Saqib Ghani

This session explores how energy companies can harness big data, machine learning, and AI to optimize plant and field operations. From predictive maintenance to smart grid optimization, attendees will learn how to apply data analytics to improve performance, reduce costs, enhance safety, and support the energy transition. 

Key Themes: 

• Using sensor data to anticipate equipment failures, schedule proactive servicing, and minimize downtime 
• Identifying inefficiencies across plants and distributed systems, optimize resource allocation, and improve overall performance 
• Training models to detect patterns, predict outcomes, and automate decisions 
• Enabling advanced insights and intelligent automation with AI 
• Connecting sensors and devices for real-time data collection 
• Using dashboards and reports to make complex insights actionable

• Learn how predictive analytics and sensor data can help identify anomalies before failures occur, reducing downtime and maintenance costs.
• Explore how intelligent forecasting and usage-based insights can optimize spare parts management and reduce excess stock.
• Discover how historical data can be leveraged to generate consistent, accurate workflows that accelerate execution and reduce human error.
• Understand how integrating asset data across platforms and cleansing inputs ensures trustworthy analytics and scalable decision-making.
• Hear how organizations are navigating cultural resistance and aligning teams to support enterprise-wide adoption of smart asset tools, including AI-powered solutions.