Top Trends Shaping the Grid Orchestration Journey in 2026

Part of keeping utilities (or any company, really) successful as industries change is by staying on top of the latest trends.

Few companies experience as many changes as utilities. Utilities must adapt to constantly evolving consumer preferences and needs, consumption patterns, new technologies, regulatory mandates, sustainability targets, and more. Staying informed about their industry’s trends and the factors that shape them is one of the best ways for utility executives to modernize for the future of energy and maintain their organizations’ competitive edge.

That’s why Gartner® recently released its latest report on power industry trends, titled “Top Power and Utilities Trends for 2026: Driving Operational Excellence.” Gartner identified six major trends for 2026: three each for business and technology .

Today I want to dive deeper into one from each category. Let’s start with…

No surprises here. Utility discussion circles have been abuzz lately with chatter about the immense value automation can bring to utility operations. AI certainly has its place in the modern energy landscape, in which decisions must often happen in a matter of seconds and/or take into account literal terabytes of data. In particular, I felt that Gartner honed in on one area of utility operations that is particularly well-suited for AI: asset health.

It's no secret that the power assets that comprise grids are aging faster than replacements can be sourced. In this time of manufacturing constraints, sky-high prices for raw materials, and soaring demand, it’s more important than ever for utilities to monitor + predict their assets’ health and address issues before a full-blown failure occurs.

But the traditional approach to asset health monitoring, with paper reports, in-person inspections by field crews, and overall reactive maintenance is no longer feasible. The sheer scale of grid assets needing monitoring plus the increasing number of threats to them calls for AI-enabled solutions . In fact, Gartner found that “By 2027, AI-enabled asset intelligence will cut outages by 40%, helping utilities to move from reactive to predictive maintenance.”

We’ve observed similar industry trends at GE Vernova, which prompted our recent focus on GridOS® Visual Intelligence, our own AI-enabled asset intelligence solution. Visual Intelligence’s workflow is simple to use, but immensely powerful: it overlays network infrastructure with terrain scans and photos, using a color-coding system to flag the precise areas where power assets are at risk. It then automatically prioritizes each anomaly by risk of damage, then generating and assigning work orders to an appropriate stakeholder for follow-up. This workflow unlocks preventative maintenance for utilities, empowering them to take corrective action long before a disruption can occur.

Utilities’ increased interest in AI-enabled asset intelligence solutions was a major factor behind our decision to acquire Alteia SA, the company behind Visual Intelligence’s technology. The visual insights of Visual Intelligence hold tremendous value for other downstream grid applications like Advanced Distribution Management System (ADMS) and Distributed Energy Resource Management System (DERMS) . By bringing Alteia in house, we plan to develop our technology stack to feed visual insights directly into complementary grid applications. And in doing so, we will bring the value of Visual Intelligence’s visual insights beyond the asset intelligence use case. The same value, on a grander scale. Everyone wins.

Gartner says in its report, “By 2027, the first utility operating with legacy operational technology will face unrecoverable automation failures after a major cyber incident, forcing a complete operational rebuild and exposing the organization to regulatory and financial penalties.”

I have no problem believing that prediction. An increased reliance on AI and edge devices increases cybersecurity risks concurrently. The exact same automation technology that makes utilities more efficient and effective can be exploited by cybercriminals. AI’s ability to process enormous amounts of data has been noted by cybercriminals, who often use black market technologies to analyze and find vulnerabilities in companies’ cybersecurity protections. AI can also be used to create near-perfect phishing emails (eliminating the once-telltale broken English and poor grammar), startlingly lifelike chatbots that can manipulate employees into giving out sensitive information, and automated adaptive malware that constantly changes its own code to avoid detection.

In addition, the rise of DER integration has compounded cyberthreats for utilities. Many DERs connect to utility networks via unsecured internet connections. The more DERs connected to a given grid, the more potential access points hackers get to choose from.
The time is now for utilities to double down on cybersecurity – or, , there may not be a second chance. At GE Vernova, our endorsement is always on a Zero Trust grid security model, such as the one that shields our GridOS platform from cyberattacks. Zero Trust, as its name suggests, trusts absolutely no one with access to sensitive information. Systems protected by Zero Trust are loaded with protective measures against bad actors, including access restrictions, time limits before reauthentication must happen, and more. Even fully authenticated and verified users are treated as though they are accessing the system while under duress, by being bound to the same restrictions imposed on other users.

And as an added measure of assurance, Zero Trust grid security principles are built in, not bolted on. A bolted-on Zero Trust grid security model only protects a system from external threats, like the moat around a castle or the walls of a fort. It offers minimal protections against internal threats – whether a validated user gone rogue or a bad actor who managed to get past the outer defenses. Once the bolted-on grid security model has been bypassed, the entire network is at risk.

The GridOS platform and applications were built from the ground up with Zero Trust principles in mind. It protects against more than just external threats. Every tool, interface, pathway, data stream, and function within GridOS has optimal protection from internal and external threats. Continuing the castle metaphor, a built-in Zero Trust grid security model forms not just the outer moat, but internal defenses as well – think of locked doors, dead ends, patrolling guards, trapdoors, and the like. So the intruder was able to cross the moat? Good for him – now he faces a plethora of additional security measures before they reach the hidden treasures.

It all adds up to an optimal level of cybersecurity for utilities, even against the most advanced threats they’ve ever faced.

GE Vernova is pleased to share the Gartner “Top Power and Utilities Trends for 2026: Driving Operational Excellence” report for complimentary download. Simply visit its landing page and fill out the form to receive your copy.

Gartner, Top Power and Utilities Trends for 2026: Driving Operational Excellence, By Lloyd Jones, Nicole Foust, Jo-Ann Clynch, Jim Robinson, Sruthi Nair, 20 October 2025.

GARTNER is a trademark of Gartner, Inc. and/or its affiliates.