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Abstract This manuscript presents the development and deployment of a Machinery Generative Artificial Intelligence (AI) Consultant for gas turbine engines in offshore operations. The initiative aims to reduce Mean Time to Repair (MTTR) and Lost Production Opportunities (LPOs) by providing intelligent, real-time support to field technicians. The solution addresses persistent challenges in offshore troubleshooting, where engineers must navigate extensive technical documentation, hundreds of engineering drawings, and complex alarm tags. Delays in contacting Original Equipment Manufacturer (OEM) and the unavailability of machinery engineers around the clock further compound the issue, often resulting in extended downtime and operational inefficiencies. The AI consultant enhances troubleshooting by interpreting first-out alarm messages and recommending corrective actions based on Integrated Equipment Monitoring (IEM) data. It links directly to relevant engineering drawings and integrates with real-time dashboards to provide contextual alerts. The system is designed to understand and respond to HMI shutdown tags and abnormal machinery conditions, offering step-by-step guidance to technicians. This approach streamlines the diagnostic process and reduces reliance on manual document review or external consultation. The Machinery Generative AI Consultant has been successfully deployed in offshore environments, demonstrating measurable reductions in MTTR and unplanned downtime. Field case studies include resolution of Ignition Failures, Anti-Surge Valve Travel Failures, and Lube Oil High Temperature. The AI-enhanced approach has improved first-response accuracy, reduced troubleshooting time, and enabled safer, more efficient operations. Feedback from field users highlights the tool's ability to deliver timely, relevant insights without the need for extensive document searches or delayed OEM support. This work introduces a hybrid approach that combines structured troubleshooting logic with generative AI-driven decision support. It is among the first implementations in the region to integrate HMI and IEM data into an AI-powered tool specifically for gas turbine engines. The solution exemplifies how digital transformation and AI can be applied to legacy equipment to unlock operational value in offshore oil and gas settings. By automating complex diagnostic workflows and embedding expert knowledge into an accessible platform, the AI consultant represents a significant advancement in machinery support and reliability engineering.