Utilities Embrace Network Automation
Energy companies have been expanding their enterprise networks, so they support more remote workers and work sites. One ripple effect is the maintenance burden for internal technology teams rises. New artificial intelligence capabilities enable utilities to offload routine maintenance work from their staff to intelligent network management solutions.
Energy companies have been embracing work at home models, so employees spend more of the workday out of the office. Network loads increase as more employees work remotely. Furthermore, energy businesses have lots of complex remote infrastructure that needs to be maintained. They are deploying intelligent Internet of Things (IoT) devices to gain visibility into equipment performance, which also increases network traffic.
AI Automates Network Maintenance Functions
As the traffic load grows, energy companies want to limit the amount of work that technicians need to complete. New generative artificial intelligence and machine learning solutions, exemplified by ChatGPT, offer them the ability to automate manual tasks.
For instance, they can centralize and orchestrate network Lifecycle Management (LCM) functions, like setting user authorizations and assigning network addresses. Also, Intelligent Disaster Recovery (DR) solutions, which often rely on digital twin technology, enable energy enterprises to restore services quickly if an outage occurs.
intelligent Operations and Maintenance (O&M) capabilities provide energy companies with more insights into fault identification. Traditionally, network functions were split among the network equipment layer, the network hardware, and system software. As a result, troubleshooting was challenging because a great deal of information had to be correlated. AI associates information faster and more accurately than humans.
While the new features can be quite helpful, they present energy companies with challenges. The technology is new. Consequently, the solutions may work in theory but break down when implemented. So, integrating these capabilities into existing network infrastructure can be daunting.
Also, energy corporations lack experience with the tools. Therefore, they must put processes in place to train staff.
Energy companies are extending their enterprise networks, which means more work for the technology support team. Vendors are using AI to automate more of the traditional manual work. However, energy companies need to put checks in place to ensure that their staff understands how to take advantage of the new features.