Authored by Sujoy Choudhury, Chief Strategy Officer, The Chatterjee Group (TCG) & Lummus Digital, and originally published in Refining India (March 2026 Issue), this strategic note explores how oil and gas companies are moving beyond isolated AI pilots to enterprise-scale deployment.
It outlines what it takes to move from experimentation to platform-driven AI adoption across refining and petrochemical operations.
Refining and petrochemical organisations globally are:
Expanding capacity
Managing feedstock variability
Operating under tightening margin pressures
Balancing sustainability mandates with profitability
Yet most AI initiatives remain confined to pilots. Scaling value requires an enterprise-grade AI architecture built for industrial complexity.
A live AI-powered Real-Time Optimisation (RTO) implementation delivering:
$58 million in economic benefit for a $3B petrochemical major
Yield and throughput improvement
Energy savings and margin enhancement
Bottleneck visibility without major capex
Key capabilities required for scale:
Hybrid modelling (first-principles + AI/ML)
Modular analytics engines
Semantic data frameworks (ontology & knowledge graph driven)
Unified real-time + batch data architecture
Enterprise-grade governance and compliance
Cloud-agnostic deployment
Pre-built industrial workflows
Autonomous AI in refinery environments Managing hallucination risks Human-in-the-loop oversight models Safe and scalable AI governance frameworks
