Abstract:
The downstream petroleum industry in Ghana is one among many sectors
characterised by the convergence of numerous hazardous exposures that can
potentially cause serious catastrophe and work-related accidents. Several
studies have been conducted separately on the applications of artificial
intelligence technology, occupational safety, the effects of artificial intelligence
on safety, and technology and occupational safety. The general objective of the
study was to analyse artificial intelligence technology application and
occupational safety to improve occupational safety in downstream petroleum
industry. The study applied the quantitative research approach. The study relied
on primary interval data obtained through questionnaire administration. The
data were processed with tools from STATA 15. Data were analysed using
descriptive, correlation and synthesis frameworks and descriptive statistics,
regression techniques. The results of the study showed that predictive analytics
of the environment was found to be the most common area of AI technology
application in the downstream petroleum industry, followed by cyber security
and compliance with safety rules. Technology attitudes, trust, social norms, and
technology adoption culture were observed to be significant determinants of AI
acceptance in the downstream petroleum sector. The primary effect of AI
technology application in the downstream petroleum sector appears to be
precision in decision. A novel framework for model AI technology application
for improved occupational safety comprising of the following system
characteristics: inputs, AI-based models, occupational safety modes, and
efficiency indices. The study findings have implications for how occupational
health and safety within the downstream petroleum sector is addressed
