How AI is changing our finance operating model

Airwallex’s Finance team is restructuring its approach to AI by combining distributed experimentation from domain experts with centralized standards for developing, testing, and scaling automation. Early citizen-development efforts enabled finance staff to create useful tools, such as journal-entry and payroll-consolidation applications, but many prototypes stalled before production, duplicated work, or remained dependent on their original creators. To address this, the company hired a finance engineer reporting to the CFO to establish shared practices for prioritization, product readiness, testing, and reusable AI workflows, while retaining domain experts as the source of automation ideas. The team aims to move beyond dashboards and human-assisted applications toward triggered and end-to-end API-based workflows, recognizing that such systems require rigorous handling of edge cases and broader product-management skills. Its development process now emphasizes rapid MVP delivery, cross-regional testing, centralized repositories for agent skills and tools, and global adoption, while targeted hiring, including in tax automation, is expected to generate substantial savings. The approach frames AI transformation primarily as a leadership and organizational challenge, with success measured by whether teams trust and consistently use scalable tools rather than maintaining parallel manual processes.

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