The Five Convergences (Part V of VI): AI as Designer – The Hidden Architect

In this episode of AIxEnergy, host Michael Vincent continues the series on The Five Convergences, a framework mapping how artificial intelligence is reshaping energy systems from the inside out. Episode five explores one of the most creative and transformative roles of AI: AI as Designer.

Unlike optimization or control, AI as Designer steps into the earliest stages of the energy transition. It does not just help utilities run existing infrastructure more efficiently; it helps us imagine, site, permit, and design the infrastructure of tomorrow. Brandon N. Owens, founder of AIxEnergy.io and author of The Five Convergences of AI and Energy, explains how AI is becoming the hidden architect of the future grid.

Owens begins by outlining the problem: the U.S. and global energy transitions are not bottlenecked by technology but by planning and permitting. Transmission projects can spend a decade in regulatory limbo before the first shovel hits the ground. Permitting disputes stall wind farms and solar parks for years. AI, he argues, has the potential to compress these front-end bottlenecks dramatically—turning timelines measured in years into months.

The conversation explores siting and permitting, perhaps the most contentious domain of all. Traditionally, analysts pore over environmental impact statements, zoning laws, and ecological studies, often manually and adversarially. Owens highlights prototypes like PermitAI, which have shown that machine learning can digest millions of words from past environmental filings and make them instantly searchable. Beyond text, AI can integrate satellite imagery, land-use maps, and species data to recommend sites that balance cost, environmental impact, and equity.

From permitting, the episode moves to infrastructure design itself. Owens describes how AI unlocks “design space exploration.” For microgrids, this means simulating thousands of possible combinations of solar panels, batteries, backup generators, and load strategies. Where human engineers might model a handful of scenarios, AI can test thousands, finding configurations that are cheaper, cleaner, and more resilient. The same principle applies to transmission routing: AI can weigh geography, land ownership, costs, and environmental trade-offs to propose alignments that minimize conflict while maximizing reliability.

The discussion then broadens into novel solutions—cases where AI surfaces design options humans might never consider. Because it is not bound by precedent or habit, AI can propose hybrid architectures, unconventional siting strategies, or tariff models that balance fairness and grid stability in ways traditional approaches overlook.

Of course, the role of AI as Designer is not without risks. Owens and Vincent discuss how bias in training data can lead to inequitable siting outcomes or unfair tariff designs. Transparency and governance are vital; communities must trust the logic behind AI-driven recommendations. The episode emphasizes that AI should augment human judgment, not replace it, and that public participation is essential. Designing infrastructure is as much about people and politics as it is about algorithms.

In closing, Owens situates AI as Designer within the broader arc of the Five Convergences. While AI as Controller grabs headlines and AI as Optimizer saves money, AI as Designer tackles the most fundamental bottleneck of all: the time it takes to build. By compressing permitting cycles, unlocking novel solutions, and accelerating design, AI as Designer could become one of the most important enablers of the clean energy transition.

This episode paints AI not as a flashy operator but as a hidden architect—a partner in imagination that helps societies design the systems we will depend on for generations.

Transcript

Michael: Welcome to A-I-x-Energy, the podcast where we explore the rising intersection of artificial intelligence and the systems that power our world.

I'm your host Michael Vincent, and today we continue our deep-dive series into The Five Convergences — a framework that maps how artificial intelligence, or A-I, is reshaping electric infrastructure from the inside out. This is episode five of six on the topic, and today we begin our next deep dive--this one into the concept of A-I as Designer.

Our guest today is Brandon N. Owens — founder of A-I-x-Energy dot I-O and the author of not one, but two reports: The Five Convergences of A-I and Energy and Artificial Intelligence and US Electricity Demand: Trends and Outlook to Two Thousand Forty. Together, these reports form the intellectual foundation for understanding A-I’s physical footprint on the American electric grid.

Today we’re focusing on one of the most important shifts happening in the energy industry — something called AI as Designer. Can you explain what that means?

Brandon: Thanks, Michael. It’s great to be here. AI as Designer is powerful because it moves us from simply running the grid more efficiently to rethinking how we create the grid in the first place. It’s about embedding intelligence into planning, siting, permitting, and design—compressing timelines and uncovering solutions humans might never see on their own.

Michael: So let’s frame this. When you say “AI as Designer,” what’s the big picture?

Brandon: The way I think about it is this: for decades, the clean energy challenge hasn’t been about whether we have the technology—we do. Solar panels, wind turbines, batteries, transmission lines, all of it exists. The bottleneck is the front end—planning and permitting. Projects can spend a decade in queues before construction starts. AI as Designer promises to shorten that dramatically by analyzing massive datasets, simulating trade-offs, and producing design options that compress multi-year timelines into months.

Michael: So the role of AI here is not just optimization after the fact, but creativity upfront.

Brandon: Exactly. It’s as though you’re moving AI from the passenger seat into the architect’s chair.

Michael: Let’s take siting and permitting, because that’s where so many projects stall.

Brandon: In the U.S., interconnection queues are a great example—hundreds of gigawatts of solar, wind, and storage waiting for approval. Why? Because each project requires exhaustive analysis: maps, environmental reports, local zoning laws, community impact assessments. It’s slow, costly, and often adversarial. AI can help by scanning and synthesizing all that information at once. A prototype like PermitAI, developed at Pacific Northwest National Lab, created a searchable database of millions of words from past environmental impact statements. Instead of weeks spent hunting for precedent, you can find it in seconds. And it doesn’t stop at text. AI can integrate satellite imagery, species maps, hydrology data, and community demographics. Instead of just saying, “This site works,” it can show why it balances cost, environmental impact, and equity considerations.

Michael: Which sounds almost like turning permitting from a roadblock into a design dialogue.

Brandon: That’s the goal. And while AI won’t eliminate the politics, it makes the process faster and more transparent. Imagine compressing permitting timelines from 7–10 years down to 2–3. That’s the scale of change we’re talking about.

Michael: Once the site is chosen, design begins. How does AI step into that stage?

Brandon: This is where AI really shines. Take microgrids. A microgrid might combine solar panels, batteries, backup diesel generators, and smart demand-response systems. An engineer might model a few dozen configurations. AI can simulate tens of thousands—testing cost, emissions, reliability, and resilience. There’s an actual case where AI-designed microgrids turned out 20 percent cheaper and more resilient than standard engineering approaches because the algorithm found combinations humans never tried. The same is true of transmission planning. Routing a new high-voltage line involves thousands of variables—topography, land ownership, costs, ecological sensitivity. AI can propose alignments that minimize conflict while maximizing resilience.

Michael: So AI doesn’t replace engineers, it gives them a dramatically bigger design canvas.

Brandon: Exactly. Think of AI as expanding the imagination of the designer.

And sometimes AI surfaces solutions that no one would have considered.

Yes. Humans rely on heuristics—we look for patterns we know. AI has no such bias. It might discover a hybrid energy park design where solar and wind assets are co-sited with storage in a configuration that reduces curtailment dramatically.

Or it might reveal a novel tariff structure that balances grid stability and fairness to low-income households. These are non-obvious insights. AI is less about incremental prediction and more about creative discovery.

Michael: So in a way, AI becomes a design partner that thinks differently from us. But with creativity comes risk. What should we be cautious about?

Brandon: Several things. First, bias. If the data reflects inequities—say, prioritizing wealthy neighborhoods for reliability—that bias can creep into AI siting or design recommendations. Second, transparency. If AI produces a brilliant design but no one can explain how it got there, communities won’t trust it.

We need governance frameworks where AI augments human judgment, not replaces it. And we need community participation. Design is not just technical—it’s social.

Michael: So the danger isn’t rogue AI—it’s using AI without guardrails. When you step back, what does AI as Designer mean for the bigger picture?

Brandon: It’s also about imagination. AI doesn’t just help us do what we’ve always done more efficiently—it helps us design systems we might never have thought possible. That’s why I call AI as Designer one of the most transformative convergences.

It’s about acceleration. Today, permitting and planning delays are a top barrier to meeting climate goals. If AI can compress those bottlenecks, we can move clean energy projects faster from concept to reality.

Michael: That’s a great way to put it. AI as Designer isn’t flashy—it’s not controlling the grid minute by minute—but it’s shaping the blueprint for the energy systems we’ll depend on for generations.

Brandon: Exactly. It’s the hidden architect of the future grid.

Michael: Brandon, thanks so much for joining us.

Brandon: Always a pleasure.

Michael: Thanks for joining us, Brandon. And thank you for listening to A-I-X-Energy. If you enjoyed today’s episode, share it with a colleague, subscribe, and join us next time as we explore the convergences shaping our energy future. Visit A-I-X-Energy. The “Five Convergences” report goes deep into AI as Designer with more examples and governance recommendations.