By Erik Åsberg, Chief Technology Officer at eSmart Systems. eSmart Systems won the ‘Best SaaS Product for Energy / Utilities / Telecoms‘ category at The 2025 SaaS Awards.

The energy sector is in the middle of a profound transformation.

From renewable integration to climate resilience, utilities are being asked to deliver more with fewer resources and tighter budgets. But one of the most urgent challenges is not about technology or infrastructure, it is about people. A significant portion of the utility workforce is nearing retirement, and replacing decades of institutional knowledge is not simple. In this environment, AI-powered SaaS solutions are emerging as a lifeline, bridging the gap between experienced workers and a new generation of employees.

By combining AI, cloud-based intelligence, and intuitive interfaces, grid intelligence platforms empower utilities to maintain efficiency, safety, and reliability despite workforce challenges – by preserving the knowledge, insights, and best practices that have traditionally lived in the minds of veteran inspectors. This knowledge and insight is also accessible across all utility departments, supporting planning for inspections, maintenance, and investment strategies.

The looming workforce crisis in utilities

According to the U.S. Department of Energy, nearly 25% of the current utility workforce will be eligible for retirement within the next five years. Many of these employees are field inspectors, linemen, and engineers who have accumulated decades of operational knowledge about the power grid. When these workers retire, utilities face two significant challenges:

1. Knowledge drain – Critical insights about asset conditions, maintenance history, and local terrain are lost.
2. Skill gaps – New recruits, though often tech-savvy, lack hands-on experience with the complex realities of grid operations.

This workforce shift can lead to increased outages, slower response times, and higher operational costs if not addressed. For utilities to remain resilient, they need a way to capture and retain institutional knowledge while enabling less experienced employees to make informed decisions. This is where AI-powered SaaS comes in.

From manual inspections to intelligent digital twins

Traditionally, grid inspections required teams of workers traveling long distances, climbing towers, or using helicopters to visually assess infrastructure. These methods were time-consuming, expensive, and risky. Even when drone inspections began to replace some manual work, the resulting images and videos were often stored as isolated files or PDF reports, lacking the context needed for future planning.

Grid Vision® and similar platforms transform this model. By centralizing all inspection data in the cloud and layering AI-driven analytics on top, utilities create a dynamic, digital twin of their infrastructure. This digital twin does not just store images; it contextualizes them:

• Time tracking reveals how assets degrade over the years, not just between scheduled inspections.
• AI-powered defect detection automatically identifies defects and missing components, removing guesswork.
• Geospatial intelligence connects inspection data with environmental conditions like weather, terrain, or wildfire risk.

For new employees, this means they no longer need decades of personal experience to understand asset health. They can access a clear, data-driven view of every asset, complete with historical trends and AI-generated recommendations.

Knowledge retention through AI

One of the most powerful aspects of AI-powered SaaS is its ability to capture and retain knowledge that would otherwise walk out the door with retiring employees. Every defect detected, every image annotated, and every maintenance decision logged is stored and organized for future use. Over time, this creates a self-learning system that not only documents what was done but also improves its predictive capabilities.

For example, Evergy, one of the leading utilities in the U.S., has leveraged AI-powered inspections to reduce inspection time by 83% and streamline planning processes. With all historical data centralized, their teams can instantly compare current images to past inspections and spot trends that even the experienced human eye might miss.

Similarly, Xcel Energy identified 60% more defects compared to traditional methods by leveraging AI-driven image analysis. These insights are invaluable for training new employees and ensuring that nothing critical is overlooked.

Enhancing safety and job satisfaction

Workforce challenges are not just about knowledge loss; they also involve safety and employee retention. Field inspections are inherently risky, requiring workers to operate in hazardous conditions, from high-voltage lines to remote, weather-impacted regions.

AI-powered SaaS reduces the need for on-site inspections by enabling virtual inspections through drones and high-resolution cameras. Maintenance teams can review data safely from a central location, intervening only when physical repairs are necessary. This approach:

• Minimizes exposure to hazardous environments.
• Reduces physical strain, which can improve long-term job satisfaction.
• Allows experienced workers to focus on higher-value tasks like strategic planning and training.

RePower, for example, reported improved team morale after transitioning to AI-supported inspections. By automating data collection and analysis, they streamlined inspection processes, increased coverage, and reduced manual workload, allowing teams to concentrate on proactive maintenance planning.

Scalable intelligence for the next generation

The skills shortage in utilities is not a short-term issue; it is a structural challenge that will persist for years. AI-powered SaaS offers a scalable solution that grows with the utility’s needs. Whether it is expanding inspections to transformers, substations, or power plants, grid intelligence platforms provide a consistent, unified system of record for all asset health data.

Moreover, these platforms offer intuitive, query-based tools. A utility manager can simply draw a polygon on a map and ask, “Show me all high-risk wooden poles within this area.” The platform instantly surfaces relevant data, enabling informed decision-making without requiring specialized field experience.

Key benefits of AI-powered SaaS for workforce challenges

Accelerated onboarding: New employees gain instant access to comprehensive asset histories.

Guided decision-making: AI recommendations highlight the highest-priority tasks.

Lower OPEX: Automated defect detection reduces unnecessary field visits and emergency repairs.

Future-proofing: Data captured today continues to benefit the utility years into the future.

Case study insights

WEB Bonaire achieved a 28% reduction in CAIDI (Customer Average Interruption Duration Index) by improving outage management with AI-powered insights. This not only improved service reliability but also gave teams better tools for managing workload and prioritizing critical repairs.

Evergy accelerated inspection timelines from days to hours, freeing up skilled workers for strategic initiatives.

Xcel Energy found that AI-based inspections identified significantly more defects than manual methods, giving teams a stronger foundation for proactive maintenance.

These real-world results highlight how AI-powered SaaS solutions directly address both operational and workforce challenges.

Building the workforce of the future

While AI and SaaS platforms cannot fully replace the knowledge and intuition of experienced workers, they can augment human expertise in ways that were not possible even a decade ago. By creating a digital ecosystem where every inspection, repair, and observation is captured, utilities can ensure that future teams, no matter their size or experience, have access to the insights they need.

Training programs can also be enhanced with real-world examples drawn directly from the utility’s own data. New employees can review annotated images of past defects, learn from historical trends, and practice identifying high-risk areas, all within the context of the digital twin.

The bigger picture: AI, SaaS, and resilience

The workforce crisis is only one piece of the puzzle. Utilities also face increasing regulatory pressure, aging infrastructure, and the need to adapt to extreme weather events. AI-powered SaaS addresses these broader challenges by:

• Improving grid reliability through early fault detection.
• Reducing OPEX with automated inspections and predictive analytics.
• Supporting sustainability goals by minimizing unnecessary site visits and extending asset lifecycles.

Turning a challenge into an opportunity

The skills shortage in the utility sector is a serious challenge, but it also represents an opportunity for digital transformation. By investing in AI-powered SaaS, utilities can not only overcome immediate workforce gaps but also position themselves for a smarter, more resilient future.

Grid Vision® and similar platforms prove that the combination of AI and SaaS can unlock new levels of efficiency, safety, and strategic foresight. As the next generation of workers steps in, they will inherit not just a grid, but an intelligent, data-driven system designed for long-term success.