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National AI Strategy - Policy brief

This brief allows you to get a quick understanding of the Department for Business, Energy, and Industrial Strategy and Department for Digital, Culture, Media, and Sport's National AI Strategy and what it means for local government


  • The UK’s successes in AI were supported by the 2017 Industrial Strategy, which set out the government’s vision to make the UK a global centre for AI innovation
  • In April 2018, the government and the UK’s AI ecosystem agreed to a nearly £1 billion AI Sector Deal to boost the UK’s global position as a leader in developing AI technologies.
  • The Office for Artificial Intelligence was created as a new team to take responsibility for overarching AI policy across the government and to be a focal point for the AI ecosystem through its secretariat of the AI Council.
  • The government’s AI Council, established in 2019, has played a central role in developing this strategy, including its roadmap published at the beginning of 2021.
  • The strategy recognises that Artificial Intelligence can mean different things in different scenarios. A working definition is included: ‘machines that perform tasks normally requiring human intelligence, especially when the machines learn from data how to do those tasks’.

What does it mean for local government?

The use of AI, more specifically predictive analytics, remains at an early stage in local government, although it is becoming more common. Much of the sector is just starting to consider the opportunities and risks of this type of technology. To support the sector in predictive analytics, the Local Government Association produced this guide for councils and provided case studies from three local government projects that utilised the technology.

When considering the use of these technologies, a sector-specific approach is essential. Data plays a vital role in the work of councils, and the sector is committed to protecting people’s privacy. Councils must be able to innovate whilst also ensuring that the ethical and legal context they are operating in protects the public and strengthens trust in the use of data. It is also crucial that local government complies with the public sector equality duty. The Equality and Human Rights Commission recently published this guide for public bodies on considering the Public Sector Equality Duty when a public body uses artificial intelligence.

The Local Government Association has been working alongside the Central Digital and Data Office (CDDO) in the Cabinet Office and the Centre for Data Ethics and Innovation (CDEI) to investigate the interest and approach for a national online register or hub capable of holding high-level information about data analytics projects in the public sector. These projects would include those making use of artificial intelligence, machine learning and predictive analytics to support outcomes and decision-making. This includes the development of the Algorithmic Transparency Standard.

If you work in local government and are interested in using advanced and predictive analytics, consider joining the Advanced & Predictive Analytics Network in Local Government (APAN). The network allows practitioners working in local authorities to share intelligence and promote transparency in using algorithms and predictive analytics in councils. For more information and how to join, visit the website.


  • As the fastest-growing deep technology in the world, Artificial Intelligence (AI) holds enormous potential to drive economic growth and transform societies. The government believes the UK is well placed to lead the world over the next ten years in research and innovation, talent development and creating a progressive regulatory and business environment.



There are three pillars to the National AI Strategy:

Investing in the long-term needs of the ecosystem

Developing skills and talent:

Research with employers has found that recruiting and retaining top AI and data science talent within the UK is challenging, yet demand is increasing. The government wants to close the skills gap across those who:

  • Build AI, meeting the demand in industry and academia through expanding fellowships and conversion courses
  • Those who use AI by expanding training for the existing workforce by working with industry to identify what skills are needed, and developing skills boot camps
  • Inspire all to be excited by the possibilities of AI, including children, so there’s a growing and diverse AI literate workforce.

​​​Investing in research and innovation:

The Government plans to launch a national AI Research and Innovation Programme, so the UK is a starting point for many AI breakthroughs over the next ten years. This research programme will aim to:

  • Develop transformative new AI technologies
  • Build new research and innovation capacity to deliver the ideas, technologies, and workforce of the future
  • Build collaborative networks across the UK AI research ecosystem
  • Support the UK’s adoption of AI technologies across all sectors.
  • Strengthen international collaboration in research and innovation by continuing to participate in Horizon Europe and using official development assistance to support R&D partnerships in developing countries.

Access to data:

The National Data Strategy lays out the government’s approach to ‘developing effective AI systems’. However, ethical data stewardship is crucial to ensuring the economic and social benefit of increased data availability can be realised and data owners can be trusted. Strengthening data foundations, which improves the quality of data overall, such as ensuring its findable, accessible, interoperable, and reusable (FAIR), is key to higher AI adoption levels. The government estimates that 80% of the time spent on an AI project is spent cleaning, standardising, and making the data fit for purpose. Poor-quality datasets are a risk for existing biases and exclusions in AI if they are unrepresentative. The government is committed to strengthening how public authorities share data, including through APIs (Application Programming Interfaces), and encouraging businesses to do the same.

Access to computing power:

Computing power is essential to developing and using AI and is both a competitiveness and security issue. Yet the UK’s infrastructure lags behind other major economies, and there is an access gap between large-scale enterprises and researchers. As part of the strategy, the government committed to evaluating the needs and capacity within the UK and driving sustained public and private investment.

Accessing finance:

Despite investment in deep tech companies increasing by 291% in the five years preceding the strategy, deal sizes remain considerably smaller compared to the US. The government is committed to evaluating the state of funding and exploring investment gaps and barriers to accessing financing for AI innovative companies. To ensure that investment into the UK’s AI ecosystem complies with efforts to protect national security, the government introduced the National Security and Investment Act, which provided new powers to screen investments effectively and efficiently.

Ensuring AI benefits all sectors and regions

Commercialising AI and driving adoption:

The strategy recognises the government’s role in using public procurement to broaden the use of AI and the technology to solve public policy challenges. According to EY research, 27% of UK organisations in the private and third sectors have implemented AI technologies in business processes, 38% are planning and piloting AI technology, and 33% have not adopted AI and are not planning to. The government committed as part of the strategy to evaluating what support is required to grow the market.

AI for public benefit:

The government recognises its role in stimulating and applying AI innovation to broader strategic goals across sectors and industries, such as in the NHS and meeting the government’s net-zero targets. This will be done through the Office for AI, working closely with the Office for Science and Technology to understand the government’s strategic goals and where AI can provide a catalytic contribution. The Innovation Strategy also set out the government’s plans to stimulate innovation, which includes AI as an innovative technology.

Governing AI effectively

Protecting the public and building trust:

Concerns about the potential risks and harms associated with AI technologies regarding fairness, bias, and accountability have been raised. Cyber security should be considered early in developing and deploying AI systems to prevent security risks from arising: a ‘secure by design’ approach. Different regulators currently regulate AI, and a government and House of Lords report had the view that ‘blanket AI-specific regulation at this stage would be inappropriate and existing sector-specific regulators are best placed to consider the impact on their sector of any subsequent regulation which may be needed.

International governance and collaboration:

The UK helped found the Global Partnership on AI. It supported the global development of trust frameworks at the OECD, Council of Europe, and UNESCO levels.

AI and global digital technical standards:

The UK’s Plan for Digital Regulation sets out the government’s ambition to use digital technical standards to provide an agile and pro innovation way to regulate AI technologies and build consistency in technical approaches.

AI assurance:

The assurance ecosystem is emerging within the public and private sectors but is currently fragmented. The Centre for Data Ethics and Innovation is publishing an AI assurance roadmap to support the development of a mature AI assurance ecosystem.

Public sector leading from the front:

The Government Digital Service worked with the Alan Turing Institute to guide AI ethics and safety in the public sector in 2019. This guidance identifies potential harms caused by AI systems and proposes measures to counteract them. The government is currently working with the Alan Turing Institute to update them to provide public servants with the most current information about state of the art in responsible AI innovation. The Cabinet Office developed an Algorithmic Transparency Standard to address algorithmic decision-making bias.