In this episode of the Econ Dev Show, I share my talk from the Utility Economic Development Association’s 2025 Fall Forum in Traverse City, Michigan. We dig into how AI moves economic development from gut‑feel to data discipline—especially when utilities turn raw infrastructure data (power, water, sewer, fiber) into usable intelligence that speeds RFIs and project decisions.
Listen: Econ Dev Show Podcast – Episode 196
Watch: YouTube episode
Key takeaways
- Start by making one dataset machine‑readable—even if it never leaves your organization.
- Treat AI like infrastructure, not a chatbot. Build systems that work continuously.
- Use APIs to connect datasets and automate workflows.
- Chain models to combine reasoning, retrieval, and structured output.
- Capture tribal knowledge by turning tacit expertise into structured data.
- Automate RFI responses by connecting clean site data to AI scoring.
- Try “vibe coding”: describe desired outcomes before you design logic.
- Stop optimizing for Google; optimize for AI systems that synthesize and act.
- Run small monthly experiments to test models and internal automations.
- Advocate internally—utilities are the backbone of AI‑enabled economic development.
If you want to see how Sitehunt puts these ideas into practice, we’d love to walk through a demo with your data.
Adapted from an article originally published on Econ Dev Show. Read the original post