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Tech groups: New Jersey can win AI 'inference' work if it modernizes grid planning and incentivizes efficient data centers
Summary
Industry witnesses urged the legislature to focus on attracting AI inference data centers close to users, enforce data‑center efficiency standards and invest in AI‑driven grid tools, arguing New Jersey can capture economic gains without hosting the energy‑intensive training clusters.
Representatives of New Jersey’s technology sector told senators that the state can still capture significant economic value from the AI economy by targeting incentives and infrastructure for inference‑focused data centers and startup ecosystems.
Aaron Price, CEO of TechInet (as introduced), told the committee that inference facilities—those that serve real‑time end‑user requests—benefit from geographic proximity to customers and are a better fit for New Jersey than energy‑heavy training campuses that typically locate in low‑cost regions. Price and other witnesses proposed four near‑term steps: invest in AI‑optimized smart‑grid software and controls, offer targeted energy incentives for startups and growth companies, pursue public‑grid partnerships for AI and energy research, and fund community education on the economic trade‑offs.
Justin of Better Future Labs explained the energy lifecycle for AI systems—pre‑training, training and inference—and said training centers (with very large GPU clusters) are likely to locate where land and power are cheapest, but inference centers can be competitive in New Jersey because of latency advantages. Brian Klingbeil of Insono urged consolidation of inefficient legacy data centers and adoption of minimum PUE (power usage effectiveness) standards as a way to cut overall demand without sacrificing cloud services.
Industry witnesses also said AI itself can help reduce load growth by optimizing operations, and they offered to supply case studies and technical recommendations to the committee. Lawmakers asked for specific examples and data to support claims about consolidation and energy savings; panelists agreed to follow up with documented cases and contact lists.
