Why We Waited on AI, and Why We're All In Now
Written by Sal LoPorto, CEO & Co-Founder, SparkChange
AI is everywhere right now, and for good reason. It's exciting. It's powerful. And it's moving fast.
Let's be real: the healthcare revenue cycle is complex, fragile, and already stretched thin. Tossing AI into the mix without a solid foundation? That's a recipe for chaos, not transformation. At SparkChange, we took a different approach.
We waited.
Not because we didn't believe in AI but because we believed in solving real problems first. In healthcare, this means starting with the basics: understanding your data, refining your processes, and addressing what's broken. Only then can AI accelerate what's working, instead of amplifying the chaos.
Fix What's Broken Before You Automate It
“Let’s be real: the healthcare revenue cycle is complex, fragile, and already stretched thin. Tossing AI into the mix without a solid foundation? That’s a recipe for chaos, not transformation.”
When we started SparkChange, we weren't thinking about AI. We were thinking about how to help health systems do more with less.
Revenue cycle teams were drowning in work. Systems weren't talking to each other. Leaders were flying blind when it came to data. So, we focused on solving those problems first—with analytics, automation, and hands-on services designed by people who have lived through this work.
That foundation became SparkInsight™ our operational intelligence layer. It's what gives our clients visibility into what's happening in their revenue cycle and where to act. It's not just dashboards. It's direction.
And once we had that? We built SparkImedes™.
The Right Time for AI Is When It Makes You Better
We didn't build SparkImedes™ to ride the wave. We built it because it was the right next step.
It's our AI engine—fed by SparkInsight™, trained on real data, and designed to work with the messy, real-world workflows health systems live with every day. It's not trying to be a black box that replaces your teams. It's an intelligence layer that makes them more effective.
That means:
Spotting revenue risks early and automatically
Prioritizing work based on real impact, not guesswork
Adapting in real time to changing payer behavior
It's not just smarter automation. It's decision support that's grounded in experience and context.
AI Alone Doesn't Change Healthcare. People Do.
Here's what we've learned: AI can't fix what's broken. But it can speed up what's working.
That's why we didn't start with algorithms—we started with expertise. SparkChange was built by engineers, strategists, and revenue cycle leaders who understand the real-world complexity of healthcare. We built the structure. Then, we added the engine.
Now, our approach combines:
Data-driven analytics that expose the friction
Strategic services that solve the root causes
AI-powered automation that accelerates everything
It's not hype. It's durable, sustainable change.
We're Not Trying to Disrupt the Revenue Cycle. We're Reinventing It.
Buzzwords are easy. Reinvention takes work.
However, the payoff is worth it: faster payments, fewer errors, better utilization of your team's time, and increased visibility into your performance. We're not trying to be an AI company. We're striving to be the partner that helps you build a more efficient revenue cycle—with the tools, talent, and technology that drive results.
So yeah, now we're all in on AI.
Because we finally have the right foundation to make it matter.
