Those “wins of omission” are key data in the investment case for distributed energy projects. There also may be a parallel in the cost-benefit argument for industrial-scale artificial intelligence.

“We see the promise of AI, we really do, but we need help to know what’s real and what’s not real,” Mark Moffat, CEO of industrial AI software firm IFS, said earlier this week at this company’s IFS Unleashed event in Orlando.

Indeed, previous research by McKinsey, Bain and others have theorized that inclusion of AI into asset development and operations monitoring could unlock trillions of dollars in savings heretofore untapped or hidden. Yet those forecasts admit that a “productivity paradox” looms in which companies have all the data they might need but limited sense of what to do with it.

The potential of AI to both accrue value in savings for businesses and create jobs is championed and challenged when it comes to fear of machine autonomy and lost employment. Partially the point of the Unleashed conference is to show what IFS itself has achieved in partnership with a global range of companies and sectors but also to elevate vendor-neutral awareness of a multi-trillion-dollar value proposition in how AI creates revenue by what it helps the ground-level operation avoid in wasted effort.

Even the most well-oiled machines in the industrial sector may only be working at 60% of potential when it comes to unlocking the value of buried but relevant data or exposing useless practices draining the enterprise. Institutional knowledge on record is there and ready to be deployed but it may require digital colleagues which can retrieve, analyze and distill that in hours instead of months.

The best AI tools aren’t cheap but can you afford not to go there?

“It’s a choice, and you have to take it. You have to embrace this AI world,” Moffat said in his IFS Unleashed keynote at the Orlando World Center Marriott. “Where is your 40 percent to be unlocked?”

Finding those efficiencies is not just an IFS sales pitch. Unleashed backed it up with plenty of sessions on real-world use cases involving companies as unique from each other as Southwest Airlines, distillery William Grant & Sons, Siemens, Cadillac’s Formula One team leadership, Kodiak Gas Services, Microsoft, Thomson Reuters, Aveva, Black Hills Energy and TXNM Energy.

Energy was not the sole focus of IFS Unleashed but it was front and center as the proverbial double-edged sword. The extra electrification needed to meet AI and cloud-based computing load just in the U.S. is projected at more than 100 GW at a time of slow grid interconnection processes, and the supply chain for critical equipment like gas-fired turbines could take years to satisfy.

“There’s massive pressure,” Moffat pointed out. “If you’re in the market today for a gas turbine—good luck.”

Using GWs to save GWs

And yet successful agentic and generative AI tools may give as good as they take when it comes to energy. At last year’s NYC Climate Week in New York, a report by NVIDIA calculated that AI could make energy-intensive industries such as chemicals, rail, cement and transportation more energy efficient by up to 5 and 7 percent over previous consumption.

Just those industries combined draw about 2,400 GW in continuous power demand according to various reports, so even a 5% efficiency would save close to 120 GW. In simple math terms, even a humble half of the 40% promise alluded to by IFS would total almost 500 GW trimmed from electricity load by those industries alone. Multiply that by all the other industrial sectors and you’re talking terawatt hours of efficiency, which could prove to be an infrastructural miracle.

Ok, so blessed are the ironmakers of the world, you might say. What’s in it for me?

Reduced demand balances supply in a way that may avert a cataclysmic electricity pricing crisis of the first magnitude, that’s what.

Electricity prices in the constrained PJM Interconnection of the eastern U.S. rose nearly 50% in the past five years, while customers within New York ISO are enduring close to 60% in hikes over the time frame.

“It’s the reality of the current moment,” said Elizaveta Malashenko, now a managing director for the power & utilities practice at Houston-based consulting firm Alvarez & Marsal but with a career-long background in energy research and regulatory issues, during one of the IFS Unleashed breakout sessions.

“The big challenge is not the lack of quality in a utility’s investment plan but an affordability crisis,” Malashenko added.

Intelligence that drives resiliency: Microgrid believers can relate

Those attending IFS Unleashed heard plenty about AI and robotics, including a popular soccer ball kicking mini robot which took on all comers and kicked this author’s pride by hitting all three of the penalty shots on goal in a demonstration. The author’s defense was trash, that’s for sure.

Meanwhile, infinitely more accomplished sports heroes such as Tom Brady talked at IFS Unleashed about the value of resiliency in their own lives and careers. Digging deeper to find resolve to compete is a human thing, but tirelessly investigating the data well to drive value is AI.

Energy resiliency and efficiency may be key takeaways from an operations and maintenance viewpoint. Experts from Siemens, Aveva and other companies talked about the impact that agentic AI tools make in helping diagnose and fix mechanical issues such as at a green hydrogen plant and finding the key mechanical breakdowns in a batch of power generation equipment intended for an Alaska microgrid.

Those AI tools might increase operational efficiency by isolating and defining fixes needed in days rather than weeks. And time lost is money lost—there’s that “win by omission” value paradigm for microgrids as well as AI.

“How much do you truly obsess over your data?” Andy Pratt, corporate vice president of the emerging technologies group at Microsoft, said in an IFS Unleashed session. “Making decisions on critical infrastructure is based on more data in more places … as long as that data is trusted.”

During the Unleashed event IFS also released its Industrial Index surveying 2,200 leaders at companies in 14 nations and launched its IFS Intelligence AI product focused on industrial-scale data and problem solving.

In detailing the potential of the agentic AI tools for finding that 40% sweet spot in hidden value, IFS CEO Moffat pinpointed human interaction as critical for success in utilizing AI at the operations level.

“The missing 40% is already inside the business,” he said in a statement about the Intelligence product launch. “It sits in the expertise of the control room, the knowledge of the night shift, and the data spread across every system. IFS Intelligence brings all of it together and puts it to work. People can ask a question, take action, or hand a task to a digital worker, all within the rules, permissions and approvals that govern their business. That is how industry closes the gap.”

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