Sarcouncil Journal of Engineering and Computer Sciences

Abstract: The oil and gas industry is under pressure to manage growing volumes of complex data to support highly regulated and risk environments. Artificial intelligence (AI) powered solutions are emerging as valuable partners. However, in the AI era, the most effective solutions don’t rely on machines alone, as they blend AI with human expertise as hybrid intelligence. This article theoretically looks at how Oil and Gas companies can define enterprise data management systems, particularly in areas of Data Governance, Asset Hierarchies, Data Standards, and material classification leveraging AI capabilities. In the area of data standards and data quality, AI can automate routine tasks like Intelligent Automation, real-time feedback loops, and guided suggestions that can help reduce the data cleansing cycles and benefit trust in their data, faster availability for the maintenance work process, and supports audit, operational efficiency and compliance and industry standards (ISO 14224). It is very important to incorporate hybrid intelligence for organizations that are undergoing transformation or planning for large-scale modernization initiatives. Based on my experience, this approach leads to tangible improvement in master records to complex asset structures (L1 through L8) and improves compliance and accelerates workflows for their preventive and reactive process. Hybrid intelligence brings together humans and AI to work alongside to support the volume and speed. The organizational part of governance can provide human judgment and oversight of data, while AI can support the data volume and improve the decision-making process. This structure of human intervention brings high-impact decisions between innovation and accountability.