Factors that Influence AI Investment Decisions in Oman's Hydrocarbons Industry: A Review of the Theoretical Literature and Proposed Theoretical Mode

Abstract

Artificial Intelligence technologies have exceptional capabilities that enhance the production efficiency of oil and gas companies by saving time and energy in terms of the technologies used and the workers involved, provided that the technology used is cost-effective for the field of concern. AI gradually penetrates various stages of the oil and gas sectors, such as intelligent drilling, intelligent development, intelligent pipelines, and intelligent refineries. This paper presents a comprehensive model for studying the elements that drive AI investment decisions in Oman's hydrocarbons industry. This study combined theories of the technology acceptance model (TAM), innovation diffusion theory (IDT), business environment factors, and risk management with AI investment decisions. This study aims to discover the key factors that influence AI investment decisions by studying numerous elements that impact AI investment decisions in the sector. These drivers include AI's innovation attributes, the external and internal business environment, risk management, and the moderating of perceived usefulness and perceived ease of use. Gaining insight into these elements enables players in Oman's hydrocarbons sector to make informed decisions about AI investment decisions. This, in turn, can lead to increased operational efficiency, cost savings, and better decisionmaking processes.