Building the future of global finance in the age of AI
Shannon Scott
Chief Product Officer, Airwallex
Financial teams today are under tremendous pressure. CFOs and other financial leaders are dealing with an incredible volume of transactions – payments, payroll, reimbursements, and general spend – while trying to keep pace with evolving regulations, monitor employee behaviors, understand vendors, and ultimately make sense of financial data.
What it really comes down to is legibility. As more inputs flow into the financial leader’s world, many are struggling to actually understand their cash flow and distill it in a way that ensures the business is operating in a very healthy way.
As if that weren’t challenging enough, there’s the question of AI and how you’re successfully deploying it.
AI is moving faster than any previous technology wave, and finance leaders are doing what they can to adapt to the moment; however, most are trying to work with AI on top of legacy systems. For 50% of finance leaders, the default response to global finance challenges is to patch workflows rather than re-evaluate the underlying systems.* But bolting AI onto legacy tech fundamentally misunderstands the opportunity.
To truly move faster, finance leaders don’t just need AI tools for their teams. They need the infrastructure, operating system, and intelligence layer to work as one.
AI doesn’t operate in a vacuum
Across the world, AI adoption in finance has leaped more than 600% in the last year alone. Copilots, dashboards, and agents suggest a future where finance becomes more automated, intelligent, and responsive. But beneath the surface, most financial operations remain deeply fragmented.
AI can summarize and optimize workflows, but it can’t fix fragmentation on its own. If your banking, payments, and financial data are disconnected, AI is working with an incomplete picture. This leads to misinformed decisions and missed opportunities.
More importantly, ad hoc AI innovation leaves financial leaders grappling with the same questions: How do I make sense of this torrent of inputs? Is the firm financially stable? Am I deploying capital effectively? With legacy systems, answering those questions often requires large teams, manual consolidation, and significant effort.
Infrastructure enables AI to put cash flow into context
AI doesn’t operate in isolation; it amplifies whatever system it sits on. And most financial infrastructure today is built to process transactions, not actually understand them. It knows what happened, but not the why behind it.
That missing context is critical – because the future of finance isn’t just about blindly automating. It’s about powering autonomous, context-aware decision-making. On its own, AI can’t bridge the gaps created by regulatory complexity, licensing issues, and slow or expensive global financial rails.
These are foundational constraints. Legacy systems put a cap on speed, visibility, automation, and overall operational agility. But when infrastructure, software, and AI are vertically integrated – when they work as one – something fundamentally different gets unlocked. Namely, a single source of truth for global finances. That means full visibility across entities, currencies, and workflows. Now you’re giving AI a wealth of knowledge to work with.
It’s the difference between AI as a feature and AI as a system-level advantage.
Two paths to AI adoption – and where they lead
AI is rapidly automating knowledge work across finance. But how companies adopt it is starting to create a meaningful divide.
For many, the approach is incremental: layering AI tools onto already fragmented systems. This may improve individual workflows and deliver quick wins, but it may not address deeper structural issues – particularly a lack of unified financial infrastructure.
When AI operates on incomplete or disconnected data, it can surface insights that appear accurate but lack full context. Decisions may get made faster, but not necessarily better.
Other companies are taking a different approach. Instead of retrofitting AI onto legacy systems, they’re rethinking the foundation – designing for global, real-time financial operations from day zero.
The difference becomes clear in moments of volatility. When markets shift – whether due to FX movement, regulatory changes, or supply chain disruption – finance teams need to act with speed and precision. That requires real-time visibility, coordinated systems, and the ability to move capital seamlessly and cost-effectively across entities and currencies.
Short-term AI adoption optimizes for speed within existing systems. Long-term thinking builds systems that are intelligent, adaptable, and fast by design.
Where AI executes, humans will become more strategic
The future of finance is indeed autonomous. But it’s not about replacing humans; it’s about redefining how the work happens. For instance, today, even a single transaction can involve a complex chain: vendor onboarding, invoice matching, approval workflows, payment execution, and reconciliation.
Each step is manual, which means each step risks losing context. AI agents change this. They operate across the chain – each with a defined role, clear context, and specific responsibility. They can validate vendors, match invoices, optimize payment methods, detect anomalies, and prepare transactions, all while presenting that context to a human for final verification and control.
At Airwallex, we talk about this as the shift from descriptive to predictive finance – from reporting what happened to anticipating what will happen next. AI doesn’t replace finance teams; it gives them superpowers, enabling faster decisions, deeper insights, and more strategic impact.
Modern finance leaders don’t want to think about payment methods or fragmented systems. They want one platform that works globally from day one. This is where infrastructure becomes so important. Because infrastructure – not features – determines how efficiently and strategically a finance team can operate worldwide.
How Airwallex enables autonomous finance
This is exactly where Airwallex comes into play. We’re bringing AI to our customers through a vertically integrated financial platform where infrastructure, software, and AI work as one. We’ve built:
Global financial infrastructure (accounts, transfers, FX, cards, payment acceptance, yield)
Integrated software (spending, billing, workflows, automations, reconciliation)
AI layered across both
This creates a single source of truth for your company’s global finances that tracks every inflow, outflow, and approval flow – across every entity and currency. And that foundation enables something others can’t: AI that operates with full organizational context, rather than fragmented data.
We’re already building toward this future. Among other capabilities, Airwallex’s AI helps manage treasury decisions, validate compliance, optimize payment routing and FX exposure, and automate expense management and reconciliation.
Intelligent global finance is no longer theoretical – and Airwallex is turning AI-native infrastructure and software into real, tangible gains across payments, treasury, and spend for companies across the globe.
Sources:
Airwallex report: Global financial operations. (2026).
Shannon Scott
Chief Product Officer, Airwallex
Shannon is responsible for Airwallex's product strategy and roadmap, spanning financial infrastructure, business software, and embedded finance solutions.
