Each round table has a different topic, and attendees can select the round table they want to participate in. Round table leaders will spend the first 15 minutes meeting the delegates and providing a case study/lessons learned log/industry update and then moderating a 30-minute discussion with the group where they can give feedback and ask questions. The final 10 –15 minutes will be spent agreeing on 3 -5 industry recommendations. A selection of these recommendations will be shared with the whole audience, and all of them will be summarized in the post-event report.

1. Adapting AI Solutions for Legacy Systems: Overcoming Integration Challenges
   Don Murray, Safe Software
2. Demystifying AI: Bridging the Knowledge Gap
   George Danner, Business Laboratory
3. Data Democratization: Empowering Teams with Data-Driven Insights
   Catalina Herrera, Dataiku
4. Optimizing AI for Edge Computing: Extending AI Capabilities Beyond the Cloud
5. Building Trust in AI Models: Transparency and Explainability
   Tanima Dutta, ONGC Videsh
6. Scaling AI Applications: From Pilots to Enterprise-Wide Adoption
   Sean Mee, OutSystems
7. Empowering Middle Management in AI Implementation: Bridging Strategy and Execution
   Sean Barnes, WSS Solutions
8. Ensuring Data Quality for AI: Challenges in Data Collection and Cleaning
9. Exploring AI-Driven Predictive Maintenance: Real-World Use Cases
   Justin Swansburg, Databot
10. Balancing Automation with Human Expertise in AI-Driven Decision Making
11. Future-Proofing AI Investments: Adapting to Rapid Technological Change
    Dr. Riad Efendi, Technip FMC
12. Using Publicly Available Data to Analyze Hiring Trends and Patterns
    Abhijeet Narvekar, The FerVID Group