Slide 1: Data to Decision: Phenomenological AI in Energy Smart Environments. Slide 2: Agenda. Slide 3: The Vision: Energy Smart Environments. Slide 4: The Challenge: Complexity & Dynamics. Slide 5: The Data Deluge in Energy. Slide 6: Data-Driven Energy Management: The Foundation. Slide 7: Benefits of Data-Driven Approaches. Slide 8: Enter Artificial Intelligence. Slide 9: AI Techniques in Energy Management. Slide 10: Beyond the Black Box: Introducing Phenomenological AI. Slide 11: Phenomenological vs. Purely Data-Driven AI. Slide 12: Why Phenomenological AI for Energy?. Slide 13: Key Principles of Phenomenological AI in Energy. Slide 14: The Data Ecosystem: Sources & Integration. Slide 15: Data Challenges & Opportunities. Slide 16: The Data-to-Decision Pipeline. Slide 17: Phenomenological AI in Practice: Applications. Slide 18: Building the Framework: Key Considerations. Slide 19: Overcoming Hurdles: Trust & Interpretability. Slide 20: The Future: Integrated & Autonomous. Slide 21: Conclusion: Powering Decisions with Phenomenological AI