The UK government: thoughts on the impact of AI on UK jobs and training

The report titled "The Impact of AI on UK Jobs and Training" was published in October 2023 by the UK Department for Education. The report aims to provide an assessment of the potential impact of AI on jobs and training in the UK, with a focus on identifying which jobs are most likely to be affected by advances in AI and how training pathways can be adapted to prepare workers for the changing landscape of work.

The report begins with an introduction that highlights the growing importance of AI in the UK economy and the potential implications for the labour market. It notes that while AI has the potential to increase productivity and create new high-value jobs, it also poses challenges and disruptions to the labour market. The report aims to provide a comprehensive analysis of the potential impact of AI on jobs and training in the UK, with a focus on identifying which jobs are most likely to be affected by advances in AI and how training pathways can be adapted to prepare workers for the changing landscape of work.

How are occupations assessed for their exposure to the impact of AI?

The AI Occupational Exposure (AIOE) score is a measure used in the report to estimate the relative exposure of UK jobs to AI. It is calculated based on the level and importance of each ability combined with the rating for the relatedness of each AI application to create the score. The AIOE score allows jobs to be ranked to show which jobs are more and less likely to be impacted by advances in AI, based on the abilities required to perform the job. The AIOE score is constructed based on assumptions around the use of a defined set of common AI applications and it is believed that these represent fundamental applications of AI. The AIOE score is used to assess the relative exposure of UK jobs to AI by industry, geography and skill level of occupation.

How does exposure to AI vary across different industries and regions in the UK?

According to the report, the finance and insurance sector is the most exposed to AI, followed by the information and communication, professional, scientific and technical, property, public administration and defence and education sectors. In terms of regions, workers in London and the South East have the highest exposure to AI, reflecting the greater concentration of professional occupations in those areas. Workers in the North East are in jobs with the least exposure to AI across the UK. However, overall, the variation in exposure to AI across the geographical areas is much smaller than the variation observed across occupations or industries. The report also notes that employees with more advanced qualifications are typically in jobs more exposed to AI. For example, employees with a level 6 qualification (equivalent to a degree) are more likely to work in a job with higher exposure to AI than employees with a level 3 qualification (equivalent to A-Levels). Employees with qualifications in accounting and finance through Further Education or apprenticeships and economics and mathematics through Higher Education are typically in jobs more exposed to AI. Employees with qualifications at level 3 or below in building and construction, manufacturing technologies and transportation operations and maintenance are in jobs that are least exposed to AI.

Which occupations are most exposed to AI?

The report provides a list of the top 20 occupations that are most exposed to AI, based on the AI Occupational Exposure (AIOE) score. Some of the occupations most exposed to AI include management consultants, business analysts, accountants and psychologists. These occupations are associated with more clerical work and are prevalent across finance, law and business management roles. On the other hand, the occupations least exposed to AI include sport professionals, roofers and steel erectors. It's important to note that the exposure score is based on several assumptions and the rankings should be interpreted with caution. The themes highlighted by the analysis are expected to continue.

What are the training routes to the successful adoption of AI in British people and businesses?

The report discusses several training routes that are associated with different levels of exposure to AI in jobs. These training routes include:

1. General compulsory education: This is the first level of education and is typically completed by age 16. Jobs that require only this level of education are less exposed to AI.

2. General compulsory education with a longer period of work-related training or work experience: This is the second level of education and is typically completed by age 18. Jobs that require this level of education are more exposed to AI than those that require only general compulsory education.

3. Post-compulsory education below degree level: This is the third level of education and includes vocational qualifications and apprenticeships. Jobs that require this level of education are more exposed to AI than those that require only general compulsory education.

4. Professional occupations normally requiring a degree or equivalent period of relevant work experience: This is the fourth level of education and includes jobs that require a degree or equivalent work experience. Jobs that require this level of education are the most exposed to AI. The report also notes that employees who achieved apprenticeships at level 4 and above are in jobs most exposed to AI compared to any other route. However, this is based on a small sample and the reference period for the data means it mainly includes the level 4 and 5 apprenticeship frameworks available before the introduction of new standards and growth in higher level apprenticeships from 2017 onwards. These apprenticeships were predominantly in accounting, professional services and IT, which typically are held by those in the occupations that are most exposed to AI.

What is the overall impact of AI on UK jobs and training?

The overall impact of AI on UK jobs and training is complex and multifaceted. While AI has the potential to increase productivity and create new high-value jobs in the UK economy, it also poses challenges and disruptions to the labour market. The report highlights that 10-30% of jobs are automatable with AI, indicating that a significant portion of the workforce may face changes in their job roles due to automation. Furthermore, the exposure to AI varies across different occupations, industries and geographic locations. Certain occupations, particularly those in professional and managerial roles, are more exposed to AI, while others, such as sport professionals and construction workers, are less exposed. This variation in exposure is also observed across different levels of education and training routes, with employees with higher levels of qualification and certain training routes being in occupations more exposed to AI. Overall, the impact of AI on UK jobs and training underscores the importance of understanding and preparing for the potential changes in the labour market. It is essential for policy-makers, educators and businesses to consider the implications of AI on jobs and training and to develop strategies to support workers in adapting to the evolving landscape of work.

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