AI Fieldwork

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.

The first wave of utility digitization is over; the new executive mandate is to get predictive. Fulfilling that mandate requires a new breed of field technology built on three pillars: active intelligence at the point of capture, seamless enterprise integration, and immediate operational insight driven by modern data analytics and artificial intelligence. The combination of the three pillars creates a resilient operational model, helping utilities manage grid complexity and adopt smart grid technologies. It also supports the shift from reactive responses to predictive operations.”

Modern construction sites face constant, high-pressure risk, yet most safety systems still lag behind. AI, robotics, and site cameras now give field teams faster visibility, tighter coordination, and a better shot at preventing injuries before they happen.

GeoAI combines artificial intelligence with geospatial data in a deep learning model to help field teams work faster, make better decisions, and stay ahead of operational challenges. This blog explains how GeoAI evolved, what it enables today, and how it’s reshaping asset management, risk detection, and resource planning across industries. It also explores practical considerations like implementation, data security, and future trends including IoT integration and adaptive machine learning.

Manual inspections in manufacturing slow down production, introduce inconsistency, and make it harder to catch defects early. AI-driven inspections offer real-time visibility, faster detection, and a structured path toward higher quality at scale.

Fulcrum Audio FastFill is transforming how field teams collect data, offering faster, hands-free workflows through AI-powered voice input. Before this feature became widely available, early adopters were already putting it to the test on their custom Fulcrum apps. Their feedback has given us valuable insights into how organizations can optimize their forms and workflows for this game-changing tool.

Fulcrum Audio FastFill is a voice-powered AI feature that replaces manual typing with real-time, structured voice dictation for field data capture. It solves common problems in the field by turning spoken input into accurate records, helping teams move faster and stay focused on their work.

Energy keeps the world running, but keeping energy systems running has never been more complex. Demand is rising, infrastructure is aging, and the push for lower emissions is reshaping how power is generated and delivered. At the same time, supply chains are strained, regulations are tightening, and skilled labor shortages make efficiency more critical than ever. The energy industry is in the middle of a digital transformation for fieldwork, with new technologies reshaping how field teams operate and respond to these challenges.

The architecture, engineering, and construction (AEC) industry faces unique challenges: complex projects, tight deadlines, and ever-increasing client demands. But a digital revolution is underway, offering solutions to these challenges and reshaping how we design, build, and manage the world around us. This transformation is leading to a fundamental rethinking of workflows, collaboration, and the very nature of construction itself. To understand why, let’s explore the forces driving this digital revolution and how it’s changing the AEC landscape.

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. 

The utility industry is at a crossroads. Energy demand is rising, but the skilled workforce needed to maintain the grid is shrinking. Much of the infrastructure is decades old and increasingly prone to issues, while extreme weather and tighter regulations add even more pressure. Transmission and distribution (T&D) field teams, tasked with keeping everything running, are being stretched thin. Artificial intelligence (AI) is providing a path forward. Advances in AI in utilities are modernizing how utilities handle inspections, maintenance, and field operations, AI is helping teams work smarter, faster, and safer. This blog dives into how AI is transforming T&D field strategies to boost grid reliability, streamline tasks, and even reshape the future of fieldwork.

Reinforced concrete inspections are tough work. Inspectors squint at cracks, measure with gauges, jot down notes, and hope their instincts hit the mark. It’s slow, inconsistent, and overdue for an upgrade. With aging infrastructure presenting growing challenges, traditional visual assessments alone don’t cut it.

Preventive maintenance is a cornerstone of asset management, and for many organizations, integrating AI into their maintenance programs seems like a no-brainer. Yet, while businesses race to harness AI’s analytical power, they’re often overlooking a critical factor: their data. In fact, many teams are falling into a common trap—focusing on AI’s potential without addressing the data quality issues that undermine its effectiveness.

Greetings, everyone. Today, I’m thrilled to share an important step forward for Fulcrum, one that brings to life our vision of enabling field efficiency and unifying the field with the office. 

AI-driven field data collection makes fieldwork smoother, faster, and error-free. With modern tools at their fingertips, field teams now capture real-time insights and act on data directly in the field. Industries like utilities, engineering, telecom, and environmental management are getting actionable information on the spot, cutting out delays and transforming raw data into instant solutions.

The fieldwork landscape is changing fast, evolving from outdated manual processes into a domain driven by AI-powered solutions. What used to be a slow, error-filled, paper-based process has evolved into a system driven by digital precision, efficiency, and real-time decision-making. As the leap from paper to tech, and now to field AI, transforms how on-site operations are conducted, the result is not just faster processes, but smarter, more reliable workflows.

If you’re not quite on board with the idea of practical AI, you’re not alone. Between generating nightmare images of uncanny valley mutants with too many (and too bendy) fingers and news stories of AI missteps and hallucinations, it’s easy to dismiss AI as another tech novelty. 

The integration of artificial intelligence (AI) with remote sensing technologies is transforming groundwater monitoring, providing unparalleled insights into water quality across extensive geographical areas. This innovative approach is particularly beneficial for water utility and field operations teams looking to enhance their monitoring and management capabilities.

AI is transforming utility maintenance by predicting failures before they happen, slashing downtime and unnecessary costs. With smart integration of IoT sensors and real-time analytics, utilities can now catch issues early and plan targeted fixes. This blog unpacks how AI-driven predictive maintenance reshapes grid reliability, energy efficiency, and long-term infrastructure health.

FieldTech refers to the integrated hardware and software systems that support field operations in demanding, remote, or regulated environments. From drones and sensors to AI-powered platforms and offline data sync, FieldTech helps field teams capture accurate data, reduce inefficiencies, and bridge the gap between the field and the office. As industries push for greater efficiency, safety, and compliance, FieldTech continues to evolve as a critical part of modern operations.

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.