IFS Survey Finds Utilities Prioritize Grid Resilience and AI
IFS says utilities are shifting investment toward grid resilience, reliability, affordability and operational performance in a press release describing research conducted by Censuswide. The survey covered 850 C level and senior utility executives.
The research found that 26% of utilities are reevaluating asset portfolios to prioritize existing grid infrastructure. It also found that 57% of utility leaders consider AI critical for reducing operating costs, while 47% see it as critical for improving asset performance and managing demand growth from electrification.
Operational data silos constrain 49% of surveyed organizations. Only 33% describe their asset lifecycle management capabilities as advanced, while 51% use asset management systems with limited predictive capabilities that operate in silos.
Utilities are also considering battery energy storage and distributed energy resource management systems to handle demand volatility and prolonged outages. Among respondents, 22% expect advanced geothermal energy to have the greatest long term impact on continuous clean baseload power, while 18% selected small modular reactors. Another 46% consider AI critical for accelerating the integration of renewable and distributed energy.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Sep 24 Leviton Plans $100 Million Network Manufacturing Expansion Sep 24 Synteq Digital Opens Chicago GPU Infrastructure Site Sep 24 STL Adds Fiber Trunk Assemblies for AI Data Centers Sep 24 Canaan to Show Bitcoin Mining Heat Systems at BTCHEL Sep 24 Energy Disruptors: UNITE 2026 to Examine AI Power Demand in CalgarySilicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
ABB and BCG Report Backs Hybrid AC/DC Power for AI Data Centers
Schneider Electric Says AI Can Cut Building Energy Use by Up to 22%
Huawei Unveils Grid Interactive AI Data Center Solution
Huawei and Partners Launch Grid Forming and AI Initiative
DIMAAG-AI and Toshiba Develop Battery Storage for AI Data Centers
Daily AI Brief: the AI news that matters, in your inbox.