PwC accelerates utility network migration with >90% automated error resolution

Utility companies rely on accurate Geographic Information System (GIS) data to keep the lights on: mapping infrastructure, planning maintenance, and responding to outages. But migrating that data from legacy systems onto Esri's ArcGIS Utility Network, which many utilities use to manage grid infrastructure, often surfaces a wave of data errors that have accumulated for years. With 100k to 1 million errors to resolve, manual fix-by-fix remediation can be slow, inconsistent, and depends on specialized GIS professionals, making the process difficult to scale. Costs and schedule risks can quickly escalate.

PwC's new GIS Data Remediation solution can help change that. It's a modular AI pipeline organized in four stages: detect validation errors, smart resolve (identify spatial and data patterns, recommend explainable fixes), generate deploy-ready remediation code, then validate and document the changes, with a person approving each fix before it touches the data.

Why it matters for clients

For utility clients undertaking a GIS migration, the solution changes what used to be a slow, manual slog into a scalable, governed process: 

• Faster migrations. Manual error remediation takes 10–12 minutes per error today. PwC’s solution can handle each error in 1–2 minutes, saving 70–80% of remediation time. For utilities facing 100k to 1 million errors, that's the difference between months of work and weeks. Automating error diagnosis and remediation removes the biggest bottleneck in a typical utility network migration, helping reduce the time spent on manual, case-by-case review.

• Confidence in the data. A governed, human-approved workflow means each fix is reviewed before it's applied, so clients get the speed of automation without losing oversight of their data.

• Errors caught at scale. Instead of relying on specialized GIS staff to find and fix issues one at a time, the solution automates the process, helping reduce effort and dependency on hard-to-find GIS professionals.

PwC's solution can achieve an >90% solve rate on validation errors, with deployment to client environments underway and a target of over 90% accuracy at client go-live. 

What sets this apart

This solution is purpose-built for Esri's ArcGIS Utility Network migration. Unlike rules-based or generic data-quality solution, it combines agentic pattern recognition with fix caching and human-in-the-loop governance, automatically identifying spatial and data relationships that cause errors, learning from previously-applied fixes, and keeping an audit trail of each remediation before approval.

Built for utilities at scale

GIS data problems don't stay small. As utility networks grow and systems change hands, the volume of errors compounds, and manual review becomes less realistic each year. Utilities migrating 100k to 1 million errors can't afford months of specialist triage.  

PwC's GIS Data Remediation solution can give utility clients a way to catch up on that backlog and keep pace with their data going forward, without adding headcount.