Part of the SYNAPSE 2026 series | Rob van der Woude, Chief Tax Officer, Fonoa | Rhodah Nyamongo and Richard Stern, WUGTPC
Most businesses are still working out how to use AI in their tax operations. The question they are asking is: how do we get there? It is a reasonable question. But it misses something more urgent. Tax authorities in many markets are not figuring out how to use AI. They are already using it, and they are using it to analyse your data.
That was the starting point for one of the most thought-provoking sessions at SYNAPSE 2026, Fonoa's annual conference for indirect tax professionals. Rob van der Woude, Chief Tax Officer at Fonoa, was joined by Rhodah Nyamongo and Richard Stern from the World University Group on Tax Policy and Compliance (WUGTPC), bringing a perspective from the authority and policy side that reframed the urgency of getting tax data right.
Here are some of their top insights:
1. The volume of data flowing through tax systems can’t be processed manually
The scale of global transactional data has grown beyond what any manual review process can handle. Cross-border transactions, e-invoices, and digital reporting submissions are arriving continuously, across hundreds of jurisdictions, in formats that vary significantly by market. Tax authorities that want to stay effective have had to find a way to make sense of it all. AI is that way.
By 2030, multiple core tax authority functions are expected to be AI-powered as standard. That is not a distant ambition. It is the direction authorities are already moving in, and it has direct implications for every business filing in those markets.
2. The tax function is not changing. The way it is processed is.
Richard Stern offered the clearest framing of what this shift actually means for businesses:
"Tax functions are staying the same. It's the way of processing it that needs to be reimagined." — Richard Stern, WUGTPC
The compliance obligation has not changed. What has changed is the speed and sophistication with which authorities can identify discrepancies and act on them. A mismatch that might previously have taken months to surface through a manual audit can now be flagged in the time it takes to process a filing. Businesses that assume they have time to find and fix data issues before an authority does are working with an outdated mental model.
3. Up-to-date digital systems are no longer optional
The practical implication of operating in an environment where authorities are running AI on your data is straightforward: your systems have to be current, your data has to be accurate, and you need to be able to explain the reasoning behind your decisions.
Keeping digital systems up to date is non-negotiable. Methodology changes need clear rationale behind them. And the data submitted to authorities needs to be consistent across every system it touches, because inconsistency is exactly the kind of signal that automated analysis is designed to detect.
The session also made the point that this shift is an opportunity as well as a challenge. Businesses that build robust systems and clean data infrastructure are not just protecting themselves from scrutiny. They are building the kind of trust with tax administrations that makes compliance a more straightforward, lower-risk part of doing business over time.
Bottom line: If your data tells different stories in different places, AI will find it
The businesses that will find AI-powered tax authority scrutiny most disruptive are the ones whose data does not hold up to consistent analysis. The ones that will not are the ones that have already done the foundational work: clean data, current systems, and a clear audit trail behind every decision. The question is not whether authorities will look closely at your data. It is whether what they find reflects the business you are running.
