What do you see as the most significant opportunities to harness AI in treasury?

I believe the biggest opportunities come down to five key areas. I like to think of them as the fingers on one hand, each playing a unique role, but working best together:

• The thumb, which gives your hand strength and control, represents cash flow forecasting – something every treasury team relies on. AI can increase the accuracy of forecasts with real-time data and trends.

• The index finger stands for team productivity. Tools like robotic process automation (RPA) can handle repetitive tasks, and Generative AI can help us document and improve our workflows, saving time and reducing errors.

• The middle finger symbolises risk management. In an unpredictable world, AI-powered algorithms help us spot risks early, test scenarios, and respond more quickly when things change.

• The ring finger is about compliance. AI solutions can help us stay on top of different tax rules, regulations and KYC checks, especially when operating across multiple countries.

• The pinky, small but mighty, stands for payment fraud detection. AI algorithms can quietly monitor payment activity in the background and alert us to anything unusual.

Are you planning to use AI in your treasury?

For us, AI in treasury isn’t just a future concept – it’s an active and evolving part of our journey.

Following our spin-off four years ago, we had the unique opportunity to build our European treasury from the ground up. Initially we took a pragmatic approach – keep things simple, manual, and focused on establishing solid foundational processes. This gave us a valuable proof of concept, and a clear view of where the bottlenecks and opportunities lay.

We’re now moving into a transformational phase, where AI is positioned to play a central role in how we evolve. Our immediate focus is on improving the accuracy of cash flow forecasting using predictive analytics. In a fast-moving and margin-sensitive industry like logistics, where payment terms and customer behaviours can vary significantly, forecasting can be especially challenging.

We’re also beginning to explore how AI can help detect payment anomalies and fraud – a critical area for any treasury managing high transaction volumes across regions. By using AI to monitor for outliers and suspicious behaviour in real-time, we aim to move from reactive to proactive risk mitigation.

Alongside forecasting and fraud detection, we see exciting opportunities to leverage AI in dynamic discounting and payment prioritisation, which could enhance our cash conversion cycle and further improve working capital efficiency.

We’re still in the early stages of implementation, but we’ve laid the groundwork. We use Kyriba as our treasury management system and are partnering with Actualise Consulting to co-develop a predictive cash flow forecasting model that will blend internal financial data and external market indicators.

What do you see as the main barriers to adopting AI in treasury?

One of the biggest challenges we face is data – not the lack of it, but the condition it’s in. Treasury teams often work with data spread across multiple systems, in different formats, and at varying levels of accuracy. Before AI can do anything meaningful, we need to get that data clean, connected, and consistent.

Then there are issues like change management and skills. Let’s be honest – introducing AI into treasury means more than just installing a new tool. It’s a mindset shift. And while treasury professionals are experts in finance and risk, most aren’t trained in AI or data science.

Finally, cost and complexity can be real barriers, especially when you’re starting out. AI tools often need customisation, integration with existing systems, and a period of trial and learning. The ROI is there, but it may take time to show up on the balance sheet. In tight budget environments, that can make initial investment a harder sell.

What advice would you give other treasury teams seeking to adopt AI?

Adopting AI in treasury doesn’t have to be overwhelming! You don’t need to dive into complex technology right away – just start small and look for areas where AI or automation can make your life easier.

Start by pinpointing one or two pain points. Maybe cash flow forecasting is a challenge, or you’re spending too much time reconciling payments. Then try a pilot project first. This keeps things manageable, lets you experiment, and helps build confidence across the team.

You’ll want to bring your team along for the journey. AI isn’t just about technology, it’s about people. Investing in a bit of training, like basic data analysis or even data visualisation tools like PowerBI can go a long way. You can also work with your IT, compliance, and risk colleagues to make sure everything is secure and aligned.

Most importantly, don’t be intimidated. AI isn’t here to replace treasury professionals, it’s here to help us work smarter. The future of treasury belongs to those who can blend the best of both worlds: technology and human insight.