Applied AI in Energy Supply Chain Workshop 

Thursday, December 7 | 9am-5pm | Price: $750 


Nick King
Nick King
Data Kinetic

This workshop has been specifically designed for supply chain, procurement, and logistics professionals

Join us for an immersive and interactive workshop focused on the transformative role of Artificial Intelligence (AI) in the energy supply chain. This workshop is designed to provide participants with a comprehensive understanding of how AI can be strategically applied to enhance efficiency, compliance, and sustainability in the energy sector. 

Key Highlights of the Workshop

In-Depth Exploration of Applied AI: 

  • Delve into the world of applied AI systems, understanding their role in profiling and planning for the continuous improvement of energy supply chain systems.

Compliance and External Factors:

  • Gain insights into navigating complex compliance landscapes, including the Inflation Reduction Act (IRA), White House Executive Orders, and other regulatory frameworks.

Practical Use Cases of ML/AI:

  • Learn through real-world examples how machine learning and AI are revolutionizing the stages of discovery, development, production, and enhancement in the energy sector.

Collaboration and Technology Evolution:

  • Discover the importance of teamwork and staying abreast with evolving technologies, working effectively with teams, vendors, and technology partners to ensure operational continuity and capability.

This workshop is ideal for professionals in the energy sector, including environmental and sustainability managers, C-suite executives, technology providers, consultants, data scientists, analysts, AI experts, emission tracking and reporting specialists, and regulatory compliance officers. It promises to be an enlightening experience, equipping participants with the knowledge and skills to harness AI for a more sustainable and efficient energy future.

Post-Day Session Schedule

Morning Session

●    09:00 AM – 10:30 AM: Part One
       ○    Business factors, decision making, organization programs, governance, and value creation assessment.
●    10:30 AM – 11:00 AM: Break
●    11:00 AM – 12:30 PM: Part Two
       ○    Establishing a foundation for compounding systems and knowledge management.
       ○    Architecting for infinitely unique requirements at scale.
       ○    Skill management, and operations.
●    12:30 PM – 01:30 PM: Lunch Break

Afternoon Session

●    01:30 PM – 03:00 PM: Part Three
       ○    Use case exploration and core concepts.
●    03:00 PM – 03:30 PM: Break
●    03:30 PM – 05:00 PM: Part Four
       ○    Hands-on experimentation which could be based on any number of the use cases (e.g., Demand Forecasting, Supply Optimization, Maintenance and Asset Management, etc.).


Use Cases Available to cover

 1. Demand Forecasting
●     Predictive Analytics: Utilizing AI to analyze historical and real-time data to predict future energy demands.
●     Anomaly Detection: Identifying unusual patterns that could indicate a problem or opportunity in energy consumption.

 2. Supply Optimization
●     Smart Grids: Implementing AI to optimize the distribution of energy in smart grids.
●     Renewable Energy Integration: Enhancing the integration of renewable energy sources like wind and solar into the grid.

 3. Maintenance and Asset Management
●     Predictive Maintenance: Using AI to predict when equipment will require maintenance or replacement.
●      Resource Allocation: Optimizing the allocation of resources and workforce for maintenance tasks.

 4. Sustainability and Compliance - Focus on Scope 3 management
●     Emission Tracking: Employing AI to track and manage greenhouse gas emissions.
●     Regulatory Compliance: Utilizing AI to ensure that operations comply with environmental regulations and standards.

 5. Security and Infrastructure Protection
●     Cybersecurity: Leveraging AI to protect the energy infrastructure from cyber threats.
●     Physical Security: Using AI for surveillance and monitoring of physical infrastructure.

 6. Logistics and Supply Chain Optimization
●     Route Optimization: Utilizing AI to optimize transportation routes for fuel and other energy supplies.
●      Inventory Management: Using AI to manage and optimize inventory levels of energy supplies.

 7. Emergency Response and Crisis Management
●     Disaster Prediction: Employing AI for predicting natural disasters that could affect the energy supply.
●     Crisis Response: Utilizing AI to optimize response strategies during emergencies.