Generative AI and Agentic Systems in Energy: Taming Big Data, AI, and Beyond for Energy Now
A comprehensive full-day workshop covering the latest in AI and energy technologies
▸ Oilfield Digital Maturity – Current State, Digital Twins, Remote Monitoring and Autonomous controls
▸ Advancements in IoT and IIoT – Sensor fusion, Edge, Fog, and Cloud computing, Real-time Operational Data pipelines and AI Readiness
▸ Web 3.0 and Blockchain for energy – Decentralized data, contracts and transactions management at scale
▸ Machine Learning – From predictive to prescriptive to cognitive analytics, current state and cost of delayed adoption
▸ The key concepts, differences and how to leverage AI, Gen AI, Agentic AI
▸ Use cases for predictive maintenance, reduce cost of inefficiency, and proactive decision making with AI, Gen AI and Agentic AI
▸ Data Platforms and Model Platforms – For unifying Operational Technology and Information Technology for maximizing value of data securely and fast
▸ Cyberthreats, Cybersecurity for the hyper connected, real-time operational worlds of energy – The current state, the future needs and pathways with Agentic Systems
▸ Agentic AI Organization – Building a future ready organization in the era of Agentic AI
He is a transformational leader whose work spans industry, academia, and research. Globally recognized for his unique blend of scientific depth, technological expertise, and business strategy, he has made pioneering contributions to Quantum Mechanics, Data Science, Artificial Intelligence, Big Data, and Digital Transformation.
He holds the distinction of being the first Chief Data Scientist in the Oil and Gas/Energy industry. His career includes senior leadership roles at Halliburton—where he served as
Technology Fellow and Chief Data Scientist—along with influential positions at Acxiom Corporation, Network Solutions, and AOL.
Dr. Priyadarshy is currently the CoE-OGE Visiting Chair Professor at IIT Bombay and serves as an adjunct or visiting professor at multiple universities across the United
States, India, and other countries. He is also an advisor, investor, and board advisor for emerging technology companies in the USA, India, and Switzerland.
Dr. Priyadarshy is currently the CoE-OGE Visiting Chair Professor at IIT Bombay and serves as an adjunct or visiting professor at multiple universities across the United States, India, and other countries. He is also an advisor, investor, and board advisor for emerging technology companies in the USA, India, and Switzerland.
With over 56 publications, ten patents, and recognition as the 2021–2022 SPE Distinguished Lecturer, Dr. Priyadarshy continues to shape the future of science, technology, and digital innovation.
Join us for this intensive masterclass and gain practical insights into leveraging generative AI and agentic systems in the energy sector.
Reimagining Energy with Generative and Agentic AI – From Insight to Intelligent Action
▸ By the end of this workshop, participants will be able to:
▸ Identify high-impact Generative AI and Agentic AI use cases across the energy value chain.
▸ Understand production-grade AI architecture for energy environments (IT/OT integration).
▸ Design a practical AI strategy and 12-month roadmap.
▸ Implement guardrails for safety, governance, and compliance.
▸ Develop measurable business cases for AI deployment.
▸ Difference between predictive AI, optimization, digital twins, GenAI.
▸ What agentic AI means: goal-driven orchestration and tool use.
▸ Assistive → Human-in-the-loop → Semi-autonomous systems
▸ Asset performance & predictive maintenance copilots.
▸ Grid & plant operations optimization.
▸ Engineering documentation & knowledge copilots.
▸Customer service & revenue assurance automation.
▸ESG & compliance reporting automation.
▸Interactive table exercise: classify use cases by autonomy level.
▸ Copilot → Co-worker → Crew model.
▸ Retrieval-augmented generation (RAG) for grounded outputs.
▸ Tool-using agents integrating SCADA, EAM, GIS, CRM systems.
▸Policy-as-code guardrails and human approvals.
▸Common failure modes and risk mitigation.
▸ Data layer: time-series, asset data, weather, documents.
▸ Model layer: domain models + GenAI.
▸ Orchestration layer: workflow engines and agent routers.
▸Trust layer: cyber security, identity, OT/IT segregation.
▸Observability: cost, latency, hallucination metrics.
▸ Define north-star business outcomes (reliability, OPEX, emissions).
▸ Balanced portfolio: 70% near-term, 20% augmentation, 10% moonshots.
▸ AI operating model and governance.
▸90-day, 6-month, 12-month roadmap.
▸Select one measurable, bounded use case.
▸ Define KPIs (MTTR, truck rolls avoided, reporting cycle time).
▸ Establish guardrails and approvals.
▸Final principle: Start with workflow + metric + boundary.
Join us for this Reimagining Energy with Generative and Agentic AI – From Insight to Intelligent Action.