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employee, and every reporting obligation simultaneously. I’ve seen this play out in three specific places consistently. Wage code mapping is still mostly manual. Teams export lists, read descriptions, rely on institutional memory, and hope the person who set it up three years ago documented their reasoning. With STP Phase 2 already here and Payday Super arriving on 1 July 2026, the same pay element now needs to be classified correctly across multiple regimes at once. Automation doesn’t solve that upstream problem. It inherits it. Reconciliation across payroll, STP, and payroll tax surfaces variances. What it doesn’t do is explain them. And explanation is exactly what regulators are looking for. A Big 4 firm demonstrated what’s possible when it analysed over 3.2 million payslip records for a single Australian employer, identifying underpayment issues that manual review couldn’t have surfaced at that volume. But that capability isn’t being applied consistently to the employment tax reconciliation problem, where the need for a clear, explainable story exists every single reporting period.
Reconciliation across payroll, STP, and payroll tax surfaces variances. What it doesn’t do is explain them. And explanation is exactly what regulators are looking for.
Our 2026 State of Payroll Compliance Report, surveying 540 Australian payroll and business decision-makers, found 77% of organisations now use AI or automation in some form for payroll compliance. That number tells you automation is no longer report also found. Only 64% of those organisations reported full confidence that they were paying employees correctly. Automation is everywhere. Confidence isn’t. That gap is where the real conversation needs to start. Where Automation Stops Short Automation follows rules. It does exactly what it’s told, which means when the underlying classification is wrong, optional. It’s infrastructure. But here’s what that same automation scales that error across every pay cycle, every
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GLOBAL PAYROLL MAGAZINE ISSUE 24
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