Beyond the meter: How property intelligence can predict the future of energy demand

EV charging and surging demand

Two forces are dramatically reshaping the energy landscape: electric vehicles (EV) and Artificial Intelligence (AI). A single EV charging at home is equivalent to adding a major new appliance across millions of households. Predicting this load requires intelligence beyond simple demographics; it requires parcel-level data to identify which properties are most likely to adopt high-load technologies:

• Municipalities: Combining GIS parcel data with traffic flow models is essential for strategically placing public charging infrastructure.
• Utilities and insurers: Identifying parcels with (or likely to have) EV chargers is crucial for assessing local grid stress and insurance liability risks associated with high-load equipment.

Rising demand is also surging from AI data centers, where loads have tripled over the past decade and are projected to triple again by 2028. This rapid growth creates a significant supply/demand gap, putting upward pressure on electricity prices.¹

Mark C. Christie, former FERC Chairman and current Director of the Center for Energy Law & Policy, warns that the U.S. faces an “unprecedented surge” in power demand.

“The next 3 years will be a crucial window for major investments, upgrades, and policy actions required to optimize all available energy, protect the average American’s pocketbook, and fuel continued innovation and economic growth,” notes Christie.²

The shift from reactive metering to predictive intelligence

For decades, utilities relied on historical consumption and weather to forecast demand. This system is now obsolete; it fails to capture the physical attributes of buildings and the rapid adoptions of solar and EVs.

Cotality provides the missing link. We integrate "structural DNA"—complex parcel and building data—with growth intelligence to create a precise, bottom-up model for energy demand.

Parcel data and growth intelligence

Parcel data provides hundreds of attributes that are fundamental predictors of energy use, including building characteristics, energy efficiency features and usage context like zoning. This structural intelligence allows us to move beyond simple weather correlation and model the precise energy requirements of a building stock.

When paired with growth intelligence—which monitors development pipelines and permit activity—this becomes a powerful tool. Utilities can simulate the impact of planned developments before they break ground by:

• Predicting the exact load a new housing development will place on a specific transformer or feeder line.
• Identifying where distribution equipment is most likely to be overloaded in the next five years, allowing utilities to optimize capital expenditure for upgrades rather than react to failures.

Value and resilience

The ability to plan for demand is directly tied to property value and resilience, a fact we quantified in the Cotality Australia "Watts it Worth" report. Our analysis of six million homes proved that energy performance is a measurable contributor to market value; for example, homes with solar power commanded an average value uplift of 2.7% in Australia.

This impacts the entire property ecosystem:

• For Insurers: Lower-demand homes often imply better construction standards and lower risk exposure to grid failures.
• For Lenders: Energy-efficient properties are more resilient to future price hikes, potentially lowering default risk. This is critical as average electricity bills in 2026 have risen over 30% since 2019.³
• For Policymakers: Evidence of value premiums supports the push for stricter efficiency disclosure and targeted incentives.

Powering the future with data clarity

The challenge of rapid electrification is immense. The solution isn't just building more capacity; it’s achieving data clarity. Cotality empowers stakeholders to move from macro-level guesswork to parcel-specific prediction, ensuring the next generation of energy infrastructure is robust, efficient, and resilient.