Michael O'Loughlin is joining me from Argonautica, and he's also the US Ambassador to the MENA Fintech Association. Michael, welcome back to the show. Thanks so much for joining us today.
Good morning. Really good to be back.
So this is a topic that everyone has been talking about. Let's talk a little bit about the cycle that we're in right now. There's a lot of noise still, and we're early, but we're moving into this real implementation stage. So where are we in this stage — and walk us through what exactly this whole thing means?
I think you hit the nail on the head that we're moving from hype to implementation. Now, what does that mean? Even that phrase sounds like a Dilbert cartoon. I think what we're actually moving is from demos — moving beyond demos to proof of concepts and pilots. And now we're actually seeing that it does work, but trying to find the perfect use case. So the implementation piece is where we're going to see the last two years of being very much around: does it work? Can we try different tools, try different pieces, almost sitting on the outside. Now it's time to embed.
So for the investors watching this morning — how do you separate a real opportunity from what people are calling AI tourism? Bolting on from a pitch deck without really looking underneath it all.
That's a good question. I think a lot of people, when they look at what you just asked, they want to know: is this actually helping us make better decisions? Because at the end of the day, nobody wakes up in the morning wanting to use AI — they don't think about it that way. Marketing 101: the creation of a need that was never there before. But if everyone's talking about it, people are getting more curious. And I think that's the major shift — the curiosity piece. But now we're seeing more and more that boards are actually wondering what happens next. We've given you an awful lot of money. You've asked for the money. The budgets have been expanded. We want to see a return on the investment. So they're getting a little bit impatient about where the value is being added. Is it helping us make faster decisions? Is it helping us make more money, save more money? These are the questions being asked in the banks right now, specific to financial services.
Financial services is very well known for not being forgiving — the margin for error is tiny. Walk us through why that environment is so demanding, and why it's actually pushing more companies to succeed and add value rather than less.
I would look at it slightly differently. If AI gives you a poor movie recommendation, or sends you to a restaurant where you didn't enjoy the meal, you can forgive that. But in the world of financial services — where compliance, risk, and reputation are paramount — you're going to end up in situations where you might send millions of dollars to the wrong person, or approve the wrong credit rating, or approve a loan that shouldn't have been approved. These margins for error are not forgiving. For that reason alone, banking just won't put up with 99% accuracy. And I think as an investor, we're looking at all these companies right now and asking ourselves: will they be here next year? Will they be sticky? Will they embed themselves in the workflows? And back to the banking question — why is it not forgiving? They have systems that work today. The old "if it ain't broke, don't fix it." If they're bringing in new technologies, they really want to know that they're going to work long term too.
So where are the most compelling opportunities — both here in the States and over in the Gulf?
The Gulf is renowned in recent years for building new, cutting-edge infrastructure and adopting new technologies, while here in the West we're very much modernising legacy technology and legacy infrastructure. There's nothing wrong with either approach — it's just where we're at. But the real opportunities to leverage AI right now in financial services are in compliance, risk management, and capital markets workflows — and actually embedding them deep.
When we talk about AI in finance specifically — what are investors and funders getting wrong about it right now, given all the noise?
I think many people are overestimating the models and underestimating the distribution factor. AI adoption is the difficult piece of the puzzle. We're going to see that while we look at the models as the be-all and end-all, getting beyond the political nature of AI in large organisations — where different siloed teams are using different workflows — is going to be a major pushback. And I think that's where the companies that get it right will actually focus on the adoption piece. You can build smart AI. Not anyone can do it, but the people who build smart AI and focus on the adoption piece — which is the last mile — they're the people who are going to win long term.
AI is part of our everyday life now. Where is the future of this in finance — and how do you continue to implement it without losing money? What advice would you give investors watching today?
I'm in a slightly privileged position. I'm part of a company that has been investing in small language models really focused on industry-specific applications — in this case, financial services and fintech. If I look at that pillar of Argonautica and what we do, we're very much focused on: will this company be useful, needed, and embedded? These are the important questions. Meaning — will their clients need them next year? Can they remain sticky and useful? Can they add value beyond year one?
If the answer is obvious that they're going to be discarded after one year because AI is advancing at such a pace, that's a problem. But if they can add value from day one — really helping with the decision-making process in areas like risk management, compliance, and capital markets workflow management — and then continue to build on what they're learning from the data within the organisation, they can keep adding new products over time.
A lot of startups just focus on trying to sell into larger organisations. They have this tendency to show up and throw up — meaning they arrive and give away everything from the word go. But what we're noticing as investors is that it's the companies that add value with one piece, get inside, and then continue to build value over the years that win. And they can only do that through, again, the adoption piece.
It's fascinating to see what's going to happen in the future — and honestly, in the next couple of months. This thing is just moving so fast. It's definitely exciting to see it unfold. Michael, thank you so much for joining us. I appreciate your time today and all your insight — it's always fascinating.
Great to be here.
