AI presents tremendous opportunities for industrial organizations to improve efficiency, reduce downtime, and enhance decision-making. However, deploying AI in operational technology OT environments where uptime, safety, and security are critical, is uniquely challenging. This session will offer a practical strategies for successfully integrating AI into complex, legacy-rich industrial systems. Drawing on real-world experience from critical infrastructure and energy sectors, the session will outline key steps to assess AI readiness, system protection, and integration. Attendees will gain actionable guidance and design on mitigating cyber risks, AI pitfalls, and aligning AI efforts with broader enterprise security and compliance goals. This will focus on a Crawl, Walk, Run model of maturity,

We will explore common pitfalls, such as assuming IT patterns can directly apply to OT, and how to avoid them. The talk will also address the organizational challenges of AI adoption, including bridging IT/OT silos and building the right cross-functional teams. Whether you're starting your AI journey or scaling existing initiatives, this session will equip you with strategic and technical insights to safely and effectively deploy AI in industrial settings.

Learning Objectives:
Understand the differences in priorities between OT and IT systems
Define key technical and cultural prerequisites for AI in OT environments
Safeguard AI pipelines from cyber threats and data quality issues
Apply architecture patterns for edge, cloud, and hybrid AI deployment
Foster collaboration across IT, OT, and data science teams