What tomorrow’s utilities are getting right today

The utilities companies that invest in their data foundations today are those that will best navigate the upheavals to come

Utilities have spent decades building the physical networks that keep cities running: water mains, power lines, gas pipelines, fibre corridors. As the sector faces mounting pressure from electrification, decarbonisation and the rapid expansion of AI-driven datacentres, the organisations best positioned to adapt are those that have also invested in the systems that make sense of operational data.

That shift is already under way. Across the sector, the ability to automate, integrate and virtualise operational data is becoming a genuine competitive differentiator. The technology rarely makes headlines, but it is reshaping how utilities operate, respond to crises and prepare for a very different energy landscape.

Spatial computing is changing the point of work

Field workers have operated with limited information at hand for decades. Site visits meant carrying printed diagrams, referencing static manuals and recording observations on paper before returning to the office to update systems. The model was slow, error-prone and increasingly untenable as infrastructure complexity grew.

Augmented reality and spatial computing are beginning to close that gap. Field teams are now using iOS devices to visualise digital twins of underground and above-ground infrastructure in real time, overlaying live sensor readings, maintenance histories and service records directly onto the physical environment. These are production tools already in use, with updates syncing back to centralised data platforms via the cloud.

What’s the impact? A technician can see real-time water pressure readings overlaid on a pipe network, or pull up the full service history of an electrical asset while standing next to it. Decisions happen faster and with greater confidence, and connecting field teams directly to the organisation’s data ecosystem compresses the time between observation and action.

Automation is reclaiming thousands of hours

Data integration is also delivering measurable efficiency gains that compound over time. Disconnected workflows and manual data handling have long weighed on utility operations, consuming resources, slowing processing and introducing errors at every handoff.

Utility services companies in Canada, for example, have been managing damage prevention processes across internet service providers, local distribution companies and municipalities province-wide, largely through manual coordination. By standardising records and automating data integration workflows, over 90% of those processes can be handled automatically, saving hundreds if not thousands of hours each year. Other utility firms have gone as far as fully automated their excavation inquiry process, cutting monthly processing time by over 97%.

The gains extend further when automation is paired with AI. A major European electricity distributor is using data integration tools combined with generative AI to digitise more than two million historical records, completing in 60 hours a task estimated at 19 years by hand. That kind of legacy modernisation unlocks decades of institutional knowledge that was previously buried in unstructured archives, making it available for planning and analysis.

Operational efficiency is valuable on its own, but the stakes rise in emergency scenarios. In high-risk situations such as wildfire monitoring, fragmented data systems can delay the flow of critical information to first responders.

During wildfire season, a North American utility deployed automated data integration and spatial processing to ingest and validate active fire data every four hours, producing near-real-time mapping of fire activity hotspots and threats to infrastructure. That visibility gives operations managers and emergency responders the information they need to act quickly, including proactively de-energising lines in threatened areas.

The same data integration capabilities that improve day-to-day productivity also form the backbone of effective emergency response. Better operational visibility is both a business advantage and a public safety necessity.

Building the foundation for what comes next

As AI reshapes both demand patterns and operational capabilities, utilities face a dual role: powering the infrastructure that AI depends on while simultaneously adopting AI to improve their own operations. That relationship only holds up if the underlying data architecture is sound.

The ability to efficiently integrate data from sensors, operational systems, historical records and AI-generated insights is what turns raw information into something useful. Strong data integration makes AI applications more effective, and AI-driven workflows improve data management tasks in return.

The utilities that invest in their data foundations today will be the ones equipped to navigate electrification, decarbonisation and the AI-driven demands ahead. These examples represent only the beginning of what becomes possible when data is treated as the strategic asset it is.

Don Murray is CEO of Safe Software