How utilities are using AI to prioritize pipe renewal, foresee future risk, and uncover failing meters before they create costly surprises.
Utilities across the Northeast operate some of the oldest and most complex water systems in the country. Pipes installed 70-100, even 120, years ago still serve dense cities where every main break disrupts traffic, businesses, and critical services. At the same time, utility leaders must plan renewal programs with limited budgets, incomplete asset data, and growing regulatory pressure.
Many systems still rely on pipe age or past break history to guide renewal decisions. But those methods often miss the pipes most likely to fail next.
In this webinar, VODA.ai’s Northeast water expert Chuck Krohg, AI expert CTO Ben Schroeder and guest speaker Scott Schweda, Superintendent of Utilities at Arlington Heights, will show how utilities are using AI-driven risk prediction to make smarter infrastructure decisions. Using real examples from the field, they will explain how data can identify which pipes are most likely to fail, where hidden leaks may be occurring, and which water meters may be under-registering and contributing to apparent losses.
The session will show how utilities can move from reactive repairs and age-based replacement to a more defensible, data-driven approach to renewal planning.
Key Takeaways
- How AI models work to predict failures
- Why pipe age or break history are poor predictor of future failures
- How predictive analytics can help utilities prioritize renewal investments
- How utilities can identify hidden water loss and underperforming meters
- Practical steps for getting started with predictive analytics using existing utility data
