Petros Paterakis

As AI continues to evolve at breakneck speed, the energy sector stands at a pivotal crossroad, balancing the promise of transformative efficiency with the complexity of real-world implementation. The true value of AI lies not in experimentation, but in aligning deployment with strategic business priorities and operational realities. This session explores how energy organizations can move beyond hype to build pragmatic, high-impact AI roadmaps.

• Why targeting business-critical challenges, not just technically interesting problems, is essential for ROI. Learn how to identify and prioritize high-value AI use cases that align with core operational goals
• Is a top-down, enterprise-wide AI rollout always the right approach? For many operators, a more agile strategy which leverages plug-and-play models within specific business units can accelerate time-to-value while minimizing risk. How do you assess if modular or enterprise scale deployment is right for your business?
• What does a robust AI governance framework look like in practice? It’s time to unpack the organizational structures, cross-functional collaboration models, and oversight mechanisms that support sustainable AI adoption