Can AI Fix Solar’s Scalability Problem?

On paper, the global solar industry has never looked stronger. The International Energy Agency reports solar panel costs have fallen by about 80 percent in the past decade. As prices drop, investment is rising and governments are setting new records for renewable energy targets. Yet projects still take too long to move from plan to installation.

Experts say the problem isn’t the technology itself, but everything that happens around it. The business side of solar — from lead generation to designing proposals to managing installs — is still largely manual. For the most part, solar projects still depend on phone calls, spreadsheets and a lot of paperwork. That slows everything down, and in a business with tight budgets and deadlines, even small mistakes can be costly.

That’s why some startups are now beginning to use AI to tackle the slow, complicated commercial side of solar. Instead of hardware, they are focusing on the behind-the-scenes work that connects customers, sales teams and installers.

The Business Bottleneck

“Most people think scaling solar means building more panels or hiring more installers,” said Areg Aghayants, founder and CEO of SolarGenix, a Los Angeles-based startup using AI to automate solar operations. “But the biggest drag on growth happens before a single panel is installed. Sales reps spend too much time on unqualified leads, and once they find good ones, it can take hours to send each proposal.”

Aghayants has spent more than a decade in the solar and battery storage sector. His company is one of several that see automation as a practical way to bridge the gap between rising demand and limited capacity. “AI can handle most of the repetitive steps — qualifying leads, generating offers, tracking progress — so human teams can focus on what matters: Relationships and customer experience,” he said.

The potential impact could be significant. Research from Wood Mackenzie shows that soft costs — things like sales, marketing, and system design — now make up more than half the price of a residential solar system. Lowering those costs could make solar more affordable and give small companies a better chance to compete.

What Automation Really Looks Like

Automation in solar does not mean robots building panels or drones installing rooftops. It is mostly about information flow. When a potential customer enters an address or uploads utility data, AI systems can generate a custom quote, design layout, and savings estimate in minutes. From there, automated systems can track the project through permitting, installation, and follow-up — steps that used to take entire teams.

“Software-first models are what will define the next generation of solar companies,” explained Aghayants. “A single salesperson with the right tools can now handle twenty times more projects than before.”

That trend mirrors a bigger shift across clean energy. BloombergNEF reports that AI and automation are now critical to helping renewables grow faster and operate more efficiently. While smarter software isn’t replacing hardware progress, it’s becoming just as essential to meeting global climate goals.

The Limits

However, there are limits to what AI can or should automate. Aghayants admits that machines still don’t do a good job of giving customers a good experience. “Technology can speed up the process, but people still need to feel valued,” he told me. “AI will improve over time, but human connection is not something it can replace yet.”

Finding the right balance between speed and trust is becoming one of the most important issues for automation in sustainable energy. AI might simplify operations, but it can also make data accuracy and oversight more risky. When algorithms automatically suggest things or make financial projections, errors can carry real consequences.

As one study by Energy Informatics notes, poor transparency and weak data governance are among the top concerns in using AI for energy systems. With more and more companies now using automation to speed up sales and design, the need for stronger checks on data quality and accountability has never been greater.

The Race To Scale

Competition is likely to show whether AI is really changing the solar business. The companies that use automation to work faster and cut costs will have an advantage over those still relying on manual processes. Aghayants believes that shift is already starting to happen as more companies find ways to do more with fewer resources. “A solar company relying on spreadsheets can’t keep up with one using an integrated AI system,” he said. “The gap in speed and cost will only grow.”

That prediction may not be far off. As clean-energy incentives expand and consumer demand rises, smaller firms face pressure to deliver more with less. Many lack the resources to build custom software, which is why white-label solutions — pre-built platforms that can be branded and used by different companies — are gaining traction. This model allows even small contractors to run at enterprise scale without deep technical knowledge.

But that adoption will not be automatic. Many small solar businesses still operate on thin margins, and investing in new software requires trust that it will pay off. As the American Council for an Energy-Efficient Economy notes, AI can help accelerate the clean-energy transition only if companies focus on measurable benefits and transparency. In other words, the technology alone is not enough to deliver results.

A Smarter Path Forward

The question of whether AI can fix solar’s scalability problem may not have a single answer. People and policies still decide the pace, even though technology can speed up solar. Rules for permits, limits on grid connectivity and ways to get money are still slow-moving parts of a system that changes quickly.

Even so, automation is fast becoming the backbone of the solar industry. But the real test for the industry isn’t how many panels it installs, but how efficiently it can manage projects from sale to installation. Companies that use smarter systems to speed up those steps could define the next stage of growth for the industry.

Aghayants thinks that change is inevitable. “We’re going towards a world where software is becoming central to how solar companies operate. The companies that adapt to this shift will grow. Those that don’t will be left behind,” he said.