8:00 - 9:00 am
Agenda
Preliminary working agenda · Session times and participation subject to change
Wednesday, February 17
9:00 - 9:30 am
Opening Keynote: The Emergence of the AI Factory Economy
AI is rapidly evolving from a software capability into a new class of industrial-scale infrastructure, requiring unprecedented levels of compute density, power capacity, cooling performance, digital connectivity and capital investment.
- AI infrastructure growth trajectories
- Hyperscale and sovereign AI investment trends
- Industrialization of AI compute
- Implications for utilities, data centers and infrastructure investors
9:30 - 10:45 am
Session 1: Time-to-Power: Grid Interconnection, Utility Capacity and Large-Load Readiness
As AI factories drive massive new electricity demand, power availability and interconnection timelines are becoming decisive factors in where, when and how AI infrastructure can be deployed.
- Large-load interconnection challenges and timelines
- Utility planning for AI-driven electricity demand growth
- Transmission, substation and distribution capacity constraints
- Cost allocation, upgrade responsibility and utility-developer coordination
10:45 - 11:15 am
Networking Coffee Break
11:15 am - 12:15 pm
Session 2: AI Factories as Power-Intensive Infrastructure: What Makes Them Different
AI-native facilities differ from traditional hyperscale data centers in their power density, cooling requirements, redundancy needs, workload profiles and infrastructure design assumptions.
- Power-density requirements for training and inference environments
- Differences between AI factories and traditional hyperscale data centers
- Facility design implications of GPU-intensive workloads
- Reliability, redundancy and operating-continuity requirements
12:15 - 1:15 pm
Networking Lunch
1:15 - 2:30 pm
Session 3: Advanced Cooling Technologies for High-Density AI Compute
Rising rack densities and thermal loads are accelerating the move toward liquid cooling, immersion cooling and next-generation thermal management strategies for AI-ready facilities.
- Direct-to-chip liquid cooling architectures
- Immersion cooling developments and deployment considerations
- Thermal efficiency and heat-rejection strategies
- Retrofitting existing facilities for high-density AI workloads
2:30 - 3:00 pm
Networking Coffee Break
3:00 - 4:00 pm
Session 4: Electrical Design, Power Density and Compute Hardware Requirements for AI Campuses
The rapid evolution of GPUs, accelerators, networking systems and rack architectures is forcing data-center infrastructure teams to rethink electrical design, power distribution and facility flexibility.
- GPU and accelerator impacts on rack-level power requirements
- UPS, switchgear, transformer and power-distribution design
- High-speed networking and interconnect infrastructure requirements
- Planning for hardware refresh cycles and changing compute architectures
4:00 - 4:15 pm
Coffee Break
4:15 - 5:15 pm
Session 5: Site Selection, Real Estate and Regional Infrastructure Competition
Regions competing for AI factory investment must now demonstrate not only land, fiber and incentives, but credible access to scalable power, water, permitting pathways and long-term infrastructure support.
- Power availability as a primary site-selection driver
- Regional competition for AI campuses and large-load projects
- Permitting, tax incentives and infrastructure development timelines
- Fiber, water, workforce and community considerations
5:15 - 6:45 pm
Networking Reception
Thursday, February 18
8:00 - 9:00 am
Networking Breakfast
9:00 - 10:15 am
Session 6: AI Infrastructure Economics: Financing, Investment and Capacity Planning
The capital intensity of AI infrastructure is reshaping digital infrastructure finance, requiring new approaches to capacity planning, risk allocation, power contracting and long-term asset valuation.
- AI infrastructure investment and financing models
- Capacity planning amid uncertain AI workload growth
- Power availability and energy costs as valuation drivers
- Private capital, hyperscale investment and infrastructure risk
10:15 - 10:45 am
Networking Coffee Break
10:45 am - 12:00 pm
Session 7: Behind-the-Meter Power for AI Campuses: Gas, Storage, Solar, Fuel Cells and Hybrid Systems
As grid capacity becomes constrained, AI infrastructure developers are increasingly evaluating onsite and dedicated power strategies to improve speed, reliability, cost control and energy resilience.
- Onsite generation models for AI campuses and large-load customers
- Gas generation, fuel cells and bridge-power strategies
- Battery storage for resilience, peak management and grid support
- Hybrid power architectures and utility coordination
12:00 - 1:00 pm
Networking Lunch
1:00 - 2:15 pm
Session 8: Sustainable AI Infrastructure: Energy Efficiency, Water Use and Carbon Strategy
The rapid expansion of AI compute is intensifying scrutiny around energy consumption, water use, emissions, community impact and the sustainability metrics used to evaluate AI infrastructure growth.
- Energy-efficiency strategies for AI-ready facilities
- Water consumption, cooling tradeoffs and local resource constraints
- Carbon reduction, clean-energy procurement and 24/7 energy goals
- Sustainability reporting, regulatory expectations and public acceptance
2:15 - 2:45 pm
Networking Coffee Break
2:45 - 4:00 pm
Session 9: Grid-Responsive AI Factories: Flexible Compute, Automation and Next-Generation Architectures
The next generation of AI infrastructure may move beyond static power consumption toward more flexible, automated and grid-responsive operating models that better align compute workloads with energy availability and grid conditions.
- Flexible compute and workload orchestration
- AI-driven facility optimization and autonomous operations
- Data centers as responsive large loads and potential grid assets
- Modular, scalable and next-generation AI infrastructure architectures