Summary
With 40 percent of the power industry workforce retirement-eligible by decade’s end and grid demand surging from data centers and EV charging, utilities face a widening inspection gap at aging Tier 2 and Tier 3 substations that manual inspection alone cannot close. Automated visual inspection, using fixed cameras, drones, and AI-powered analysis, shifts the inspector’s role from site visits to desk-based review of structured findings, maintaining coverage as experienced field staff retire.
Think about the best field inspector you know. The one who can walk into a substation and catch something subtle: a faint discoloration on a bushing, a gauge that’s reading slightly off, a vibration that doesn’t sound quite right. That person carries something you can’t put in a training manual: decades of pattern recognition built from thousands of hours in the field.
Now consider what happens when that person retires.
It’s not a hypothetical. The U.S. Department of Energy projects that roughly 40 percent of the power industry workforce will be retirement-eligible by the end of this decade. That’s a structural problem, and it’s arriving at precisely the wrong moment.
More Grid. Fewer People. Higher Stakes.
While experienced inspectors are leaving the industry, the demands being placed on the grid are accelerating in ways that would have been hard to predict even five years ago.
Commercial data centers and residential EV charging are competing for grid capacity that is already under significant strain. Analysts project that data centers alone could account for more than half of all peak load growth over the next five years, roughly 90 gigawatts of new demand. EV charging is expected to represent nearly five percent of total U.S. power demand by 2030. The infrastructure serving all of this load was largely built forty, fifty, or sixty years ago, for a grid that looked nothing like today’s.
The American Society of Civil Engineers recently gave U.S. energy infrastructure a C-minus grade. That’s a warning.
Put simply: there is more to inspect, with fewer people to inspect it, at higher consequence if something slips through.
The Limits of Manual Inspection
Manual inspection has served the industry well. But it has always carried limitations that are easy to overlook when experienced inspectors are plentiful.
Inspection findings are inherently variable. They depend on the inspector’s experience, the lighting conditions at the site, access angles, and the discipline with which documentation is recorded. Two inspectors can examine the same asset on the same day and return different findings. That variability makes trend analysis unreliable and creates blind spots in even the most conscientious inspection programs. Research suggests that even the best human inspectors, working in pairs, will miss a meaningful fraction of real defects.
Frequency matters too but increasing inspection frequency doesn’t solve a workforce shortage. You can’t schedule your way around a staffing problem.
The inspection gap is widest and the consequences most acute in Tier 2 and Tier 3 substations: the mid-level and lower-priority sites that may see a qualified inspector only once or twice a year, despite carrying meaningful load and aging equipment. These are also the sites where a slow-developing fault is most likely to go undetected until it becomes an emergency.
A Different Approach to the Same Problem
Automated visual inspection doesn’t replace the judgment of an experienced inspector. It changes what that inspector is asked to do.
Rather than driving to a substation, walking the yard, and manually documenting what they find, an inspector using an automated system reviews structured findings from a desk: historical images with anomalies flagged for attention, asset condition data organized into an actionable interface. The experienced eye is still in the loop. The difference is that it’s being applied where it’s most needed, rather than being consumed by the logistics of getting to the site.
Fixed cameras, drones, and ground-based robots each play a role in how that visual data gets collected. Artificial intelligence is what makes the analysis scalable. And the combination, properly designed and honestly evaluated, can meaningfully close the inspection gap that’s opening as the workforce transitions.
None of this is an easy button. Vendor claims in this space often outpace what the technology can reliably deliver today. The utilities that will benefit most are the ones that understand both the genuine promise of automated inspection and its real current limitations, and who work with partners willing to be straight about the difference.
The Conversation Worth Having Now
The workforce transition in the power industry is already underway. The load growth is already happening. The substations aging out of their design envelope are already carrying more than they were built for.
Automated visual inspection won’t solve every part of that problem. But it addresses the part that’s hardest to solve any other way: how do you maintain inspection coverage as the people who have always provided it begin to retire?
Systems With Intelligence’s new white paper, The Promise of Automated Inspection in Electric Utilities, examines this question in full, covering the technology options, the AI models behind visual analysis, the business case for deployment, and the practical questions any utility should be asking before it begins. If your organization is thinking about how to protect inspection coverage over the next decade, it’s the right place to start.