“Virtually all utility providers currently use manually operated drones and/or basic GPS-based automated flights to collect data via drone service providers or in-house programs, but manual data capture is not the ideal solution for scalability,” added Kabe Termes, director of solutions engineering for Skydio, of Redwood City, California. “Training requirements for operators are high, flight efficiency can be low [especially with pilots who do not regularly fly] and data review is tedious.”

Termes believes more widespread adoption of drones will be driven by improved flight autonomy, AI analytics and regulatory pathways that allow for remote operations. “Any time you can relieve the operator of spending any mental collateral on functions such as preventing collisions, they can spend more time focusing on the mission at hand,” Termes said.

Automated drones and AI analytics make the collection of detailed data more efficient, consistent and rapid. And while the operator/pilot is still present, data can be collected to build a safety case for automated drone inspections without the direct oversight of a human operator/pilot.