With rising gas and electricity prices and data center sprawl, many Americans say their relationship with utilities makes them stressed, and somewhat ironically—powerless. The mandates are many for power utilities and their leaders these days. Customers increasingly expect visibility into service status, energy usage, billing, and available program options. Regulators expect clear reporting. Executives need confidence that investments are producing measurable outcomes.
Artificial intelligence can help, but where, and what’s the impact worth?
Utilities that create trusted, accessible information environments are better positioned to meet and even exceed expectations, and leaders at those utilities who demonstrate information integrity are more able to show how their capital investments in AI truly unlock value.
Spotting Information Integrity Gaps & Traps
Whether responding to an outage, prioritizing maintenance, planning capital improvements, or answering customer questions, decisions depend on reliable data.
Several information integrity obstacles are common across utilities:
- Information spread across disconnected operational, customer, financial, and asset management systems
- Manual processes slow processing and sharing
- Data quality and governance issues that limit the effectiveness of analytics and AI initiatives
Real-World Data Trap Example:
PG&E San Bruno (California, 2010). The pipeline ruptured where the company’s own records said the line was seamless. It wasn’t, and the operating pressure was set on those bad records. The community is still healing from the resulting explosion.
How Do Leaders Know Where AI Will Create Enduring Value?
New tools are coming out all the time, so utility leaders have to examine them carefully for true ROI potential. One of the highest-return opportunities is using AI to improve the quality of the organization’s underlying data and operating models.
AI can help:
- Identify data quality issues and inconsistencies
- Standardize asset and operational information
- Improve process documentation and institutional knowledge
- Clean up and refine models that support reporting, forecasting, and decision-making
When AI improves the foundation, every future analytics, automation, and customer experience initiative benefits.
Real-World Data Integrity Upgrade Example:
Duke Energy’s AI pole inspections. Computer vision across 33,000 miles of transmission lines, building a current picture of what’s actually in the field. It’s AI improving the data foundation itself
What Forward-Looking Utility Leaders Are Doing
2027 spells more rate increases in energy and in many places water also. To get ready for the year ahead and beyond, forward-looking utility leaders are taking these steps today:
- Building trusted, governed data foundations
- Connecting information initiatives to measurable operational and capital outcomes
- Using AI to strengthen systems and processes, not just automate tasks
- Delivering information in ways that improve decision-making for employees and customers alike
The utilities that succeed with transformative AI initiatives between now and 2030 won’t be the ones with the shiniest technology tools. They will be the ones that create the greatest trust in their information.
Because when data is accurate, accessible, and actionable, utilities and their leaders can better justify investments, improve customer experiences, and make smarter decisions about the future of the grid.
