14 Oct From GIS to Network Intelligence: How AI Is Transforming Utility Operations

 

When Utility Networks Do More Than “See”—They Can “Understand, Analyze, and Help Make Decisions”

Utilities are facing increasingly complex challenges at the same time—from managing vast numbers of assets and highly interconnected networks to handling growing volumes of field and sensor data, while meeting customer expectations for faster and more accurate services. The key question is no longer simply where an organization’s data resides, but how that data can be turned into actionable decisions.

The concept of AI-Powered Network Intelligence is taking GIS beyond its traditional role as a mapping system and into a platform that helps utilities understand network conditions, analyze relationships between assets, anticipate risks, and support workflows from the office to the field. By integrating AI into these systems, utilities can make data access, analysis, and decision-making more efficient.

 

Powering Smarter Utility Operations with AI

In the context of Geospatial AI, AI applications can be viewed through three approaches that work together: AI Tools and Models, AI Assistants, and Agentic AI, with GIS and Utility Network providing the foundation for spatial data and the relationships that define the network.

 

AI Tools and Models

AI Tools and Models can analyze data, imagery, and spatial patterns—for example, detecting trees encroaching on power lines, analyzing assets from imagery or LiDAR data, identifying Solar Rooftop opportunities, and assessing the condition or age of equipment.

These capabilities help utilities process large volumes of data and prioritize the areas or assets that should be inspected first.

 

AI Assistants

AI Assistants make it easier for users to work through natural language. Examples include generating surveys from user descriptions and analyzing imagery, text, or audio in certain workflows.

This can reduce the amount of manual data entry and support field data collection, allowing field teams to work more efficiently.

 

Agentic AI

Agentic AI connects user questions with data, tools, and GIS capabilities. A properly designed system can interpret a question, select the relevant data or tools, and carry out the appropriate workflow to produce an answer that meets the user’s needs.

For utilities, these capabilities become even more powerful when combined with Utility Network, which models the components and relationships within a system—including equipment, power lines, pipes, valves, and circuits—and analyzes network connectivity based on network conditions.

This gives AI the network context it needs to support utility operations and decision-making.

 

 

AI-Powered Utility Operations: From Risk Detection to Network Analysis

When AI works together with geospatial data and Utility Network, it can enhance utility operations across a range of activities—from risk analysis and field operations to accessing and analyzing network information through natural language. There are three key approaches:

 

Spot Risks Before They Become Disruptions

Aerial imagery, survey imagery, LiDAR data, and asset information can be analyzed with AI to identify and prioritize areas or assets that require attention. Examples include detecting trees that may encroach on power lines and analyzing buildings and rooftops to assess their potential for Solar Rooftop deployment.

These approaches allow utilities to move beyond manually reviewing large volumes of data across every location. Instead, AI can help identify areas with potential risks or opportunities, enabling teams to focus inspections and actions where they matter most.

 

Smarter Field Operations, Powered by AI

Many utility workflows begin with field data collection, whether it involves recording asset information, surveying an area, or capturing operational details. Tools such as ArcGIS Survey123 enable field crews to collect data both online and offline, while connecting that information back to the GIS.

When AI capabilities—such as survey generation and the analysis of imagery, text, or audio in certain workflows—are integrated into the process, they can reduce manual data entry and save time. This allows field personnel to focus more on verifying information and carrying out their work in the field.

 

From Searching Maps to Asking the Network

A key shift enabled by Agentic AI is that users can start with a business question without needing to know where a particular GIS tool is located within the system.

AI can interpret the question, select the relevant data or tools, and return results as lists, counts, details, or highlights on a map.

When combined with Utility Network, this capability becomes even more valuable. Network data includes more than the location of individual assets—it also captures the connections and relationships between network components. This allows users to ask questions directly in the language of utility operations, such as:

• “Where is transformer TR-XX located?”
• “Which transformer supplies power to this meter?”
• “If this transformer fails, how many customers will be affected?”

 

Behind this seemingly simple experience is a workflow that connects Agentic AI with GIS and Utility Network. This enables AI to connect user questions with the appropriate network data and analysis. To work effectively, AI, data, and GIS workflows must be designed to work together in alignment with utility processes.

 

 

3 Use Cases Combining Agentic AI and Utility Network

When Agentic AI works together with Utility Network, users can move beyond simply finding information to analyzing network connectivity and answering business questions more easily.

 

Asset Discovery: Find the Right Assets, Faster

Search for assets using an Asset ID or attributes such as equipment type, installation year, or other specified criteria, then display their location and details on the map. This provides faster access to asset information.

 

Network Connectivity: Understand How the Network Is Connected

Analyze the connectivity and paths between network components such as meters, transformers, and circuit breakers to understand how individual assets are connected and how the network flows.

 

Affected Customer: Know Who Will Be Impacted

When an outage occurs or part of the network is isolated, analysis can identify the equipment or customers that may be affected. This information can support repair planning, outage management, and more effective customer communication.

 

Behind Every Simple AI Experience Is Network-Ready Data

AI can deliver greater value when it works with high-quality data and a well-structured information model. For utilities, data is not limited to the location of an asset. It also includes the details, relationships, and connections between components across the network.

Utility Network helps manage these structures and relationships while supporting connectivity analysis and network validation. This allows AI to use network data as context when analyzing information and answering questions.

In the example architecture, Agentic AI connects user questions to the relevant data and workflows, while ArcGIS Enterprise provides GIS data and capabilities, including Utility Network and the network analysis patterns prepared for use.

Therefore, being “AI Ready” is not simply about having AI or an LLM. It requires the right data, network structure, and GIS services that AI can use as context.

Together, these elements enable utilities to access information faster, analyze situations more easily, and use data to support planning, operations, and business decision-making more effectively.

 

 

 

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