Here’s what they have to say about this pivotal moment.
The AI-driven energy expansion is a once-in-a-generation opportunity to replace vulnerable, outdated infrastructure with inherently more secure, digitally-native systems. Technologies like advanced nuclear reactors, utility-scale batteries and inverter-based resources weren’t retrofitted for the digital age - they were built for it. That means they can deliver the abundant power AI requires while offering the adaptability and resilience our national security demands.
-- Harry Krejsa
Director of Studies, Washington Office Carnegie Mellon Institute for Strategy & Technology Pittsburgh brings the past, present and future together in exciting ways, especially at the intersecting frontiers of AI and energy. Our energy and manufacturing capabilities, brought together with our deep strengths in AI and computing at our universities and in our emerging entrepreneurial ecosystems, turbocharge the region’s ability to lead in clean energy innovation, to the benefit of our workers, communities and the nation. CMU’s Scott Institute for Energy Innovation Engineering and Public Policy Department are proudly engaged in campus and community-wide collaboration to realize this ambitious vision.
- Valerie Karplus
Professor, Engineering and Public Policy Courtesy Appointment, Heinz College Associate Director, Scott Institute for Energy Innovation Rapid AI-driven electricity demand is reshaping the power sector. Financing new generation will be challenging in a world of uncertain demand forecasts, with safeguards needed to avoid passing the costs of overbuilding onto consumers. At the same time, the grid is shifting from centralized plants and long-distance transmission to a decentralized model, with power increasingly co-located with major users like data centers and factories. This system will rely on a mix of technologies - from renewables and storage to gas, nuclear and geothermal - deployed based on how quickly they can meet rising demand. While this brings opportunities for resilience and sustainability, it demands updated regulations to accommodate new players and business models.
- Chris Telmer
Associate Professor, Tepper School of Business Breakthrough energy innovations often stall in university labs or early prototypes. If we want to lead in the global energy race, we must bridge the gap between invention and deployment and build the advanced energy systems this century demands. This is a defining moment for America’s energy future, and our ability to modernize the grid and secure critical infrastructure depends on deploying AI and robotics at speed and scale. These technologies are essential not only for improving efficiency and resilience but for reducing dependencies on foreign suppliers of vital components like transformers and grid sensors.
-- Jean-Francois Legault
Associate Director, National Robotics Engineering Center America’s economic and military power depends on reliable access to critical materials for energy storage, yet today the U.S. is highly reliant on high-risk locations, including military adversaries , for the extraction, refining, processing and manufacturing of these materials, posing significant risks to U.S. jobs and economic security. Meeting the government’s call to action , analyses by CMU’s Critical Technology Initiative shows that with the right reindustrialization policies, U.S. production costs can be competitive with China , and create good jobs for high-school educated workers. Our analyses chart a path forward for how domestic lithium extraction, materials recovery, strategic allied trade partnerships, workforce training, and investment in innovations in novel battery chemistries and extraction techniques can each be important components of an American reindustrialization strategy.
- Erica R.H. Fuchs
Director, Critical Technology Initiative Kavcic-Moura Professor, Engineering and Public Policy This moment in energy history is unique because AI will play a central role in accelerating the development, optimization and operation of our energy sources. Generative AI models now usefully represent and exploit the domain knowledge for these tasks while reinforcement learning and other discovery and control learning algorithms can now solve real-world problems much faster than the old human-only method of making technological progress. This will lead to a dramatic increase in both the total amount of energy produced, and the types and complexity of energy sources and distribution networks.
A great example of this is power from nuclear fusion. Progress toward this goal has been slow but steady for many decades. In my lab, we are using AI to develop better plasma controllers that can reach the higher temperatures and pressures needed for a financially viable fusion power plant. A process of discovery and improvement that would have taken decades using old methods, can now be done in years or even months using AI.
-- Jeff Schneider
Research Professor
The Robotics Institute
School of Computer Science
Buildings are the biggest energy users in the U.S., and AI offers a transformative way to make them more efficient. In my work, we are continuously monitoring complex HVAC systems and pairing AI with digital twins so we can detect faults, reduce waste and empower engineers to focus on higher-level problem-solving. AI won’t replace human expertise - it will serve as a smart apprentice, helping us make better, faster decisions, build better systems and operate them more efficiently.
- Burcu Akinci
Department Head and Hamerschlag University Professor Civil and Environmental Engineering As extreme weather grows more unpredictable, we can no longer treat long-term infrastructure upgrades and short-term emergency responses as separate challenges. They’re deeply connected - where and how we invest in stronger infrastructure today will shape how effectively we can respond to outages tomorrow. That’s why we’re developing a sophisticated planning framework that coordinates long-term investments, like hardening power lines, with short-term emergency actions, like dispatching repair crews. Smarter, integrated planning will help make our power grids faster to recover and more resilient when the next storm hits.
- Shixiang Zhu
Assistant Professor of Data Analytics
Heinz College of Information Systems and Public Policy
