IMAI Evaluation Cover Letter
Published 16 December 2022
© Crown copyright 2022
This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk.
Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.
This publication is available at https://www.gov.uk/government/publications/evaluation-of-the-industrial-masters-in-ai-imai-programme/imai-evaluation-cover-letter--2
In 2021 the UK published the National AI Strategy which set out our ten year plan to strengthen the UK’s role as a global AI leader. This built on the success of the AI Sector Deal, announced in 2018, which provided a £1 billion commitment to realise AI technology’s economic and societal potential. Developing the AI skills and talent of the UK workforce is central to this goal.
The 2018 AI Sector Deal committed to supporting industry to invest in an AI master’s programme. The resulting Industry-Funded Masters in AI (IMAI) included support for up to 200 AI Masters places at UK universities, starting in September 2019. The IMAI programme demonstrated a wide range of successes and highlighted a number of lessons for future government interventions supporting the AI skills pipeline.
Employing a novel approach, the programme successfully leveraged £3.3 of industry funding for AI Masters for every £1 of public spend. Beyond the financial benefits, the design of the programme facilitated engagement between Higher Education Institutions and large companies, including DeepMind, Quantum Black, BAE Systems and more. Through this programme, the government provided an opportunity for students across the majority of regions to develop their skills in AI, with twelve out of seventeen institutions located outside of London and the South East. Additionally, by facilitating partnerships between industry and academia, participating universities were able to improve the business relevance of their AI Masters’ courses, helping to meet the demand for industry relevant skills.
Despite these significant accomplishments, the evaluation highlighted several limitations in the programme. Specifically, these fell in the approaches to data collection, programme objectives, and marketing and publicity. A lack of appropriate data collection meant there were limited mechanisms for evaluating student participation and graduate outcomes. Additionally, not all of the programme’s objectives were suitably represented in the Institute of Coding’s grant agreement, such as hard targets on the number of places funded. The initial targets were set relatively high and future programmes would benefit from a more evidence based approach to set more realistic targets. Finally, stakeholders indicated that more could have been done to publicise the programme to industry, Higher Education Institutions and students.
The successes and limitations of the IMAI programme have already shaped and informed the design and delivery of the AI and Data Science Conversion Course programme, announced in 2019. For example, the IMAI programme has provided valuable insights in how to successfully leverage industry funding, which has been incorporated into the design of the second phase of the AI and Data Science Conversion Course programme. The programme as a whole is also taking an improved approach to data collection, objective setting, and marketing and publicity, to ensure strong value for money for public spending. The appointment of a dedicated employer engagement partner is ensuring a targeted focus on building strong relationships between industry, academia, participating students, and the wider AI skills community to drive stronger stakeholder involvement in the programme. The programme is also focused on improving the diversity of students taking up AI courses, and emerging findings from our improved data collection process has enabled us to demonstrate the value of scholarships in improving diversity and the representation of women, as well as black and disabled students in the AI ecosystem.
Evaluation is an essential element of the policy process and ensures government officials and delivery partners learn from the successes and challenges of novel policy interventions. We have taken stock of the lessons from the IMAI evaluation, and will continue to incorporate them into the design of future AI skills initiatives. Publication of this report will enable other government skill initiatives to learn from the challenges faced within this programme.