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Building a resilient technology company is hard. Building one that can withstand constant policy change is another level of hard. Right now, companies across sectors—not just fintech—are staring down government and regulatory shifts happening faster than most orgs can process, let alone implement.
For industries like financial technology, where regulatory changes directly impact how products work, how they’re priced, and how they’re sold, the stakes are existential. Adapting in real time isn’t just an edge—it’s the bare minimum to stay in the game.
That’s why companies need to think beyond using AI as a tool. They need to rethink the entire way they build software, make decisions, and operationalize compliance. At april, we didn’t bolt AI onto our dev team; we restructured how we work to make regulatory agility the foundation. Our approach uses AI to take human-written analysis and turn it directly into code. It means faster updates, fewer silos, and a dev cycle that actually moves at the speed of policy.
When every state writes its own rules, you build for change
The U.S. tax system isn’t a single rulebook—it’s a fragmented, constantly shifting web of federal and state-level regulations. Each year, we see hundreds of changes across jurisdictions: new credits, sunset clauses, redefinitions of income, filing thresholds, and form logic. And none of them arrive on a predictable timeline. A change that passes in October still needs to be implemented and tested before filing season begins in January.
We knew we couldn’t keep up with that kind of churn using the legacy software development model most incumbents rely on—long handoffs between policy, legal, and engineering teams, often stitched together manually. So we built something different.
At april, our Tax-to-Code system lets policy experts write structured analysis, and generative AI turns that into functioning software, reviewed and refined by engineers before it ships. The AI doesn’t replace experts; it extends them. It kills the back-and-forth and accelerates our response time from weeks to days.
This is what regulatory agility looks like: Tax code changes go from policy to product without bottlenecks.
Automation isn’t the goal—strategic bandwidth is
There’s a lot of noise about AI automating work. But in regulated environments, the real value isn’t just speed—it’s the space it frees up for experts to focus on strategy.
AI helps us eliminate the repetitive, time-sucking tasks that bog down compliance work. That doesn’t just cut costs; it gives our team the bandwidth to think several steps ahead. What’s the next policy change likely to be? What would it take to adapt? What needs to be built now to stay ahead?
That’s what most companies are missing. They’re spending all their energy reacting. AI infrastructure, done right, gives you the room to anticipate.
AI can’t function without the right architecture
This only works if your infrastructure is designed to support it. We didn’t start with generative AI—we started with the assumption that regulatory change is constant and unpredictable. From there, we built a system where:
- Domain experts define the logic.
- AI transforms it into code.
- Engineers validate and ship.
The result? A feedback loop where tax and policy changes get implemented at pace, not after a six-month dev sprint.
More importantly, it’s adaptable. This model isn’t just for tax. Any company in a volatile regulatory space—health insurance, auto, logistics, energy—needs a system that can cascade policy changes through their tech stack fast, accurately, and with oversight.
Lessons for leaders in regulated industries
If you’re leading a company where compliance is high stakes, here’s what to prioritize:
- Structure your tech org for change, not stability. You can’t assume next quarter’s rules will match this one’s.
- Build collaboration between experts and AI. Don’t let legal, ops, and engineering operate in silos. AI works best when it sits between human knowledge and execution.
- Focus on speed and oversight. AI without accountability is dangerous. Human-only systems are too slow. You need both.
This is the new baseline
In today’s environment, adaptability is non-negotiable. Leaders can’t rely on manual processes or slow engineering cycles to keep up with real-time policy shifts. And AI isn’t some magic solution on its own; it needs the right infrastructure, the right workflows, and the right people in the loop.
At april, we’ve built our company around that reality. That’s how we move fast without breaking things—and how others in high-regulation industries can, too.
Ben Borodach is the cofounder and CEO of april.