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 manage some of the oldest and most complex water systems in the country. In dense, built-out communities, pipes installed 70, 100, even 120 years ago still serve under streets where every main break disrupts traffic, businesses, and critical services.
At the same time, utility leaders must make renewal decisions with limited budgets, incomplete asset data, and growing regulatory pressure. Many still rely on pipe age or break history to guide those decisions. But those methods often miss the assets 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 of Arlington Heights will show how utilities are using AI-driven risk prediction to identify high-risk pipes, hidden leaks, and under-registering meters. Using real examples from the field, they will show how utilities can move from reactive repairs 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
