Measuring the demand for AI skills in the United Kingdom:
This paper estimates the artificial intelligence-hiring intensity of occupations/industries (i.e. the share of job postings related to AI skills) in the United Kingdom during 2012-22. The analysis deploys a natural language processing algorithm (NLP) on online job postings, collected by Lightcast, w...
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| Main Author: | |
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| Other Authors: | , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Paris
OECD Publishing
2024
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| Series: | OECD Artificial Intelligence Papers
no.25 |
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | This paper estimates the artificial intelligence-hiring intensity of occupations/industries (i.e. the share of job postings related to AI skills) in the United Kingdom during 2012-22. The analysis deploys a natural language processing algorithm (NLP) on online job postings, collected by Lightcast, which provides timely and detailed insights into labour demand for different professions. The key contribution of the study lies in the design of the classification rule identifying jobs as AI-related which, contrary to the existing literature, goes beyond the simple use of keywords. Moreover, the methodology allows for comparisons between data-hiring intensive jobs, defined as the share of jobs related to data production tasks, and AI-hiring intensive jobs. Estimates point to a rise in the economy-wide AI-hiring intensity in the United Kingdom over the past decade but to fairly small levels (reaching 0.6% on average over the 2017-22 period). Over time, the demand for AI-related jobs has spread outside the traditional Information, Communication and Telecommunications industries, with the Finance and Insurance industry increasingly demanding AI skills. At a regional level, the higher demand for AI-related jobs is found in London and research hubs. At the occupation level, marked changes in the demand for AI skills are also visible. Professions such as data scientist, computer scientist, hardware engineer and robotics engineer are estimated to be the most AI-hiring intense occupations in the United Kingdom. The data and methodology used allow for the exploration of cross-country estimates in the future. |
| Physical Description: | 1 Online-Ressource (26 Seiten) 21 x 28cm. |
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| 520 | |a This paper estimates the artificial intelligence-hiring intensity of occupations/industries (i.e. the share of job postings related to AI skills) in the United Kingdom during 2012-22. The analysis deploys a natural language processing algorithm (NLP) on online job postings, collected by Lightcast, which provides timely and detailed insights into labour demand for different professions. The key contribution of the study lies in the design of the classification rule identifying jobs as AI-related which, contrary to the existing literature, goes beyond the simple use of keywords. Moreover, the methodology allows for comparisons between data-hiring intensive jobs, defined as the share of jobs related to data production tasks, and AI-hiring intensive jobs. Estimates point to a rise in the economy-wide AI-hiring intensity in the United Kingdom over the past decade but to fairly small levels (reaching 0.6% on average over the 2017-22 period). Over time, the demand for AI-related jobs has spread outside the traditional Information, Communication and Telecommunications industries, with the Finance and Insurance industry increasingly demanding AI skills. At a regional level, the higher demand for AI-related jobs is found in London and research hubs. At the occupation level, marked changes in the demand for AI skills are also visible. Professions such as data scientist, computer scientist, hardware engineer and robotics engineer are estimated to be the most AI-hiring intense occupations in the United Kingdom. The data and methodology used allow for the exploration of cross-country estimates in the future. | ||
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| spelling | Schmidt, Julia VerfasserIn aut Measuring the demand for AI skills in the United Kingdom Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane Paris OECD Publishing 2024 1 Online-Ressource (26 Seiten) 21 x 28cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OECD Artificial Intelligence Papers no.25 This paper estimates the artificial intelligence-hiring intensity of occupations/industries (i.e. the share of job postings related to AI skills) in the United Kingdom during 2012-22. The analysis deploys a natural language processing algorithm (NLP) on online job postings, collected by Lightcast, which provides timely and detailed insights into labour demand for different professions. The key contribution of the study lies in the design of the classification rule identifying jobs as AI-related which, contrary to the existing literature, goes beyond the simple use of keywords. Moreover, the methodology allows for comparisons between data-hiring intensive jobs, defined as the share of jobs related to data production tasks, and AI-hiring intensive jobs. Estimates point to a rise in the economy-wide AI-hiring intensity in the United Kingdom over the past decade but to fairly small levels (reaching 0.6% on average over the 2017-22 period). Over time, the demand for AI-related jobs has spread outside the traditional Information, Communication and Telecommunications industries, with the Finance and Insurance industry increasingly demanding AI skills. At a regional level, the higher demand for AI-related jobs is found in London and research hubs. At the occupation level, marked changes in the demand for AI skills are also visible. Professions such as data scientist, computer scientist, hardware engineer and robotics engineer are estimated to be the most AI-hiring intense occupations in the United Kingdom. The data and methodology used allow for the exploration of cross-country estimates in the future. Economics Employment Science and Technology United Kingdom Pilgrim, Graham MitwirkendeR ctb Mourougane, Annabelle MitwirkendeR ctb |
| spellingShingle | Schmidt, Julia Measuring the demand for AI skills in the United Kingdom Economics Employment Science and Technology United Kingdom |
| title | Measuring the demand for AI skills in the United Kingdom |
| title_auth | Measuring the demand for AI skills in the United Kingdom |
| title_exact_search | Measuring the demand for AI skills in the United Kingdom |
| title_full | Measuring the demand for AI skills in the United Kingdom Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_fullStr | Measuring the demand for AI skills in the United Kingdom Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_full_unstemmed | Measuring the demand for AI skills in the United Kingdom Julia, Schmidt, Graham, Pilgrim and Annabelle, Mourougane |
| title_short | Measuring the demand for AI skills in the United Kingdom |
| title_sort | measuring the demand for ai skills in the united kingdom |
| topic | Economics Employment Science and Technology United Kingdom |
| topic_facet | Economics Employment Science and Technology United Kingdom |
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