The grid of tomorrow is arriving faster than utility leaders can plan for it. Data centers, electrification and new industrial load are outpacing traditional planning cycles. Meanwhile, customers expect near real-time information, regulators demand affordability and aging assets require immediate attention.

That pressure is clear in Itron's 2026 Resourcefulness Insight Report, which surveyed 700 utility executives across the U.S., Canada, Australia, New Zealand and the Nordics. Load growth ranked as the top grid stressor at 43%, followed by customer expectations at 36%, with AI integration, new construction, affordability, distributed energy resource (DER) growth and aging infrastructure close behind.

Encouragingly, utilities aren't facing this moment empty-handed. Most have already built Advanced Metering Infrastructure (AMI) and other infrastructure that delivers the data and insights needed for better decisions. The question now is less whether utilities have intelligence than how they put it to work, from the field and control room to the boardroom.

The Foundation is Already in Place

Near real-time intelligence at the grid edge has moved into the mainstream. In our survey, 96% of utilities use near real-time data from meters, sensors and other intelligent endpoints to support operational decisions, either fully embedded or in selected workflows. That data is already informing decisions on wildfire and vegetation risk, outage detection and restoration, load management and fault location.

AMI has followed the same path. 86% of utilities use AMI data in enterprise-wide or specific workflows, well beyond its original meter-to-cash role. And 87% describe their analytics posture as highly or mostly proactive, with 44% saying advanced analytics and AI already support predictive, largely automated decisions.

The results are showing up where utilities need them. Respondents said operationalized analytics deliver the greatest value in outage management and restoration and in predictive maintenance (33% each), followed by workforce safety and efficiency (30%) and peak load management (29%). Those are the same reliability, asset and workforce outcomes utilities rank among their top priorities.

From Broad Use to Consistent Action

Using intelligence and fully operationalizing it are two different things, and the research draws that distinction sharply at the highest maturity level:

• 96% use near real-time edge data; 59% say it is fully operational.
• 86% use AMI data operationally; 41% say it is fully embedded and scalable.
• 91% call near real-time intelligence critical or very important during high-stress grid events; 35% have it fully integrated from detection through restoration.
• 93% are confident their data insights change decisions; 54% have strong feedback loops confirming that impact.

I don't read these numbers as a shortfall. They describe an industry that has built capability and is entering the next stage of maturity. U.S. utilities lead the way: 63% report fully operational edge intelligence and 49% fully embedded AMI.

The last gap deserves attention. Stronger feedback loops would give utilities clearer evidence of what works, guide future investment and build confidence about where more automation makes sense. Measuring decision impact may be the industry's next frontier.

Connection and Execution are the Real Barriers

Utilities stated that the barrier to using data for decisions isn't lack of insight but connection and execution. Technical integration led at 53%, followed by lack of automation (47%), data quality (44%) and data trust and organizational silos (42% each).

Each barrier has practical effects. Endpoint data becomes far more useful when matched with transformer, feeder and phase information, historical load and GIS connectivity. That context moves an operator from "something changed" to "here's where, what it affects and what needs attention." Without integration, that correlation is manual.

Automation is the next link: 47% of utilities rank lack of automation among their top obstacles. Routing outage events, flagging transformers for inspection or triggering predefined load-control responses are routine decisions that can happen closer to the data. The goal isn't removing people from the loop but reserving their attention for judgment calls.

Trust ties it together. An abnormal reading checked against neighboring endpoints, historical patterns and asset data arrives corroborated. The more reliably data is validated upstream, the less time crews and operators spend double-checking it.

Investments that Multiply

One striking finding from the report is that major data investments travel far beyond their original purpose: 93% of utilities say that data investments have enabled at least two additional use cases, and 47% report four or more. And 58% deliberately choose investments that can support multiple current and future uses.

That matters for capital efficiency. With 15- to 20-year asset lives and ongoing affordability pressures, every investment must keep earning its keep as needs change. Open, interoperable infrastructure lets utilities add edge intelligence to existing systems like SCADA and ADMS and extend new applications to the same endpoints and networks without starting over.

It also signals readiness. Utilities with highly or mostly proactive analytics are about three times as likely to report four or more additional use cases, and 89% say they're prepared for significant load growth, versus 57% of less proactive peers.

Three Moves for the Next Phase

Utilities already know where they are headed. Over the next three years, respondents expect to focus most on enterprise integration (28%), executive decision support (23%) and workflow automation (20%). The emphasis is shifting from acquiring new capabilities to connecting and activating the ones already in place. Based on the research, three moves stand out.

Connect before you add. Before the next standalone investment, map where existing edge, AMI and operational data could be shared across outage, asset, planning and customer workflows. Interoperability is often the fastest path to new value.

Automate the routine, elevate human oversight. Identify repeatable, well-understood decisions that can be triggered automatically, and keep human oversight on events with broader grid, safety or cost implications.

Close the loop. Build feedback mechanisms that confirm whether insights actually changed a decision and what happened as a result. That evidence supports regulatory conversations, guides the next investment and builds the trust needed to automate more.

Load growth isn't slowing down, and neither are customer expectations. Utilities have built an extraordinary foundation of grid intelligence. The advantage now belongs to those who turn it into repeatable action, making intelligence connected, trusted and embedded in the decisions that keep the grid reliable, resilient and affordable.