AI

Realizing the full potential of AI in utiltiies depends on a workforce empowered to capture high-quality data at every point of contact with the grid. By modernizing field workflows and prioritizing a human-in-the-loop approach, organizations establish the reliable data foundation necessary for long-term resilience and advanced automation.

AI data center power demands are reshaping how utilities plan, build, and maintain their electric grids and distribution systems. Faster development cycles, shifting load patterns, and new on-site assets create conditions that rely heavily on accurate, timely field intelligence. Utilities that adopt field-first workflows gain a clearer picture of evolving sites and a stronger foundation for decisions that support smart grid technology throughout each phase of AI-driven growth.

While AI can scale fault detection across rail networks, the process only succeeds when railway inspection crews confirm conditions on site. Crews verify each alert’s location and severity, capture photos, measurements, and GPS data, and document everything within structured workflows. Human-in-the-loop validation turns automated detection into actionable maintenance, cutting errors, reducing backlog, and keeping rail repairs aligned with real-world conditions. In addition, field verification keeps inspection data tied to actual track infrastructure and supports Federal Railroad Administration compliance requirements.

The landscape of utility field inspections is rapidly evolving. AI-powered UAVs (unmanned aerial vehicle), aka drones, are taking center stage, offering a safer, faster, and more efficient alternative to traditional ground-based methods. 

Infrastructure inspections have always been essential to maintaining the structures that connect and sustain modern society. These field inspections are critical for bridges, pipelines, power grids, and roadways, but they have traditionally been slow, expensive, and risky. Teams conducting inspections often rely on labor-intensive processes that involve scaling dangerous heights or working in hazardous environments. These methods are not only inefficient but often fail to capture the full picture needed for accurate maintenance planning.

Global electricity demand is projected to grow between 62% and 185 percent by 2050.  As our world becomes more electrified, new challenges threaten the reliability and stability of our power infrastructure.

As of September 2023, a staggering 30 percent of the United States finds itself grappling with moderate to severe drought conditions, signaling a distressing trend in climate patterns. This alarming development is not merely a temporary phase. In fact, experts from the UN Environmental Program have shifted away from using the term “droughts” to describe the current water scarcity issues plaguing the American West. They now refer to this persistent state of aridity as “the new, very dry normal,” a phrase that encapsulates the gravity of the situation and hints at a long-term transformation in the region’s climate. This change in terminology underscores the urgency of digital transformation in water utilities to adapt and prepare for a future where water resources might be scarcer and more precious than ever before.

Blurring faces in photos might sound simple, but it tackles a complex challenge: balancing data collection with privacy protection. Fulcrum’s AI-powered face blurring automates this process, addressing privacy concerns without slowing teams down.