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How AI-curious utilities can accelerate adoption of the new tech

Scaling AI will require responsibly expanding its use — moving from crawl to sprint.

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An Idaho National Laboratory training and modernization project for commercial plant control rooms.

Photo credit: LineVision

An Idaho National Laboratory training and modernization project for commercial plant control rooms.

Photo credit: LineVision

Utilities, by design, are slow to adopt new technology. They’re a regulated public good, and electricity is mission-critical. 

Unlike many consumer applications where “good enough” new tech is usually fine, utilities must achieve physics-level accuracy across a range of data-driven operations, simulations, and modeling applications — from planning to ongoing operations. As a result, utilities have earned a collective reputation as a conservative industry that prizes reliability far above innovation.

But utilities must change faster. Today they’re facing unprecedented pressures, including a raft of net-zero goals for many energy providers and their biggest customers. 

Utilities must generate far more electricity than ever before to support the influx of electric cars and the conversions of fossil-fueled cooking and heating systems — a huge challenge, but also an unprecedented revenue opportunity. And they must do all this while upgrading and expanding aging grids to better connect ever-changing sources of clean energy with the people and businesses that need it instantaneously.

Other industries, from customer service to content creation to business efficiency, have already benefited from embracing artificial intelligence. Due to their cautious cultures, utilities are playing catch-up, but it’s increasingly clear that the technology will be indispensable. Here’s how utilities can adopt and scale AI responsibly — and go from moving at a crawl to leading the pack. 

Crawl: De-risk with ancillary applications

Utilities manage sprawling physical infrastructure that requires massive amounts of capital and hands-on human management. Failure can throw critical operations — think hospitals and traffic lights — into darkness. Mistakes don’t just cause downtime but also can spark major safety issues like wildfires or worse.

That’s why utilities should start deploying AI for ancillary applications that are not at the heart of the organization. It’s usually far faster and easier to roll out new technology in these contexts — and therefore to deliver real benefits that earn trust without risk of upsetting core operations. 

For instance, utilities can quickly deploy AI tech that tracks global weather patterns. This can allow them to anticipate disruptions before they happen and mobilize repair teams early. AI can identify the trees that are most likely to fall — the leading cause of power outages! — so utilities can trim them back before they can down power lines. AI can also improve customer service and billing by cutting out mundane, frequently made requests, offering superior automated service, and giving agents time back to focus on complex issues that demand a human touch.

Through these initial deployments, utilities can generate valuable feedback from employees and customers to continue refining AI and improving outcomes.

Each of these applications makes utilities more efficient and doesn’t require a wholesale change to operations or systems. They’re also a useful way to get organizations familiar with the benefits of AI and start shifting the culture toward an embrace of innovation.

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Walk: Expand into operations with low-risk, high reward applications

After crawling with AI, it’s time for utilities to walk by infusing AI into operations. A savvy place to start is with AI simulation tools (such as digital twins) that can help plan for a variety of grid scenarios via virtual models. These models can ingest enormous amounts of data and envision an unprecedented range of opportunities and challenges for the quickly changing grid.

Digital twins have already delivered impressive results for industries where getting it wrong can be disastrous, such as the military and healthcare. This approach is an ideal first step into the heart of any business, demonstrating first-hand the speed and value AI can deliver to transform an enterprise in the future, without stressing operations in the present. AI-based assistants or concierge-type characters in digital twin environments can help users understand complex data sets and drive simulations for all sorts of planning scenarios, including new infrastructure build-outs, training, and disaster responses.

Utilities can also start moving at a brisker walk — even a jog — by using AI in monitoring systems that don’t just plan but also evaluate conditions in real time. For instance, AI-powered Dynamic Line Rating sensors can determine just how much electricity power lines can really handle, increasing transmission capacity by 30% or more and ultimately reducing the need for new and costly infrastructure. 

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Transition-AI: Can the Grid Handle AI’s Power Demand? | May 8 @ 1 pm ET

Are growing concerns over AI’s power demand justified? Hear from Latitude Media's Stephen Lacey and industry-leading experts as they address the energy needs of hyperscale computing, driven by artificial intelligence.

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VIRTUAL EVENT
Transition-AI: Can the Grid Handle AI’s Power Demand? | May 8 @ 1 pm ET

Are growing concerns over AI’s power demand justified? Hear from Latitude Media's Stephen Lacey and industry-leading experts as they address the energy needs of hyperscale computing, driven by artificial intelligence.

REGISTER NOW
VIRTUAL EVENT
Transition-AI: Can the Grid Handle AI’s Power Demand? | May 8 @ 1 pm ET

Are growing concerns over AI’s power demand justified? Hear from Latitude Media's Stephen Lacey and industry-leading experts as they address the energy needs of hyperscale computing, driven by artificial intelligence.

REGISTER NOW

Run: Pilot quick, scale faster

To fully achieve net-zero, utilities must run with AI. Test projects can build confidence, but utilities are notorious for spawning “pilot hell” — a vicious cycle of insisting on more and more analysis of proposed solutions until innovation partners run out of time and capital. 

Today’s challenges are just too big to spend time in endless test loops. Utilities must adopt an innovation mindset, building a culture of AI by celebrating wins, cultivating advocates, streamlining reviews, and always moving toward scale. The more utilities use artificial intelligence and get results, the more momentum we’ll see. 

Remember, AI is by definition always learning and getting better. So the faster we bring it to scale, the faster it will improve. Ultimately, utilities can realize the benefits of AI at every level of their organizations, but they need to start now.

With soaring energy demand, pressing net-zero goals and mandates to keep energy reliable and affordable, the challenges for utilities have never been greater. To meet this moment, scaling AI isn’t optional — it’s a must.

Patrick Walsh is a director of investments at National Grid Partners. He has been involved with AI for over 40 years and has invested in startups since 2007. The opinions represented in this contributed article are solely those of the author, and do not reflect the views of Latitude Media or any of its staff.

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