Artificial Intelligence Technologies is sponsored by Engineering and Physical Sciences Research Council (EPSRC). Supports fundamental advances in AI technologies across various applications.

Artificial intelligence technologies – UKRI Area of investment and support Area of investment and support: Artificial intelligence technologies This research area focuses on the reproduction or surpassing of abilities (in computational systems) that would require intelligence if humans were to perform them.

Engineering and Physical Sciences Research Council (EPSRC) The scope and what we're doing ​​Artificial Intelligence (AI) technologies aim to reproduce or surpass abilities (in computational systems) that would require intelligence if humans were to perform them.

These include: sensory understanding and interaction The applications of AI systems, including but not limited to machine learning, are diverse, ranging from understanding healthcare data to autonomous and adaptive robotic systems, to smart supply chains, video game design and content creation.

This research area primarily covers fundamental advances in AI technologies, while applications of such technologies are captured within other subject domains. We aim to maximise opportunities arising from the current increased global interest in AI and its widespread applications, as well as the government’s Industrial Strategy, namely via the National Productivity Investment Fund (NPIF).

This strategy recognises that AI and the data economy was named as one of four Grand Challenges in the Industrial Strategy, as well as AI research’s importance to data science in general and robotics and autonomous systems (RAS) specifically. It aims to show where activity can be focused to allow the UK to grow in international expertise in both fundamental theory and more applied research.

We aim to have a community which actively engages in: the challenges of responsible research and innovation public acceptability of AI ensuring that research outcomes are socially beneficial, ethical, trusted and deployable in real world situations.

We expect a supply of people with skills across the breadth of AI technologies, reflecting growing demand, and who can contribute expertise across a wide range of domains (for example, the future of healthcare delivery).

A combination of new methodology and applications Researchers will aim to combine development of new methodology and applications – for example, by working alongside research enablers such as research engineers, translational researchers and industry collaborators with application expertise.

The portfolio aims to contain AI-enabled robotics and autonomous systems technologies co-created with other disciplines, such as: human-computer interaction This should take into account how these intelligent systems interact and collaborate with humans, and consider their validation and verification, especially in application areas where the dependability, safety or security of implementations is a concern.

AI researchers will play a key role in furthering EPSRC’s future intelligent technologies and data enabling decision making cross-ICT priorities and are well placed to contribute to the other cross-ICT priorities. In order to maximise the impact of these contributions, they should ensure effective communication with researchers in other contributing areas such as natural language processing, visualisation and human-computer interaction.

We recognise the need for researchers to work with large-scale data and we encourage them to develop collaborations with users to facilitate this. We also encourage them to explore alternative routes to access sufficient computational resources – for example, use of commercial clouds.

However, UK academia should not try to imitate industry, and should focus on AI opportunities not yet identified by industry or not yet commercially viable, particularly those leading to beneficial societal impacts. AI is likely to become an increasingly dominant feature of our world and understanding the future of AI and its impact on future society are critically important research areas.

Explainability of AI decisions is key, as is the use of AI to simplify data in order to facilitate human understanding and decision making. The recent growth in this research area, namely on the data intensive sub-symbolic side of the AI technologies portfolio has implications for information and communications technologies (ICT) hardware related research areas.

We recognise that research in ICT hardware should keep up with the advances made in AI technologies and that better links between these communities need to be encouraged.

The importance of a​rtificial intelligence (AI) to UK industry was recognised in the UK’s Industrial Strategy White Paper: Building a Britain fit for the future which identified AI and the data economy as one of the four Grand Challenges for current and future UK industrial leadership.

The strength of this sector in the UK was also acknowledged in the government commissioned report Growing the AI Industry in the UK which stated that the UK has AI companies that are seen as some of the world’s most innovative, in an ecosystem that includes large corporate users of AI, providers large and small, business customers for AI services, and research experts.

This report made a number of key recommendations for actions and interventions required to sustain and develop the UK’s AI sector, which were responded to in the 2018 AI Sector Deal . A key recommendation of the report Growing the AI Industry in the UK was the need for a major step change in UK development of high-level skills for AI.

Among other things, the review recommended 200 more PhD places per year in AI at leading UK universities, attracting candidates from diverse backgrounds and from around the world. The recent UKRI investment in AI studentships through centres for doctoral training will start to tackle this recommendation. The UK is a strong international contributor in this area, evidenced by the existence of world-leading UK research groups.

In 2017 we invested £42 million in the Alan Turing Institute as part of a joint data science venture with five university partners. In 2018 the ATI evolved its role to national institute for data science and AI, and eight further universities are joining as partners.

AI and robotics and autonomous systems (RAS) technologies have an increasing impact on UK policy and the economy, improving business competitiveness, providing effective solutions to societal problems and empowering people to live more fulfilled lives and make more informed choices. A wide range of influential commentators have spoken of the societal risks and opportunities associated with AI research.

Research investment is needed not only on development of tools and techniques but also on understanding risks and maximising opportunities. The importance of – and UK international competitiveness in – machine learning (ML) is evidenced by the significant industrial investment being made in UK ML, including Google’s acquisition of DeepMind in 2014.

ML has become an enabler of many technologies (including but not restricted to language technologies) and is expected to play an increasingly important role in data analytics. Many UK universities are actively investing in data science and ML and are attracting international experts. Nevertheless, we need to ensure the UK has the trained people to cater for the serious upward trend in demand for ML skills .

Recruitment at PhD level is healthy (with keen demand from students and employers), but recruitment and retention in academia beyond this is a problem. There is the threat of key capacity being lost to industry, with universities unable to compete (for example in terms of salary, provision of computational resources and access to large scale data).

The UK is in a particularly strong position internationally to develop AI technologies in healthcare. This is partly due to having NHS data stakeholders interacting with universities and partly because the UK has one of the world’s best-established AI communities, able to offer diversity of research. This makes AI an area of national importance for the future of healthcare delivery.

View evidence sources used to inform our research strategies . Past projects, outcomes and impact Visualising our portfolio (VoP) is a tool for users to visually interact with the EPSRC portfolio and data relationships. Find out more about research area connections and funding for artificial intelligence technologies .

Find previously funded projects on EPSRC’s funding application outcomes Tableau . Last updated: 24 February 2026 This is the website for UKRI: our seven research councils, Research England and Innovate UK. Let us know if you have feedback or would like to help improve our online products and services .