AI in healthcare: Is the NHS embracing the potential?

With increasing developments in technology, how are the NHS using AI, and are they making the most of it?

The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field and has vast potential. 

AI-driven tools can analyse large amounts of information, detecting patterns, and predicting outcomes. These tools have the potential to change and improve the way that healthcare is provided to people by improving quality and efficiency. 

The NHS AI Lab was set up to make the most of the potential of AI technologies, and despite COVID-19, the past year has brought new opportunities and challenges for the use of AI in health and care. A survey was conducted, 2020-21: A year in the life of the NHS AI Lab, to explore the development and use of AI. 

The survey was open to all and received over 368 responses in 2021, 197 of whom were developers of AI for health and care.

3 Key Findings 

1. Diagnostics is the most popular area for AI in health and care 

The deployment of AI-driven technologies is not yet evenly spread across the different areas of health and social care. The figure shows the responses from survey participants who were asked about the area of focus of their technology, they were allowed to select more than one area of focus. The survey clearly shows that most of the early adopters of AI technologies are in diagnostics. Similarly to 2019, the 2021 survey indicates the use of AI is dominant in the following 4 areas:

  • Diagnostics - 57%
  • Remote monitoring - 34%
  • Triage - 32%
  • Population health - 25%

2. AI products have some way to go before large scale use

Although the levels of readiness for the deployment of AI technologies in health and care have significantly increased from 2019 to 2021, it is still in the early stages. Around half of AI developers surveyed in the UK believe their product will be ready for deployment at scale in one year; up 24 percentage points from the last survey.

  • Ready in 1 year: 54% developers
  • Ready in 3 years: 79% developers
  • Ready in 5 years: 87% developers

3. The COVID-19 pandemic has influenced progress

The pandemic has had a mixed effect on the development and adoption of AI technologies into health and care settings.

A third of AI developers in the survey indicated a negative impact, giving examples of problems with re-deployment of clinical staff, reduced data collection, and lack of engagement for non-COVID-19 activity. However, a similar number indicated positive impacts where healthcare pressures had resulted in a rapid uptake of AI tools and increased acceptability for digital technologies being used to deliver care.

What’s next for the NHS AI Lab?

The UK has the second-highest number of AI-driven healthcare technologies in development globally after the US, according to NIHR Innovation Observatory’s Mapping the Global Activity of AI Health Technologies, 2021. The aim of the NHS AI Lab is to continue creating an environment that enables both developers and adopters of AI technologies to thrive, and to bring the benefits of AI quickly and safely to the people who need it most.

Here is a selection of things NHS AI Lab is doing in 2021:

  • Continuing to support the pandemic response through increasing use of the National COVID-19 Chest Imaging Database 
  • Work with a steady supplier of early stage AI technologies to get them tested and trialled within one to two years 
  • Educated and share knowledge with others who are developing and using AI in health and care so that progress is faster, quialty is imporved and costs reduced 
  • Help the most promising technologies get approved, commissioned and into widespread use in the NHS

Featured Articles

AI in SOC: Where Should Security Teams Look to Apply It?

As threats evolve, AI's continuous learning ensures robust protection that can prove invaluable for security operations centres

Swiss Re: Pharma, Not IT, to See Most Adverse Effects of AI

Swiss Re' AI report revealed surprising results showing pharmaceuticals stands to be the most adversely effected industry from the applications of AI

AI Safety Summit Seoul: Did it Meet Industry Expectations?

Before the summit, there were high hopes for meaningful outcomes - we see if industry leaders like EY's Beatriz Sanz Saiz thinks so

IBM's Salesforce Partnering Shows watsonx's Enterprise Reach

AI Strategy

Are Business and Government Diverging on AI Safety?

AI Strategy

Alteryx Industry-First AI Copilot Sees New Era of Analytics

AI Applications