GE Vernova Electrification Software Named a Leader for its Purpose-Built Industrial AI Offerings in the Energy Sector

GE Vernova’s Electrification Software business is focused on delivering AI-enabled applications and insights needed to accelerate electrification and decarbonization across the entire energy ecosystem – from how it’s created and how it’s orchestrated to how it’s consumed.

In the inaugural Verdantix report, “Green Quadrant: Industrial AI Analytics Software,” (September 2025), the independent industry analyst firm ranked GE Vernova a “Leader.” Verdantix ranks software providers in this report based on:

Based on these criteria, GE Vernova garnered strong scores across focus areas illustrating proven differentiation as an energy-first data and AI company that delivers defined AI use cases as part of core offerings. For GE Vernova, this report includes Electrification Software business solutions such as Meridium APM, SmartSignal, CERius, GridOS® Orchestration Software, and Proficy software alongside GE Vernova’s overall AI strategy and outlook.

In the following blog, I highlight how GE Vernova’s Electrification Software business offers a differentiated energy-first delivery of AI that turns industrial data into actionable insights. GE Vernova’s software has the ability to ingest and transform data, deploy machine learning (ML) models, and expand to artificial intelligence (AI) use cases; and the company is developing Generative and Agentic AI products to increase customer efficiency.

GE Vernova continues its strong focus on MLOps and AIOps capabilities, such as the GridOS Data Fabric and its Essentials platform with the goal of providing AI with a vertical focus—rather than a horizontal ‘general’ AI play. Today, GE Vernova’s Electrification Software business unites assets, workflows and insights.

With significant industry experience from more than 7,000 gas turbines deployed globally, 400+ GW of renewables, working with 90% of oil & gas super majors, and 90% of the world’s transmission utilities being equipped with GE Vernova hardware, GE Vernova has proven ability in delivering meaningful outcomes. With this focus, GE Vernova provides deep domain-based AI insights that many others cannot.

Due to extensive energy industry expertise, GE Vernova’s Electrification Software business focuses on anticipating and addressing customers’ evolving needs that will require AI to unlock advanced insights and capabilities.

Let’s explore current and future AI capabilities in GE Vernova’s software applications. GE Vernova excels in several key areas, delivering AI-enabled solutions packaged as operational workflows rather than just model toolkits:

GridOS applications that deploy AI/ML:
1. GridOS Forecasting:

2. GridOS Disruption Prepare:

3. GridOS Visual Intelligence:

GE Vernova is actively developing a range of AI capabilities through its Grid Software Advanced Technology Organization:

Essentials (SaaS platform):

Meridium APM & SmartSignal:

Optimizers:

Proficy CSense:

Proficy Data Hub (COMING SOON):

Proficy Smart Factory:

GE Vernova’s Electrification Software business provides a wide-range of AI offerings that support the ability to automate workflows and build and train models for use-case specific tasks.

GE Vernova’s Electrification Software business excels in its ability to capture and leverage data from various sources to build, deploy, and manage AI use cases.

GE Vernova’s Electrification software maintains a bold vision for the future of AI in the industrial sector that’s rooted in customer needs and collaboration. Below are some of the areas where GE Vernova sees AI going in the short and long-term:

1. Embedded and Context-Aware Intelligence

The future of industrial software will be characterized by deeply embedded, context-aware, and continuously learning intelligence. AI will transition from being a supplementary capability to becoming the essential connective tissue that unifies various systems and processes.

2. AI in Grid Software

As the electrical grid evolves into a dynamic, multi-directional system integrating renewables, storage, and distributed generation, AI will play a foundational role in real-time orchestration, prediction, and self-healing.

• Grid Stability & Flexibility:
o AI models will predict grid stress, optimize dispatch, and dynamically rebalance load, enabling utilities to manage complexity without compromising reliability.

• Autonomous Grid Control:
o Reinforcement learning and predictive optimization will drive real-time decisions that adapt to volatility from renewables, weather, and demand shifts.

• AI for Planning & Investment:
o Generative AI will simulate long-term scenarios, accelerating network planning and grid modernization decisions with data-driven foresight.

3. AI in APM: The Intelligent Asset Network

AI will transform Meridium APM from a predictive tool into a collaborative intelligence layer that connects people, assets, and data across the enterprise.

• Unified Asset Intelligence:
o Advanced models will blend structured sensor data, unstructured maintenance logs, and visual inputs into a single asset health narrative.

• Prescriptive & Generative AI:
o Beyond predicting failure, AI will recommend optimized interventions, simulate outcomes, and support engineers with generative insights tailored to their operating context.

• Connected Enterprise:
o Meridium APM will expand beyond single-site reliability into a networked enterprise capability—learning from every asset, across every region—to continuously improve performance, sustainability, and cost efficiency.

4. AI in Historian & Manufacturing Software

Historian and manufacturing systems will evolve from data repositories to intelligent insight engines that power closed-loop optimization across operations.

• AI-Enabled Proficy Historian:
o In the 2026 release of Proficy Historian, AI will encompass configuration, query generation, and metric building. For example, if you ask Proficy Historian a question about your data, it will build out the query for you.

The integration of AI into industrial software is set to revolutionize how we manage and optimize complex systems. From grid software to asset performance management and historian systems, AI will provide the intelligence needed to achieve greater efficiency, reliability, and adaptability. As we move forward, the focus will be on creating deeply embedded, context-aware solutions that continuously learn and adapt to the evolving landscape of industrial operations.