AI Acceptance and Employee Productivity in The Oil And Gas Sector: A Qualitative Study of The Acceptance–Productivity Gap
Hisyam Muhammad Abdullah ORCID ↗ · Anggara Wisesa ORCID ↗
International Journal of Research in Business and Social Science · 2026 · Vol. 15 / Issue 6 · 16-27
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Abstract
The implementation of Artificial Intelligence (AI) in the oil and gas sector is increasingly expanding as an effort to improve operational efficiency and support employees’ work activities. However, the successful adoption of AI depends not only on the availability of technology but also on employees’ level of acceptance and ability to utilize it effectively. This study aims to analyze the impact of AI Acceptance on employee productivity at PT Seashore and identify the factors that cause AI acceptance to have not yet resulted in optimal productivity improvements. This study employs a qualitative approach using a case study method through semi-structured interviews with three AI-using employees and four key informants. Data were analyzed thematically based on the Technology Acceptance Model (TAM) perspective using Open Code. The findings indicate that AI Acceptance has a good impact on productivity, particularly in administrative, repetitive, and structured tasks, by saving time and improving efficiency. However, this impact remains suboptimal due to limitations in prompting, inaccuracies and hallucinations, the need for verification and rework, the risk of overreliance, limited technical understanding, task suitability, and constraints related to AI access and governance.
Keywords: {'name': 'AI Acceptance'}, {'name': 'Employee Productivity'}, {'name': 'Technology Acceptance Model'}, {'name': 'Oil and Gas'}, {'name': 'Artificial Intelligence'}
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Hisyam Muhammad Abdullah
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Anggara Wisesa
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