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Adoption of AI by the HR function in the civil service

Adoption of AI by the HR function in the civil service
Adoption of AI by the HR function in the civil service
Purpose: this paper uses the Technology Acceptance Model (TAM) to assess the readiness of the HR function within the UK Civil Service (CSHR) to implement AI to support performance. Academic literature in relation to AI acceptance in HR functions is currently limited, so this paper aims to establish a better understanding of the current landscape and level of ambition in this area.

Design/methodology/approach: a quantitative research approach was adopted to determine likely behavioral intentions of workers in the human resource (HR)function if AI were implemented, by investigating key aspects of the TAM (the perceived usefulness of AI and the transparency of the CSHR in adopting AI).

Findings: while the results suggest that the CSHR is not ready to harness AI opportunities, employees were personally ready, despite perceiving a lack of sufficient knowledge in this area. The paper identifies that more time needs to be spent on raising awareness and upskilling the HR function before the CS can be considered fully ready to harness these opportunities.

Originality/value: the penetration of artificial intelligence (AI) technologies into the global workforce brings transformative potential to the governance structures and use of digital platforms in public sector organizations. AI is likely to play a role in the operation of HR functions and influence how they might operate in the near future.
0142-5455
Smith, M.
3385b39a-2463-47b0-9e73-0938e03e280e
Prabhakar, G.
5b50483d-63f8-4891-beb0-3fd73a98a033
Nisar, T.M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Tseng, H.
e99b04eb-d384-4d6f-8e37-31f980ffcbc7
Smith, M.
3385b39a-2463-47b0-9e73-0938e03e280e
Prabhakar, G.
5b50483d-63f8-4891-beb0-3fd73a98a033
Nisar, T.M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Tseng, H.
e99b04eb-d384-4d6f-8e37-31f980ffcbc7

Smith, M., Prabhakar, G., Nisar, T.M. and Tseng, H. (2024) Adoption of AI by the HR function in the civil service. Employee Relations. (doi:10.1108/ER-02-2024-0096).

Record type: Article

Abstract

Purpose: this paper uses the Technology Acceptance Model (TAM) to assess the readiness of the HR function within the UK Civil Service (CSHR) to implement AI to support performance. Academic literature in relation to AI acceptance in HR functions is currently limited, so this paper aims to establish a better understanding of the current landscape and level of ambition in this area.

Design/methodology/approach: a quantitative research approach was adopted to determine likely behavioral intentions of workers in the human resource (HR)function if AI were implemented, by investigating key aspects of the TAM (the perceived usefulness of AI and the transparency of the CSHR in adopting AI).

Findings: while the results suggest that the CSHR is not ready to harness AI opportunities, employees were personally ready, despite perceiving a lack of sufficient knowledge in this area. The paper identifies that more time needs to be spent on raising awareness and upskilling the HR function before the CS can be considered fully ready to harness these opportunities.

Originality/value: the penetration of artificial intelligence (AI) technologies into the global workforce brings transformative potential to the governance structures and use of digital platforms in public sector organizations. AI is likely to play a role in the operation of HR functions and influence how they might operate in the near future.

Other
Attached standard file_ (1) - Accepted Manuscript
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More information

e-pub ahead of print date: 28 November 2024
Published date: 20 December 2024

Identifiers

Local EPrints ID: 497337
URI: http://eprints.soton.ac.uk/id/eprint/497337
ISSN: 0142-5455
PURE UUID: 38328e7d-ed8a-428c-92b4-4b77f049680d
ORCID for T.M. Nisar: ORCID iD orcid.org/0000-0003-2240-5327

Catalogue record

Date deposited: 20 Jan 2025 17:50
Last modified: 10 Apr 2025 01:39

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Contributors

Author: M. Smith
Author: G. Prabhakar
Author: T.M. Nisar ORCID iD
Author: H. Tseng

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