AI has a context problem

AI adoption in finance is constrained less by model capability than by fragmented data, workflows, and infrastructure that prevent systems from accessing the trusted context needed to execute decisions autonomously. A Forrester Consulting study commissioned by Airwallex in June 2026 found that only 11% of finance workflows operate without human intervention, while 65% of finance leaders identified inconsistent data and 61% cited cross-region and entity integration complexity as barriers to scaling AI. The piece argues that autonomous finance requires a unified view of balances, transactions, approvals, entities, and settlements, alongside governed workflows and operational infrastructure such as licences, payment rails, and security controls. It compares the shift to electrification, suggesting that organisations gain the most when they redesign underlying operations rather than merely add new technology. Airwallex presents its global licensing and payment-network infrastructure, as well as Minor Hotels’ reported US$7 million annual savings from consolidating payments, as examples of how integrated platforms can reduce complexity while creating the data foundation needed for secure AI-driven financial operations.

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