptual framework for understanding what influences confidence in AI.

Digital Technology Assessment Criteria (DTAC)

NHS England has completed a provisional review of DTAC to consider how the efficiency and efficacy can be improved, hearing evidence and recommendations with industry and NHS providers

Evidence standards framework (ESF) for digital health technologies

As digital health technologies (DHTs) develop at an increasing pace, we've worked with stakeholders, system partners and thought leaders to develop standards that ensure new DHTs are clinically effective and offer value to the health and care system: the evidence standards framework (ESF).

Good Machine Learning Practice for Medical Device Development: Guiding Principles

27 October 2021: Ten guiding principles that can inform the development of Good Machine Learning Practice (GMLP).

GP mythbuster 109: Use of artificial intelligence (AI) in GP services

14 July 2025. Using artificial intelligence (AI) in general practice has potential benefits for delivering care, but its use must align with regulatory requirements and good clinical governance to ensure safe and compliant implementation in healthcare delivery.

Guidance and case studies for teams adopting AI technologies in the public sector (Ai.Gov.uk knowledge hub)

Guidance and case studies for teams adopting AI technologies in the public sector.

Guidance for Anonymisation

28/3/2025 Updated guidance for all organisations that want to anonymise personal data and identify the issues which should be considered to effectively use anoymisation techniques.

Guidance on the Impact Evaluation of AI Interventions

Guidance on the impact evaluation of AI interventions, complementing HMT's Magenta Book (guidance on evaluation more broadly).

Guidance on the use of AI-enabled ambient scribing products in health and care setting

This guidance outlines key considerations for NHS technology leaders implementing ambient scribing products across health and care settings in England. Ambient scribing products, when combined with generative Artificial Intelligence (AI), can convert speech directly into structured medical documentation, such as notes and letters. The products are sometimes referred to as ambient scribes or AI scribes and include advanced ambient voice technologies (AVTs) used for clinical or patient documentation and workflow support.

Guidelines for AI procurement

A summary of best practice addressing specific challenges of acquiring Artificial Intelligence technologies in government.

Health and Care Professions Council (HCPC) – Joint Statement on AI in Health and Care Education (2026)

A joint statement from a collaboration of five regulators, including the HCPC on principles relating to the use of Artificial Intelligence (AI) in education and training. This is intended to sit alongside HCPC's Artificial intelligence (AI) in education guidance (April 2024)

How are GPs using AI? Insights from the front line

Using a mixed-methods approach, the research combined findings from our annual GP Voice Survey with a series of online focus groups to explore how GPs across the UK are using AI in clinical practice.

How would clinicians use time freed up by technology?

Explores how time freed up by technology is used in practice and clinician perspectives on how such time could be used in the NHS.

Introduction to AI Assurance

An introductory guide for practitioners interested in finding out how assurance techniques can support the development of responsible AI.

Making AI in healthcare work for women: New reports

Two recently published reports reveal that while AI has the potential to revolutionise health care, current technologies may be worsening rather than solving existing health inequalities for women. Published in 2025.

How AI is enhancing the quality of care, workforce support, patient safety, person centred care, productivity, education and training to date. This work is based on conversations with a broad range of people from specialists, GPs and dentists to researchers and innovators. Published 16 May 2025.

Navigating AI – practical questions for NHS leaders to ask

14 August 2025. As Artificial intelligence (AI) becomes increasingly embedded into clinical pathways and new models of care, NHS leaders play a critical role in ensuring safe and ethical implementation that drives benefits for patients and staff. Download our new toolkit, designed to support your conversations at each stage of the journey from considering using AI through to implementing solutions into business-as-usual workflows.

NHS Digital Academy resources

In 2023, the NHS Digital Academy published an Artificial Intelligence (AI) capability framework to help healthcare workers identify gaps in their current knowledge.

NHS England Ambient Voice Technology (AVT) Supplier Registry

A national self-certified registry of AVT suppliers to support and accelerate local procurement and assurance activities to support for NHS organisations in adoption and scaling. This includes a list of self-certified suppliers, and a resource library. Published January 2026.

NHSX AI Dictionary

A simple dictionary of common AI terms with a health and care context, with basic search and navigation.

Practical Lessons from Generating Synthetic Healthcare Data with Bayesian Networks

We explore the integration of resampling, probabilistic graphical modelling, latent variable identification, and outlier analysis for producing realistic synthetic data based on UK primary care patient data.

Principles for Artificial Intelligence (AI) and its application in healthcare

Discusses how AI is being used in healthcare delivery and an examination of potential benefits and drawbacks with respect to patients, clinicians, and the efficiency of the overall healthcare system. Published July 2024.

Priorities for an AI in health care strategy

Six key priorities policymakers and health care leaders must address through such a strategy if the benefits of AI are to be realised.

Putting the United Kingdom at the forefront of using artificial intelligence for the benefit of health and care: a mixed methods formative evaluation of the NHS Artificial Intelligence Lab

This document reports on the background, methods, findings, discussion and conclusions of the independent evaluation of the NHS AI Lab

Regulations and guidance for developers

Understand what regulations and best practice principles to follow when developing your digital health technology.

Scaling innovations in public health systems: guidance and toolkit

The World Health Organization guidance and toolkit for scaling innovations in public health systems offer an evidence-based, practical framework to assist governments to lead, coordinate and sustain the scaling of health innovations

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups. We hope that adoption of the STANDING Together recommendations by stakeholders across the AI health technology lifecycle will enable everyone in society to benefit from technologies which are safe and effective.

Tech to save time: how the NHS can realise the benefits

Drawing on the Health Foundation’s own research and a rapid evidence review by The Evidence Centre, this analysis explores situations where health technologies have had no or negative impact on staff time and investigates why.

The Future State of Health and Healthcare in 2035

A vision for seven technologies reshaping the NHS

The known lessons for approaching AI

6 March 2025: This report explores five key lessons for NHS leaders, drawing on learnings from past technology implementations to ensure AI delivers real value for patients and staff. By learning from previous implementations, trust leaders can avoid common pitfalls and make smarter decisions about AI adoption.

The role of artificial intelligence in healthcare: a structured literature review

This paper presents the findings from a literature review of 288 academic articles on AI in healthcare published 1 April 2021.

The Topol Review: Preparing the healthcare workforce to deliver the digital future

The Topol Review explores how to prepare the healthcare workforce, through education and training, to deliver the digital future. It makes recommendations that will enable NHS staff to make the most of innovative technologies such as genomics, digital medicine, artificial intelligence and robotics to improve services.