Vision and Strategic Goals (by 2035)

Current Context: Pennsylvania is already an energy leader with one of the largest shale gas basins in the world, the second-largest nuclear fleet in the U.S., and growing renewable and clean energy assets. As AI increases demand for firm, reliable power, Pennsylvania has the chance to marry its energy strengths with AI-enabled solutions for grid management, energy efficiency, and system resiliency.

Deploying AI-enabled energy management at scale, including predictive analytics for grid operations, optimized siting for new generation, and next-generation demand response solutions, would position Pennsylvania as a global leader in energy/AI convergence. Early pilots tied to data centers could demonstrate feasibility and exportable expertise.

Key Metric: Percentage of Pennsylvania’s grid operations utilizing AI-enabled forecasting and management tools (with targets for adoption by PJM and utilities), and reductions in interconnection approval times or outage durations attributable to AI tools.

Current Context:  Pennsylvania is increasingly on the AI map. With seven R1 universities, the Pittsburgh Supercomputing Center, and a broad and deep network of other public and private higher education institutions spread throughout the state, considerable AI R&D already is taking place. The highest profile AI cluster is in the Pittsburgh region anchored by Carnegie Mellon University with notable private sector companies garnering national and global headlines and driving talent attraction. Philadelphia, with its burgeoning life sciences muscle, is accelerating the pace of medical discovery through applied AI. Pennsylvania’s state government was recently recognized by Code for America as one of the top 3 states for AI usage, training and capacity building in state government.

Shared, centralized R1 super-computing power to meet the extraordinarily significant data and capital requirements, along with shared research instruments, commercial cloud, experimental technologies, leveraging the national research computing and data ecosystem.

Key Metric: Growth in venture capital investment in Pennsylvania AI and advanced technology start-ups (tracked by Pitchbook/CB Insights), with 2x current levels by 2030. Supplement with tracking of technology licenses and spinouts from universities.

Current Context: Data centers and advanced manufacturing facilities require reliable, around-the-clock energy. PJM currently faces a tightening capacity market, with coal retirements and new load growth stressing the system. Pennsylvania has the resource mix to expand generation but faces permitting and interconnection bottlenecks.

Pennsylvania positions itself as the first state to demonstrate an “all-of-the-above” scalable model for firm power.

Key Metric: Total GW of new, firm capacity added in Pennsylvania dedicated to industrial and compute load, with a rolling target (e.g., 5–7 GW by 2030, adjusted annually for demand forecasts).

Current Context: Pennsylvania’s innovation economy is deeply regional. Pittsburgh anchors world leading expertise in AI, robotics, and advanced manufacturing while also building a burgeoning life sciences cluster connected to its health systems and research institutions. Philadelphia continues to expand its leadership in biotech, pharmaceuticals, and applied AI in life sciences, positioning the city as one of the nation’s fastest-growing health innovation hubs. State College and surrounding areas provide strength in materials science, agriculture, and energy research, while the northeast/Lehigh Valley, the northwest, anchored by Erie, and central Pennsylvania, bring resource-rich energy corridors and emerging tech manufacturing footprints.

Despite these assets, the commonwealth’s innovation economy remains uneven. Pennsylvania ranked 15th in the Milken Institute’s 2022 State Technology and Science Index, placing it in Tier 2 nationally. While the state performs strongly in research and risk capital inputs, it lags in technology talent density and tech sector concentration. By intentionally developing regional innovation corridors, Pennsylvania can connect these complementary strengths – energy, AI, robotics, and life sciences, while addressing gaps in talent and technology diffusion.

Create designated Regional AI Activation Corridors supported by “communities of practice” that integrate universities, health systems, advanced manufacturing, and energy development. By clustering and aligning investments across regions with a specific emphasis on AI adoption and R&D, these corridors can accelerate knowledge spillover, talent retention, and commercialization.

Key Metric: Net new jobs in AI, automation, and advanced technology occupations created within designated corridors, paired with median wage growth compared to statewide averages. Track corridor performance using Milken-aligned indicators:

• Tech Concentration and Dynamism (TCD): growth in high-tech and life sciences employment, startup formation, and regional business expansion.
• Technology and Science Workforce (TSW): increase in specialized STEM and health innovation occupations per capita within corridor regions.

Current Context: Pennsylvania’s grid faces aging infrastructure, a backlogged interconnection queue, and uneven permitting processes across municipalities. These barriers slow down both energy and data center development. To date, early signs of success are coming from the Pennsylvania Office of Transformation & Opportunity (PA OTO) through its PA Permit Fast Track Program. A specific example is Project Hazelnut, a 1,300-acre advanced technology campus featuring utility-grade server rooms, power distribution, cooling systems, and resilient network infrastructure, where PA OTO is streamlining interagency coordination and permitting timelines.

A statewide permitting overhaul tied to grid modernization, including bundled approvals, standardized local zoning templates, and AI-assisted permitting, that cuts project timelines by 30–50 percent compared to today.

Key Metric: Reduction in average interconnection and permitting timelines for major projects (measured in months), and percentage of new projects processed through standardized permitting pathways.

Current Context: Pennsylvania has a strong manufacturing base in transformers, switchgear, and other electrical equipment, but the majority of supply chains for advanced components still sit outside the state or abroad. The national transformer backlog underscores the need to localize production.

Launch of an AI Manufacturing Scaling Initiative that connects Pennsylvania’s small and mid-sized manufacturers to AI adoption tools and supply chain opportunities, allowing them to scale into suppliers for data center and grid infrastructure.

Key Metric: Percentage of total project spend on energy and data center infrastructure sourced from Pennsylvania-based firms, with a goal of reaching 20% by 2035.

Secondary Metric: Percentage increase in the number of enterprises in Pennsylvania adopting AI-enabled manufacturing processes to serve this market, with a goal of more than 150% by 2030 given the current rapid pace of AI adoption broadly.