A Center of Excellence Approach with GE Vernova’s Asset Performance Management Software

As energy enterprises embrace digital transformation, Centers of Excellence (CoEs) and centralized IT teams can lead standardizing asset management, IT infrastructure, and operational efficiencies. Modern Asset Performance Management (APM) platforms provide a foundation for enterprise-wide visibility, automation, and predictive analytics, integrating:

Energy companies may utilize CoEs to centralize expertise in technologies like AI, data analytics, and customer experience. They aim to rapidly develop and deploy solutions across their operations, improve efficiency, manage costs, and stay ahead in the evolving energy landscape. This often includes dedicated teams focusing on specific areas like data integration and cyber security with the goal to share best practices across the organization.

A few examples of energy organizations working to develop CoEs for the enterprise are:

The benefits include:

By leveraging Asset Performance Management software within a CoE framework, enterprises can reduce maintenance costs, enhance operational efficiency, and improve asset reliability at scale.

Digital CoEs act as a centralized hub for enterprise-wide innovation, helping organizations in how they:

Asset Performance Management solutions can help Digital CoEs unify asset data, streamline workflows, and implement AI-driven decision-making across the enterprise.

Traditional asset management systems often operate in silos, limiting visibility and responsiveness. APM platforms through using microservices and APIs solve this by:

Example: An energy company integrates APM alerts into its IT Service Management (ITSM) system, automating maintenance request creation based on real-time asset health data.

AI/ML models enhance Asset Performance Management platforms by:

One of the biggest challenges in asset management is the vast amount of unstructured data, such as technician maintenance logs, engineering reports, equipment manuals, and more.

Generative AI transforms this unstructured data into actionable insights by:

Computer vision enhances asset performance monitoring by automating inspections through:

Enterprises with in-house data science teams or third-party analytics tools need flexibility in applying custom models to asset data. APM platforms support BYOA by:

GE Vernova’s APM suite is designed to help energy enterprises increase asset reliability, reduce maintenance costs, and improve operational efficiency at scale. With a cloud-ready, microservice architecture, APIs / Connectors, and AI/ML for multiple use cases, APM may help centralized IT teams and Digital Centers of Excellence (CoEs) unify data across systems, streamline workflows, and predict asset failures before they occur.

As an emerging focus for GE Vernova’s APM, Generative AI is being investigated for the proper use cases to synthesize both structured and unstructured data—such as sensor readings, maintenance logs, and engineering documents—turning it into actionable insights.

Integrated computer vision models further enhance inspections, while BYOA capabilities allow organizations to apply custom models into the microservice-based architecture. By providing enterprise-wide visibility, flexibility, and scalability, GE Vernova’s APM helps energy companies reduce downtime, increase asset performance, and support long-term operational resilience.

As energy enterprises shift toward digitally driven, AI-enabled asset management, GE Vernova’s APM platforms provide the foundation for scalable, efficient, and cost-effective operations. Digital Centers of Excellence and enterprise IT teams are uniquely positioned to drive this transformation by adopting GE Vernova’s APM as a centralized intelligence hub, enterprises can feel more confident in long-term asset performance, cost savings, and operational resilience.