AI in the Age of Energy Expansion | 9:00 am - 4:30 pm

Super Early Bird Rate: $1,499

(ends June 22)

Early Bird Rate: $1,799

(ends August 28)

Stardard Rate: $1,999

The rapid expansion of AI technologies has both promise and challenges. Enterprises are discovering new ways to use AI to enhance their capabilities, but utilities and power companies are rushing to revise growth plans to respond to surging electricity needs from AI data centers. Major tech companies are becoming key players in the power sector as they build their own data facilities and invest in AI infrastructure. At the same time, generative AI and other digital technologies hold the potential to transform how energy is produced, managed and consumed and to help energy systems become more efficient and sustainable.​

9:00 - 9:30 Welcome and Context

  • Overview of training objectives & outcomes
  • Introduction to S&P Global perspectives and methodologies
  • Review of data center basics
  • Data center typologies and what differentiates them: hyperscale, colocation, edge, AI-optimized sites

 

9:30 – 10:45 | Module 1: Growth of AI and its impact on enterprises

Session: How generative AI has been adopted by enterprises thus far

  • GenAI overview
  • GenAI adoption trends and use cases for enterprises of various sizes in various industries
  • Benefits and challenges of genAI adoption
  • Key GenAI players/models and how they are different from one another
  • Interactive discussion – impact of genAI on companies and their employees

 

10:45 – 11:15 | Break #1

 

11:15 – 12:30 | Module 2: Growth of AI and its impact on data centers

Session: How AI shapes compute, power, and cooling requirements

  • AI as the catalyst for a new wave of data center expansion
  • GPU clusters – compute density and energy requirements
  • Liquid cooling, high-density rack design, options for power (including hydrogen)
  • Current data center locations and plans for new builds
  • What determines data center location
  • AI training vs. inference workloads
  • Power access, grid interconnection
  • Impact of costs – power prices, taxes (and benefits), other costs
  • Impact of local resistance, regulations
  • Interactive discussion – impacts of AI infrastructure requirements on enterprises and their IT budgets

12:30 – 1:30 | Lunch Break

 

1:30 – 2:45 | Module 3: Energy ecosystem implications

Session: Powering the data center boom

  • Electricity demand growth vs electricity supply by ISO region
  • Data center energy usage profiles, efficiency improvements, AI’s use to improve grid operations
  • Behind-the-meter solutions, e.g., batteries, microgrids, gas/nuclear hybrids
  • Sustainability: renewables, PPAs, water usage
  •  Interactive discussion: mapping AI compute growth to regional grid stress

 

2:45 – 3:15 | Break #2

 

1:30 – 2:45 | Module 4: Costs to build AI infrastructure, funding, risks

Session: Costs to build AI, capital flows, risks, innovations

  • Costs for chips, IT equipment, data centers, power infrastructure
  • Investment/borrowing: public vs private capital, hyperscale investment trends
  • Risks: things that could impact AI/data center/energy demand forecasts
  • Quantum computing data center/power requirements
  • Innovations: AI modeling changes, modular data center builds, immersion cooling, flexibility/grid interaction

 

4:15 – 4:30 | Wrap-Up Discussion & Q&A

Session: What’s next for AI adoption and the energy–data center nexus

  • Recap of key takeaways
  • Open discussion: implications for attendees’ organizations