Presenting a Qualitative Model of Artificial Intelligence Value Creation in the Human Resource Policy-Making Process of the Ministry of Petroleum

Seyed Hamed  Tafteh; Ali Farhadi Mahalli; Ali Reza  Matoufi

Authors

Seyed Hamed Tafteh Department of Public Administration, Go.C., Islamic Azad University, Gorgan, Iran Author https://orcid.org/0009-0001-9949-4922
Ali Farhadi Mahalli Department of Public Administration, Go.C., Islamic Azad University, Gorgan, Iran Author https://orcid.org/0009-0007-5703-0947
Ali Reza Matoufi Department of Public Administration, Go.C., Islamic Azad University, Gorgan, Iran Author https://orcid.org/0000-0003-3747-1546

Keywords:

Artificial intelligence value creation, policy, making, human resources

Abstract

Digital transformation and the expanding application of artificial intelligence have subjected human resource policy-making processes to fundamental changes and have increasingly highlighted the necessity of reconsidering value-creation models. Despite the importance of this issue, due to the absence of an integrated framework, the aim of this study was to present a qualitative model of artificial intelligence value creation in the human resource policy-making process of the Ministry of Petroleum. In terms of purpose, the present study was applied-developmental, and in terms of method, it was qualitative with a meta-synthesis approach. Data were collected through a systematic search of Persian and English studies published in reputable scientific databases from 2015 to 2025. Studies were evaluated in several stages based on inclusion and exclusion criteria, including language, publication time span, thematic relevance, scientific credibility, and access to full text. These stages included removing duplicate studies, screening titles and abstracts, and reviewing full texts. Finally, 38 eligible studies were included in the meta-synthesis stage. Data analysis was conducted using the seven-step method of Sandelowski and Barroso (2007), and Lincoln and Guba’s criteria were used to assess the credibility and trustworthiness of the findings. The results of the study led to the presentation of a qualitative model of artificial intelligence value creation in the human resource policy-making process of the Ministry of Petroleum. This model consisted of four main dimensions, namely agenda setting and prioritization, formulation, implementation, and evaluation, and 23 components. The results indicated that artificial intelligence value creation in human resource policy-making requires organizational digital maturity, data governance and management, development of human resource competencies, establishment of technological infrastructure, human–AI synergy, and deployment of a data-driven evaluation system. Overall, the findings of this study show that artificial intelligence value creation in the human resource policy-making process of the Ministry of Petroleum is a multilevel and integrated process that begins with problem identification and is completed through the formulation of intelligent policies, implementation based on technological infrastructure, and data-driven evaluation. This model indicates that value creation through artificial intelligence requires the simultaneous presence of four essential factors: organizational digital maturity, appropriate governance, human capital readiness, and data management.

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Presenting a Qualitative Model of Artificial Intelligence Value Creation in the Human Resource Policy-Making Process of the Ministry of Petroleum

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