Each round table covers a different topic, allowing attendees to select which one to join. Round table leaders will begin with a 5-minute introduction of themselves and a brief overview of the topic, which can include a case study, lessons learned log, or industry update. They will then facilitate a 40-minute discussion with the group, encouraging feedback and questions. The last 10 minutes will focus on agreeing on five industry recommendations. These recommendations will be shared with the entire audience and summarized in the post-event report.

1. Exploring practical pathways to scale AI/ML projects from pilot to enterprise-wide implementation.
    
2. Addressing how to equip teams with the mindset and skills needed to thrive in digital-first operations.
    
3. Tackling the unique challenges of securing industrial networks and legacy OT infrastructure.
    
4. Establishing trust, quality, and accessibility in enterprise data through effective governance frameworks.
    
5. Unpacking lessons learned in rolling out, maintaining, and integrating IoT sensors across field assets.
    
6. Assessing the organizational, technological, and cultural readiness for semi- or fully autonomous operations.
    
7. Exploring how AI and digital tools can drive measurable emissions reductions and environmental compliance.
    
8. Identifying the critical competencies and training approaches to future-proof the energy workforce.
    
9. Discussing how standards like OSDU enable interoperability, scalability, and vendor-neutral ecosystems.
    
10. Ensuring responsible AI development with policies for bias mitigation, transparency, and data ethics.