The Compliance Challenge Has Become An Engineering Problem. AI Can Help You Solve It

Danny Fields, Chief Technology and Customer Operations Officer Avalara, an agentic AI leader in global tax and compliance.

​When I talk to technology leaders about global trade compliance, I tend to get one of two responses. Either their business has already faced disruption—shipments held at customs, a refund claim that cascaded through the financials, a market entry delayed by months because the regulatory environment shifted—and they’ve been handed a mandate to make sure it doesn’t happen again. Or they haven’t, and the mandate has arrived anyway.

Either way, the message is the same: Compliance is no longer a problem that finance teams can manage through spreadsheets and experience. It’s now an engineering problem that can be solved with AI.

The volume, velocity and interconnectedness of global regulatory change has crossed a threshold where human experience alone can no longer keep pace. Tariff schedules update. HS classification rules shift. There were more than 417,000 taxability updates across the U.S. and Canada alone in 2025, according to the Avalara Tax Changes 2026 Midyear Update.

Then add in the transactions themselves subject to those changes. Over five days of Cyber Week last year, we processed 1.14 billion API calls, representing $187 billion in tax transactions and peaking at 9,124 transactions per second. The moment a compliance decision needs to be made faster than a person can make it, at a scale no team can match, across a level of complexity no spreadsheet can model, is when you’ve crossed from a compliance problem into a systems architecture problem.

Regulatory volatility is redefining risk in cross-border trade.

Consider what this means in practice for classification alone. The World Customs Organization updates Harmonized System (HS) codes on a five-year cycle, but country-specific tariff rates tied to those codes can change multiple times a year, and in the current environment, they are.