I recently sat down with the team at Nilus for their Treasury Leader Spotlight series to talk about one of the biggest shifts I’m seeing in treasury and finance right now: how AI is changing not just what we do, but how we think.
From freeing up time to focus on people (instead of admin) to empowering teams to become “strategic translators” between finance, data, and tech – AI is amplifying the human element of treasury, not replacing it.
It was a great conversation where I shared real-world examples from treasurers at NASDAQ, ASML, and Agrocorp, and why I believe the real opportunity lies in uncovering the hidden talent already sitting inside your team.
You can read the full Q&A below 👇
What happens when AI stops being a tool and starts changing how treasury teams actually think?
For Mike Richards, CEO of The Treasury Recruitment Company and host of The Treasury Career Corner podcast, the shift isn’t just coming, it’s already here. In this edition of our Treasury Leader Spotlight, Mike gets real about how AI is redefining the DNA of finance and treasury roles, from uncovering overlooked talent to championing a new kind of professional: the strategic translator. His answers reveal how AI isn’t just speeding up workflows, it’s shifting mindsets.
What’s one way AI has already changed how your team works?
AI hasn’t just changed how we work – it’s changed what we value.
For me, AI has helped reframe where we spend our time. As a recruiter, that means less time manually filtering CVs or chasing admin and more time having real conversations with candidates and clients. Just like treasury teams automating reconciliations or FX hedging, we’ve used AI tools to streamline repetitive tasks – so we can focus on building relationships, not processing data.
And I’m seeing the same shift in the clients I work with. At NASDAQ, Dana Laidhold’s treasury team uses bots to execute FX trades, generate journal entries, and complete in 20 minutes what used to take days. That time-saving unlocks the real value: deeper analysis, better decision-making, and more impactful conversations across the business.
AI hasn’t replaced the human element – it helped amplify it.
What’s the biggest shift you expect to see in finance and treasury over the next 5 years?
The rise of the “strategic translator.”
We’re already seeing treasury evolve from operational to strategic. But over the next five years, I believe we’ll see treasurers expected to sit at the intersection of finance, data, and tech – acting as translators between business objectives and AI capability.
That doesn’t mean hiring an army of coders. It means having people who are curious, tech-aware, and confident enough to ask: Can we automate this? Is there a better way?
Craig Jeffery at Strategic Treasurer calls this the rise of the “strategic translator” – and I think he’s spot on.
The future treasury professional won’t just know cash positions. They’ll know how to leverage AI tools to forecast them, explain the outputs, and challenge the assumptions behind them. That shift is already starting – and it’s only accelerating.
What do you wish more CFOs or treasury leaders would stop ignoring?
The hidden talent already sitting in their team.
Too many leaders think adopting AI means hiring a new skill set from scratch. But in reality, the skills are often already there – they just need room to breathe.
At ASML, a two-person team built a Python-based forecasting model that beat their manual one by miles. No external vendor, no seven-figure budget. Just two curious people and the space to test something new.
I’d love more CFOs to stop thinking of AI as a “technology project” and start treating it as a “people empowerment opportunity.” Give your team the time and tools to experiment.
Encourage them to explore. The best ideas often don’t come from the top – they come from the people closest to the process.
If you had a magic AI assistant for finance, what would you ask it to do first?
“Sort out the data mess.”
Ask any treasurer what slows them down – and 9 times out of 10, it’s data.
Disconnected systems, messy spreadsheets, inconsistent formatting, manual inputs – it’s like a digital jigsaw puzzle with half the pieces missing.
If I had a Corporate Treasury AI assistant, their first job would be to harmonize and map data across all treasury functions.
Pull in ERP feeds, bank data, cash positions, hedging exposures.
Then clean it, structure it, and make it ready to read and understand for the Treasurer.
AI is only as good as the data feed.
We need to fix the foundations first and then the rest becomes much easier – faster decisions, better forecasting, and more clarity all-round.
What’s the biggest misconception you think people have about AI in finance?
That it’s only for big budgets or big teams.
This one drives me mad.
AI is not just for the Google’s and JP Morgans of the world.
Companies like ASML and Agrocorp have shown you can do a lotwith a little.
At ASML, they built a forecasting tool using open-source Python and in-house talent and won an award for it too!
At Agrocorp, they’re using AI for reconciliations and FX management – no outsourced consultants were needed.
The misconception is that AI adoption is some monumental project. In reality, it often starts with a single use case and a single person asking, “What if?”
You don’t need a data science team – you need a culture that values experimentation and supports smart problem-solving. That’s where the real transformation happens.
