UK National AI Strategy - An ambitious plan

12 November 2021

A record-breaking £13.5 billion was invested in the British tech sector during the first half of 2021 alone, an exceptional start to a year by any standards! This cemented the UK as one of the world leaders in technology-oriented investment. This 2021 figure is more than those of Germany, France, and Israel combined. Over 1,400 UK-based companies will benefit from the raised sum, including start-ups with “unicorn” status (a privately held company with an overall value above $1 billion).

It is anticipated that Artificial Intelligence (AI) and Machine Learning will form the foundation of much of the Tech sector’s future. Indeed, incorporating AI in Tech is already happening in most industry sectors (particularly Fintech), including our very own R&D Tax Relief Benchmarking Toolkit. The recent announcement that 32 AI tech companies have been accepted into Applied AI 3.0 (Tech Nation’s growth programme for AI) supports this development.

The government has committed £800m to support UK innovation through the Advanced Research and Invention Agency (ARIA).The government’s recent 56-page National AI Strategy publication along with the Chancellor’s announcement of new funding to double the number of AI scholarships and Turing research fellows signals a renewed focus on R&D in AI.

Background to the Strategy

The National AI Strategy is underpinned by the reasonable assumption that AI will soon hold a strong sway over the economy, and that access to people, data, compute and finance are crucial to its development.

The UK has a long tradition in the field - from Alan Turing to DeepMind. The Strategy constitutes an important addendum to pre-existing and upcoming plans, including the Innovation Strategy, the National Data Strategy, the Digital Strategy, and the plans for a new Defence AI centre. AI has considerable infrastructural demands (e.g. the need for large datasets) and requires a considerable breadth of expertise for safe lifecycles (from development to deployment and commercialisation).

The stated goals of the Strategy can be summarised as an increase of AI-related productivity and innovation, beneficial practical implementations of AI and a trustworthy system of AI governance; delivered through a “three pillars” framework.

Pillar 1: Investing in the long-term needs of the AI ecosystem

There is a need to attract and train qualified people to further the development of AI, especially given the significant gap between supply and demand of AI skills. The £46m Turing AI fellowships, among others, are projected to lead to a great number of recruitments of leading researchers across a wide range of disciplines. The Global Talent visa route and similar initiatives are also aimed at mobilising AI talent from around the globe.

The National AI Research and Innovation (R&I) Programme is envisioned to develop transformative AI technologies for common challenges, increase R&I capacity, encourage cross-disciplinary collaborations, and support the adoption of AI (e.g., through challenge-driven research). Programmes such as Horizon Europe are expected to further increase this drive on an international level.

The importance of the availability of secured, accessible, fit-for-purpose data for AI algorithms is also not overlooked. The ongoing “Data: A new direction” consultation is already set to deal with many surrounding issues, and the Central Digital and Data Office also encourages the open availability of high-standard data.

On the financial side, the government remains committed to monitoring AI R&D funding nationally, especially to break down investment barriers. The Innovation Strategy aims at furnishing lenders with higher risk-assessing skills to facilitate access to R&I funding; a good example being the £375m “Future Fund: Breakthrough”, encouraging the cooperation of private investors and the government.

Pillar 2: Ensuring AI benefits all sectors and regions

The Office for AI and UKRI are planning a programme to identify the creation of opportunities for businesses to use AI, encourage developers to diversify the applicability of AI, and increase investors’ relevant knowledge about where critical financing may be more easily offered.

Challenge-driven AI is recognised as a key factor in powering R&I and its practical implementations. The COVID-19 Early Warning System and the National COVID-19 Chest Imaging Database are quoted as prominent examples where AI is widely used for publicly beneficial purposes, as is the incentive to employ AI in the service of intelligently combatting global warming.

Pillar 3: Governing AI effectively

AI comes with its own unique set of associated risks (e.g. privacy and human agency) and the Strategy recognises that its spread should be regulated by a risk-assessment framework to prevent and mitigate harm. A national position on AI governance is expected by the Office for AI in 2022.

R&D tax relief for AI development

Almost all commercial AI projects will involve some work that qualifies for R&D relief, but it is important to make sure that your claims are accurate and complete. For help and advice on your ongoing R&D claims please contact Eyad Hamouieh or Greg Howe.  


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