Your AI scale-up's finance function can't keep pace with growth – here’s what you need to do

AI companies are scaling to revenue heights we haven't seen since the dot-com boom. Some businesses barely two years old are hitting over £100m in annual recurring revenue. While that speed is impressive, the problem is that financial operations lag behind on systems never designed for this kind of rapid growth.

I spend most of my time speaking with founders and finance leaders at AI scale-ups, and I keep hearing the same story. You've built something genuinely innovative, secured impressive funding rounds, and you're hiring rapidly across multiple markets. Then, almost sheepishly, you'll mention your financial infrastructure is "a bit chaotic."

The reality is usually worse than you're letting on.

Are you on the typical scale-up finance journey?

Every successful AI company starts the same way, and many enjoy this trajectory: brilliant idea, initial funding, and rush to build the product. In this whirlwind, financial infrastructure slides down the list of priorities, which is understandable to a point.

Here's what typically happens. You start with basic off-the-shelf products that work well enough initially. A business account from a high-street bank. One tool for expenses. Another for vendor payments. A third for international transfers, and, last but not least, a billing tool.

Then the company grows quickly. You need to pay a development team in Estonia, open a sales office in London, and expand into APAC via Singapore or Hong Kong. Each geography brings an additional banking relationship, a new payment provider, and fresh compliance requirements.

Before you know it, you've got six different platforms, each solving just one piece of the puzzle. What began as practical solutions has spiralled into a complex web of disconnected systems. If this resonates, read on.

Why your AI company faces unique pressures

The challenges become particularly acute for AI companies experiencing hyper-growth. Investments in generative AI jumped to $56 billion (£42bn) globally in 2024, according to Tech Crunch – a 92% increase from 2023's $29bn (£22bn).

Closer to home, British AI startups raised over $1bn (£750bn) in Q1 2025 alone, Tech Nation calculates, representing the largest first quarter in three years. By mid-year, that figure had reached $2.4bn (£1.8bn), representing 30% of all UK venture capital investment.

Unlike traditional SaaS companies that might spend years building presence in a single market, AI companies often need to go global almost immediately. Customer demand emerges simultaneously across multiple regions. Investor pressure to scale quickly while maintaining tight control over cash burn creates a perfect storm.

You're facing pressure from two directions. First, your investors expect you to know your burn rate, cash projections, and runway at any moment. Second, there's operational reality. You're hiring quickly across Singapore, London, and San Francisco – all needing payment in different currencies. Engineers are buying credits from OpenAI. Your cost structure looks nothing like traditional software economics.

What traditionally took three to five years now takes 12 months. The finance infrastructure that worked for 10 people at a low-revenue base simply can't handle 200 people across many continents and multiple million revenue flows.

When do spreadsheets become your worst enemy?

A high majority of early-stage founders don't have finance backgrounds. Your job is driving vision and building product. You cobble together systems that just about work.

The upshot is you're building complex lookup models in Google Sheets to answer basic questions. How much cash do we have? What's our burn rate? How long is our runway?

Jack Zhang, our CEO at Airwallex, captured this perfectly in a recent LinkedIn post. He wrote: "CFOs still stitch together dashboards, spreadsheets, and tools just to answer: Where's my cash? What's my burn?"

These shouldn't be difficult questions in 2025. For AI scale-ups juggling multiple entities and currencies, they genuinely are.

The four hidden costs eating into your growth

The impact of fragmented financial systems goes beyond operational hassle. When you inherit this patchwork, you face challenges that directly affect company growth.

1. You're flying blind

Without a single source of truth for company spend, making informed decisions about resource allocation becomes nearly impossible. AI companies are expanding into diverse sectors. In Q1 2025, nearly half of all healthcare venture capital in the UK flowed into AI-driven startups, according to HSBC research. Each new vertical brings fresh complexity.

2. Hidden fees are draining your runway

You're losing thousands because each regional office and customer base has its own payment solution. I've spoken with founders who discovered they were paying for duplicate software subscriptions across different offices. No single system tracked everything. And don’t be that team that bills everyone in the HQ currency – efficient currency management is a sign of financial maturity.

3. Your finance team is drowning

Your finance team spends 60% of their time on reconciliation and firefighting when they should be forecasting and optimising budgets. Others have found vendor invoices processed twice, or critical payments delayed.

4. You can't answer the questions that matter

The UK market shows signs of maturity. Average pre-money valuations for British AI companies now stand at £16.6 million, with investors taking average equity stakes of 15.6% per round. They're looking for companies that can demonstrate both growth and control.

When you're preparing for your next funding round and can't quickly answer investor questions, you've got a serious problem.

What does future-proof financial infrastructure actually look like?

As of April 2025, the UK had over 2,300 AI companies, according to Beauhurst, with an estimated 240 qualifying as scale-ups. 

Success is coming to companies that can move quickly while maintaining control. That requires finance systems that provide real-time visibility, automate busywork, and scale as you grow.

Jack's observation about the evolution from SaaS to AI feels relevant here. As he put it: "SaaS gave us visibility. AI gives us velocity."

Traditional SaaS tools digitised finance but didn't actually run it. The next generation will be different. Autonomous systems that handle reconciliation, forecasting, and payments without constant human intervention.

But you can't build autonomous finance on top of disconnected systems.

For AI scale-ups, the question isn't whether to modernise your finance stack. It's when. Most companies wait until the pain becomes unbearable – preparing for a funding round, losing track of spend, finance team threatening to quit.

By that point, fixing the problem while keeping the business running is like replacing your car's engine while driving down the motorway.

The alternative is to treat financial infrastructure with the same urgency you apply to product development. Ensure robust systems are in place early, before they limit your growth.

Ultimately, your competitors are scaling quickly. Don't let your finance function be what holds you back.

At Airwallex, these conversations with AI scale-ups have shaped how we think about modern financial infrastructure. We understand that solving these challenges requires more than piecemeal solutions. In my next piece, I'll explore what a unified financial platform built for global scale actually looks like – and how the best AI companies are getting ahead of these problems before they become critical.