THE IMPACT OF ARTIFICIAL INTELLIGENCE ON JOB DESCRIPTIONS: EVOLVING SKILLS AND HR CHALLENGES
DOI:
https://doi.org/10.55197/qjssh.v7i4.1297Keywords:
artificial intelligence, job descriptions, skill transformation, human resource management, systematic literature review, task-technology fitAbstract
Although AI is reshaping work practices, few efforts have been made to examine the impact on job description as a formal organisational artefact that represents work content, competencies, and performance expectations. The present study aims to correct this gap by conducting a systematic literature review of 52 peer-reviewed studies published from 2014 to 2024 from Scopus, Web of Science Core Collection and EBSCO Business Source Complete using the PRISMA methodology. The review reflects the theoretical frameworks in Task Technology Fit and Skills Biased Technological Change, which analyse the impact of AI on task allocation and competency formation in different occupation contexts. The synthesis shows a marked shift in the design of job descriptions, where the routine specification of tasks has become less salient, higher order cognitive, interpersonal, and adaptive competencies have become more salient, and AI literacy and ethical judgement have become central competency expectations. Furthermore, the evidence also suggests that these changes are impacting core HR processes, revealing the shortcomings of traditional methods for job analysis, workforce planning and talent acquisition. These shifts in job descriptions, when led by AI, are not just technological substitutions, but a process in which the boundaries of roles, the expectations of skills, and the identities of jobs are redistributed and redefined at the same time. This paper extends the understanding of the role of job descriptions as strategic tools in which technological change is negotiated and embedded within organizational systems, further conceptualizes the work and technology approach to the micro level of job design, and builds an evidence based competency framework that can serve as a guideline for the organizational adaptation in the future in work environments that are increasingly affected by the use of AI tools.
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