If you manage solar assets today, you’ve probably had the same conversation around your ops table: how do we integrate AI into our operations?

It’s an appealing idea, we get it. And where most groups start is looking for ways to build their own systems. We get it. You own the data, and you know your business better than anyone. On paper, crafting a custom system to layer AI sounds like owning your destiny. But as more asset owners and O&M providers are discovering, building software in-house doesn’t just cost time and capital–it costs your most precious resource: focus.

And in this market, focus is everything.

The Landscape Has Shifted: Agility Isn’t Optional

The solar industry is entering a new, leaner phase. Growth is still strong, but margins are thinner, expectations are higher, and timelines are shorter.

With new legislation passed over the summer, asset managers face tightened eligibility rules and a shrinking window to qualify for incentives. And of course, it’s not just about the incentives–it’s about long-term financial success and asset stewardship.

This environment translates into acute operational pressure: faster development cycles, more scrutiny on project readiness, and a greater emphasis on data visibility and reporting integrity. Agility and transparency aren’t 'nice-to-haves' anymore–they’re how you stay competitive.

For portfolio operators managing hundreds of sites across multiple owners and capital partners, the ability to consolidate performance, financial, and contractual data quickly isn’t just convenient, it’s essential for maintaining investor trust and accelerating new development.

When the clock is ticking this loudly, the push to build homegrown analytics and AI systems vs. partner reveal hidden costs not just during development but ongoing sustainable outcomes. The smart path is to build what defines your edge and adopt what accelerates your impact.

1. Expertise: You Can’t Build Context

Let’s be honest–data problems in asset management aren’t generic IT problems. They’re rooted in the physics of production variability, the nuances of equipment degradation, the friction of work order efficiency, and the risk of contract exposure. It’s a web of interconnected dependencies.

You can staff brilliant developers, but if they’re not deeply steeped in how solar portfolios operate, you’ll spend months–or years–teaching them context before they ever deliver production-ready value. That time is a costly distraction.

When you buy a purpose-built platform, you’re not just acquiring a product–you’re getting the collective domain expertise baked into it. The platform already speaks the language of asset performance modeling, root cause analysis, and contract validation.

The goal isn’t to outsource thinking–it’s to accelerate insight to solving real challenges around portfolio returns, performance reliability, and more.

2. Timing: Speed to Value Is Your Edge

Every quarter you spend building is a quarter you’re not analyzing, reporting, or optimizing performance. When legislative deadlines and investor expectations are both tightening, speed to value becomes your competitive edge.

Internal builds often stretch across quarters–sometimes years–as requirements shift and priorities compete for developer time. Buying a proven platform means you can start getting value in weeks, not years. It lets your team focus on using insights instead of building the system that delivers them.

Remember: there’s a difference between analytics and product. A product typically provides the full scaffolding of infrastructure and architecture, security, data pipelines, processing and compute, visuals and UI / UX, etc. Building capabilities internally means potentially mirroring similar capabilities–including the requisite resourcing and ongoing constraints that goes with that.

In this environment, speed isn’t a luxury–it’s how you stay eligible, funded, and ahead.

3. Sustainability: What You Build, You Own Forever

Here’s the truth: what you build, you also have to maintain, update, and secure–forever. It’s oftentimes the hidden costs that are not well understood or factored into when building systems and products.

Every integration, API change, and version upgrade adds complexity and cost. When key developers leave, knowledge leaves with them. Technical debt compounds quietly until it consumes your team’s bandwidth.

Building a homegrown system isn’t a one-time project. It’s a long-term commitment. Buying or partnering with scalable services shifts that burden. You gain the ability to grow and adapt–to integrate new equipment, standards, and AI models–without the constant overhead of maintaining another internal product line. Anvil shared a diagram of this concept of "True Cost" (see image below).

Having worked with numerous Fortune 500 organizations in my past and several asset owners and providers today, the costs of maintaining systems are big. Costs are not always purely financial, either, but emotional and mental. What ends up being homegrown also ends up being specific pet projects for certain individuals as their own institutional knowledge is the true algorithm running the system. This ends up creating unnecessary risks on the individual(s) and the organization who must maintain the system or risk the house of cards collapsing with individuals leave. 

We’ve seen it firsthand in solar where large and small organization build internal tools that start as helpful tools turn into legacy systems that only one or two people truly understand. And are so specific that they miss out on how the industry is evolving. When that happens, innovation slows, and institutional knowledge becomes a liability.

Sustainability isn’t just environmental–it’s operational.

4. The Age of AI: Build What’s Core, Connect What’s Not

Every organization today wants to leverage AI. And that’s the right instinct. But many teams make a costly mistake: trying to build the entire ecosystem themselves.

The winning model won’t be a single, monolithic “one ring to rule them all” system. It’ll be a connected ecosystem–a mix of specialized tools that work together to drive smarter analytics and faster decisions.

For most operators, AI starts small. This can include automating data normalization, summarizing performance insights, or flagging anomalies before they impact production. The key isn’t to build every model, but to create the ecosystem that lets your data feed those models efficiently.

That’s where internal focus should go to building and refining the differentiated, high-value layers: proprietary analytics, optimization models, and investor insights. Don’t rebuild the plumbing that moves and visualizes data. Use platforms that already handle the integration, normalization, and visualization–the services that are, in some cases, industry-wide. Then build your operational edge on top.

That’s how you leverage AI without losing momentum. Build capabilities based on the intelligence you’re able to weave into your analytics while focusing on specific use cases and specialties core to the company. Speaking of focus…

The Smart Path Forward: Own Your Focus

Every organization says people are their greatest asset. Though, it’s really about how their people focus.

Focus is what turns effort into momentum. When your analysts and engineers spend time fixing data pipelines or maintaining dashboards, they’re not improving uptime or profitability. By focusing on what’s truly core–asset strategy, performance optimization, and value creation–you multiply your impact. No longer are you operating linearly where scaling means adding another project, another person. Instead, you can multiply and increase capacity where 1 + 1 = 3, 4, 5…

External platforms like LCOE.ai exist to handle the foundation: connecting your systems, cleaning your data, and surfacing insights that matter–all the while streamlining workflows like report automation. That’s what enables your team to do their best work–not more work.

The question isn’t whether you can build your own system–where you should build core capabilities while integrating and partnering with non-core competencies. In today’s high-pressure environment, building everything yourself isn’t a sign of strength–it’s a distraction with risks for long-term sustainability.

The smartest asset managers and O&M leaders know where to focus. They build what defines their edge and adopt what accelerates their impact.

In the race to scale solar, clarity–not code–is your advantage. The next chapter of asset management will belong to the companies that combine focus, clarity, and data-driven agility. Build what defines your edge. Adopt what accelerates your impact. That’s how teams scale smarter.

Want to see how it looks in action? Let’s walk through it together.