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The HC Commodities Podcast
Techno-Barbarians at the Gate: AI is coming for your operating model with Eren Zekioglu
00:49:34
AI is already changing commodity trading operating models. And unlocking adjacent technologies such as digital assets and DeFI? That itself is changing the competitive landscape and attracting new participants from outside the sector. Where is that investment going? And how profound is this change going to be? And how quickly is it going to be upon us? Our guest is Eren Zekioglu. Eren has spent a career at hedge funds and at trading houses and at the intersection of trading, operations and technology, including at Glencore and Gunvor.
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Foreign.
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Welcome to the HC Commodities Podcast, a podcast dedicated to the commodities sector and the people within it. I'm your host, Paul Chapman. This podcast is produced by HC Group, a global search firm dedicated to the commodities sector. Today we're talking AI. How is it changing operating models? How is it going to change operating models? And how is it going to unlock adjacent technologies such as digital assets and DeFi, which participants are investing? Where is that investment going and how profound is this change going to be and how quickly is it going to be upon us? Our guest is Erin Zekioglu. Aaron has spent a career at hedge funds and at trading houses and at the intersection of COO and cio, including at Glencore and Gunvor. This is in anticipation of an upcoming piece of work we're doing with the FT's Longitude Group on AI, which will roll out at the FT Global Commodities Summit, which we're sponsoring in Lausanne in April, which is always worth attending and to my mind, the best commodities event of the year. As always, you can really support the show by leaving us a positive review on the platform you're listening on. And as always, I hope you enjoy the episode. Erin, welcome to the show.
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Thank you.
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So we have a bit of a task ahead of us. So the backdrop to this is that HC Group is one of the sponsors of the FT Global Commodities Summit this year. And as part of that, we're also working on a study with their Longitude Group around AI and its impacts today and its impacts in the future on the commodity trading sector. And you're the part of setting the scene primarily because we'll come on to a bit, but your background of kind of spanning operations and technology and trading and being very much at the forefront of digital assets are going to play a role in this. But also thinking more holistically about the technology platforms as it pertains to commodity trading and kind of what the forefront of thinking maybe is. Can you just, I guess, before we go too far, is there any value in defining AI, or are we just going to allow it to be sort of a nebulous idea of just fast algorithms that can learn themselves?
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I mean, in commodities already, I mean, we are using various aspects of AI. You know, if, if you think about AI across our business, most people would probably think it is more, you know, using co pilots or forecasting tools or, you know, using AI to generate trade ideas or even document automation. So, I mean, it's. When we set, when we, when I hear the conversation about AI coming into commodities, I'm like, well, AI is Actually already here, what we're not seeing is probably the, you know, the big reduction that we're all hoping for, but at the moment we're using it for more optimization and improving our processes across a surface.
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Yeah, you say, well, quite off the bat there, you're talking about the big reduction. Is it fair to say that you can kind of pull AI into a couple of different buckets? One is kind of this idea of alpha generation, better decision making, you know, whether that's on sort of long term asset deals or short term trading. And then the other is primarily using gentic AI to speed up processes, reduce the number of times a human has to touch any given kind of work stream. Can you just help us understand and pass those two? And you said reduction there. Is that the main emphasis?
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Well, look, I mean to generate trade ideas in, in the sort of web2 space that we used to have, which we still have took a long time and it took a lot of bodies to do. Now you can put all your trading ideas into various AI tools and it will give you various different scenarios of what you can and can't do, whether you're going to go short, whether you're going to go long and whatnot. And there's a lot of bots that currently do that. I think from the operating model side of a trading company. I think this is where AI becomes a lot more useful in terms of maintaining growth in terms of headcount, but also, you know, increasing our capabilities from a trading perspective. And it's sort of a term that's used quite freely around trading that, you know, AI is going to take a position in terms of a role or AI is going to reduce our headcount. But I really don't see that happening anytime soon because within the commodity space it's still very, very early. There's not enough people that really understand the full capabilities of it one and two, there's an enormous risk element to it as well in terms of legal and compliance. Back before AI was around, we were using algo trading and then when that sort of surfaced was a lot of issues of legal and compliance with a lack of understanding of how this algorithmic trading could actually make decisions before the human could.
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Yeah, yeah. And, and part of the, the study that we, we're doing is trying to understand where AI is today, which key areas it's adding value or not, and then kind of more longitudinally what types of the different categories of organizations and how they're thinking about how it will deliver a competitive advantage or not. You Know, as you see it at the moment, and you've worked obviously at the forefront of technology and operations and operating models for all of these different types of organizations. Do you have any sense of, kind of what language we should be using when we compare but also comparing hedge funds versus trading houses versus let's say asset backed majors, I mean you kind of start from the, the analog world to the algorithmic world to then the AI world. You know, are hedge funds light years ahead of the trading houses who in turn are in light years ahead of the asset back traders? Or is that a, a bit of a cliche and, and not actually the truth? And we should be looking at those different categories and, and we're seeing different strides being made by each.
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Well, I think, you know, with the hedge fund space, I mean the, I would say they are structurally ahead. You know, they were built around models. You know, they were built to compete and compute and you know, if history has taught us anything, they deploy faster, their data is cleaner, their culture is a little bit more web three literate. You know, tracing. Trading houses are probably physical. Trading houses are far more complex. There's a lot of sort of legacy systems rolling around. There's some cultural resistance. There's layers and layers of processes because there's layers and layers of characters and roles within a physical trading house. You know, after execution, you've got the middle officer, you got the risk manager, you've got the credit card, the financing guy, you've got a plethora of layers. And externally obviously you have the ship owner, the inspector, the guy in the storage facility, you've got the broker, you've got the agent that there's so many nuances that you know, trying to implement AI internally also has to be a little bit externally as well because we have so many people involved. So trading houses are, will always be a little bit more slow. But I think hedge funds are far more advanced. For sure. They're running models, we're running operating models and that's a huge difference. And you know, if you look at the sort of the firm like Citadel, you look at, you know, Millennium, you look at, you know, Baliasnik, from what we're seeing and hearing, they're experimenting AI models in parallel with their current operating model today. And anything that looks good, anything that looks safe, it's adopted very, very quickly. But within a trading house, you know, there is a lot of blessings and baptizing that needs to go on from, you know, the compliance guy needs to be comfortable with it, the legal guy needs to Become comfortable with it and more important, that the trader needs to be comfortable that the information they're receiving is accurate. Because let's not forget, you know, AI is really just a newcomer to the game. In the last sort of, you know, three to five years. Trust needs to be earned. And if you look at the way ChatGPT is set up compared to the likes of Grok, it's the hosting of the data and some of the sensitive information that traders are putting into the likes of ChatGPT should not be underestimated because now that full adoption is becoming pandemically widespread with ChatGPT, there is information that could be manipulated with tools like this. We were always on the back foot of, you know, how do we use it? But now it's not like, okay, we need to have knowledge, it's how do we ask for knowledge. And I think that's the way AI has been slightly mislooked at and most people are using it now to plunge in very sensitive information. But, but to go back to your question, yes, I do think the hedge funds are much more intelligently mature when it comes to using AI products for sure.
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Counterintuitively using that description, which I think was very interesting, you've got these hedge funds that are kind of their raison d', etre, if you'd like, is being the middleman between lots of different entities. And you've got some of those are obviously counterparties, some of those are inspection. All these, the bits and the ecosystem that they sit at the heart at and have been very good at, kind of the spider's web within that, you know, is there an argument that kind of, you know, we've got a new rise of traders, the asset backed traders, particularly the NOCs, which have very large internal ecosystems where you're not reliant on external partners also participating in your AI regiment. Does that give them a capacity to leapfrog in some ways the trading houses in this area?
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It does, absolutely. I mean, if you look at most NOCs, you know, they've for them, they're very new into this trading space. And if you look at some of the biggest and greatest NOCs, they've started adopting trading companies in the last sort of five to 10 years. And you know, for them it's very easy to adopt AI technology, blockchain technology from smart contracts and whatnot, because they're starting from zero now. If you look at the likes of some very well known trading companies adopting AI and changing their operating model, it's becoming a little bit more difficult and some very large, well known trading companies have become a bit like a bank in terms of processes is hard to change. There are too many stakeholders now to approve, to test and get this thing rolled out. With an noc, it's, it's, you know, they have, they're starting from a place where you know, their etrm, they could quite easily use various AI tools to automate execution, decision making, execution, run a risk model, do a position in P and L, allocate risk and then move straight over to financing and logistics. So I think the NOC space is probably the most interesting space when it comes to AI adoption for sure. But obviously this puts traders on a back foot as well. If you start looking at some of the hires that are going into the trading community, before it was I need a trader that comes from an engineering background, then that's moved over to I need a trader that understands Python. Now we're looking at, okay, I need a trader that really has had some experience in digital assets, especially AI. So I think the evolution of the requirement is Testament to what NOCs and trading companies are now looking for in order to sort of cement their future.
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And I want to come on to digital assets and DeFi and AI and spend some time on that because there's a continuum there that perhaps, I guess I haven't not quite twigged, but seems like they're accelerants to one another. Just before we sort of, I want to kind of do a bit of a Donald Rumsfeld here, kind of the known knowns, if you like, which is the swirling around at the moment. And part of our survey is right where we're seeing adoption, where we're seeing impacts already of AI and we've kind of touched around a few. Right. So there's trading outcomes, so better trading decisions, better trading execution from AI. Then there's kind of the, the middle and back office piece which I know you believe might sort of collapse and devolve into just one office if you'd like over time. But sort of, you know, obviously the agentic AI, the ability to sit there and prove, evaluate, approve, move through kind of all that piece.
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Yeah.
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And then there's obviously the compliance and the surveillance world about making sure that not only are you surveilling yourself in terms of good actors, but also your capacity to surveil counterparties and perhaps, you know, the very public traffic, you're a loss and now trying to recoup the money might not have happened if you'd had some of these pieces in place. Where, you know, can you just give me some sense on each of those, whether, you know, are we seeing it today? It's in place. You use case is obvious. Hire hordes of sort of AI and Python coders and get Palantir in if you dare and let's get going. Is that all sort of quite vanilla and established?
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Well, I mean, look, if you look at the functions of a trading house, we are all derivatives of the execution of that trade. The trader needs the risk manager, the risk manager needs the middle officer, the middle officer needs the credit card and finance and whatnot. We are all derivatives of that execution. And that information, I think where it sort of historically has always slowed us down is the translation of that data. But, you know, AI is already improving that. And it's obvious with the way we're getting sort of faster forecasts, not just in our market, but also from a macro point of view. And that's something which we've never really had before. You know, that would probably take an army of analysts. But, you know, any trader can cut, paste a moving average trade and stick it into a generative AI tool and it will give it some various long and short options. But, you know, to go back to what you were saying, you're right. Document processing has, has increasingly helped with AI, the compliance monitoring. I think that is where, where AI has helped enormously, you know, where before you would need, and especially in the commodity sector, if you've noticed the muscle of compliance has really built up in the last sort of, you know, five to eight years. And that's because, you know, more checks need to be done, more KYC needs to be done. And if you look at that whole compliance operating model, you know, you'd be going to check on various government websites, you'd be checking LinkedIn, you'd be checking, you'll be scrolling through Web2 to find answers. You know, if I wanted to know some information about HC and Paul Chapman, you know, it would, Web2 would say, right, here's all the information you have and you, all your answers are here. Obviously with AI, the adoption of Web3, your answer is here. Paul Chapman, handsome guy, lives in Texas, entrepreneur of HC Capital. All your information is there. So that really enhances, it really gives sort of compliance, the protein that needs to become very strong and very, very fast. And I think AI has completely changed that operating model. Obviously the backside of that now is how, where is this data going that I'm looking at? Can anyone else see what I'm doing? Obviously it also reduces error freight Optimization is something that is enormously important for the shipping guys. And yeah, no, it's real. It's real and we have much better forecast for it. And it's reduced. AI has definitely reduced our decision time, our execution time, our settlement time, and especially the time it takes to deploy capital, which is enormously important for us.
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The energy and resources sector is experiencing unprecedented changes. To help navigate this change and capture its opportunities, HC Group launched Enco Insights, a global advisory network dedicated to the sector providing senior advisors and subject matter experts to investment and infrastructure funds, law firms and corporates. Enco Insights leverages HC Group's 20 years of connections in energy and commodities to give clients the expertise they need. Need when the stakes are high. And insight matters. Learn more@encoinsights.com all that makes sense to me. I guess the one question I have is on that actual sort of trade idea piece is this where, you know, in the absence of having proprietary data sets, you know, your former shop, gunboard, whatever, it might, you know, it might have some storage tanks or had refineries or whatever it might be that there's data that no one else has and I can use that to make better calls, or is that anathema really in the end, at the, you know, there's no such thing as proprietary data anymore and everyone can figure it out and, and everyone's trade is expressed physically somewhere. And, and actually, you know, the gains so far in AI are speed of execution, yes, but also, and then speed of processing. But there's little to point at in the way of kind of, you know, AI's better at making money, so to speak.
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I think in a paper world, AI is used to make better trading decisions. I think in a physical world, I don't believe right now I'm seeing any evidence of that because, you know, the physical world still has an issue of being transparent. So if you want to fully adopt AI, there needs to be an element of transparency. And the commodities industry has. Transparency really is only useful within the operating model at the front level in terms of execution. Sometimes transparency is not an advantage. So I think, you know, on the paper side, whether you're hedging, I think AI has been enormously successful. Will we ever hear about it? Will anyone actually admit it, to using it? I don't know. I mean, the data science teams that probably the Gumballs and the Trapeguras and the Glencores have would prove me wrong. I think for physical trading, I think the human trader still needs to make the decision. Finally, I think with the way I look at the commodities trader is it's more still web2. It knows where all the information is and you make the decision on which piece of information you want to use. On the paper side it can tell you exactly down to the pinpoint when you should enter and when you should exit. And it could not only do that, but it can also execute the trade for you and it can also bank your profit and loss out of interest on that.
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And this is one of those things, I guess they'll play out over time. But in that world I'm still paying my physical trader for commensurately with the alpha they're generating, the career risk they're taking. In that paper world that person suddenly becomes an executor or non existent. Right. And it's the system that is generating the money and I'm kind of paying the capital owners who are putting their capital at risk. I mean is that a fair statement? Do you, could we. If the physical world goes that way, suddenly actually the physical trader is no longer the Ferrari driver in the, you know, in the company forecourt.
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Yeah, look, I mean I think the way I see it is you become an ambassador of that, of that model. You become an ambassador of the decision. So for me it's the physical trader I don't think will be replaced. It cannot be replaced by AI. It can be enhanced by using AI technology. But in an industry which is still very, very much relationship based, there is a trust issue. So commodity traders need to speak to each other. They cannot just rely on AI generated forecast or decision making. That I don't believe will happen. But I do think by 2030 the full operating model of a trading company of what happens after execution, that's where you'll see the change for a paper trader. Yeah, honestly, I just think you won't need historical old baraboy traders anymore. I think you'll need much more computer science traders for sure. Because look, if you look at trading, the technology companies are much more occupied within trading than we like to admit. You know for years ago trading companies, whether it's hedge funds or commodity traders, they needed technology to improve facts. They needed to be to control headcount. They needed better decisions. They needed for technology, they needed to record. But now in, in this web three space technology companies need commodity companies. They need it to be more powerful. They need their own source of energy. So it's, you know, two hands have now started to clap. So for me it's like the paper trader becomes much more powerful. I think the commodities Trader equally becomes powerful, but not in, not in the same office. The front office will always be more attractive.
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But you're suggesting that middle and back office is going to become quite vestigial.
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Yeah, yeah, there is. No, I don't think, you know, you've touched on it. I don't think there'll be a middle and back office anymore. It's just going to be an office in the same way that, you know, there's going to be no such thing as, you know, defi. It's just going to be called finance. There's that there's no such tokenization won't exist. It's just going to be called as it is. In the same way that, you know, AI won't even be a word. It will just be normal.
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Yeah, yeah, it's just technology.
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Yeah, yeah. It'll just be adopted, you know, in, you know, like when, you know, when we first discovered electricity. Wow, that's amazing. But the use case for it was obviously expanded and very rarely use the word. So I think we're still very early in terms of what AI is going to do to trading. But also if you look at the audience as well, I mean, AI is really only exploded in the last sort of, you know, three to five years. But if you look at the, the people that are the first newcomers of it, they're from a generation which still getting used to it, they really want to use it, they see the power of it. But then the layers behind them is, okay, we have an operating model, a constitution if you like. We can't change just like that. But NOCs that are either starting trading companies or building their own trading desks, they're looking at the traditional commodity traders going, okay, perhaps we can do things a little bit different.
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Well, Jeff Curry said this. I, I kind of asked what, you know, do you think the door is going to close on the number of new entrants? And he said, absolutely not. But you've got to be defi ready, right?
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Absolutely.
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And in reality he was sort of saying, you know, you've got to be able to take, set up a platform that's AI native as opposed to reworking from your existing operating model. And, and that could present a huge opportunity. Let me, let me just, let me do the second part of my Donald Rumsfeld, which is kind of the unknown unknowns and you've touched on a few, which is kind of like, I guess this idea of I can sort of intuitively think and from conversations and being in and around it. Oh, you know. Yes, Agentic AI could, you could pretty much figure out LNG spot cargoes because you've got a lot of known, you know, variables around, you know, port depth and storage capacity, you know, all this kind of stuff.
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Right.
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I guess the trying to sort of ask the hard unknown unknowns, which is kind of like trying to understand a bit more, broaden the horizons about how transformative this could be. You've kind of mentioned defy, which is oh well, suddenly this is the technology that unlocks that sort of thought piece about tracing units on a blockchain as opposed to tracing money through bank accounts. But could it be more profound is suddenly this, this is the entryway for your technology company or Amazon to trade its own commodities, you know, on the back end. I mean, how could AI, you know, what is the capacity for AI to be absolutely transformative in ways that we're not even thinking today when it comes to this sector?
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Yeah, I mean, if you look at some of the stablecoin companies that are now fully opening trading companies. So right back to what I was saying earlier, there's a lot of stablecoin companies now which are now trying to penetrate the commodities trading business. So they know that they have faster access to faster information, they know they're automating their operating models, but they now also want to operate a 247 market with 247 financing. So I think you're starting to see a coupling of new players coming into commodities, new players forming better partnerships with traders as well. And I think all that is really down to the adoption of AI, the adoption of TradeFi, the adoption of smart contracts, the adoption of blockchain technology.
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Yeah, and using that logic though, obviously at the moment there's lots of Asset backed organizations, NOCs we've sort of mentioned, but you've got majors, refiners, miners, all also on some journey to build out a trading capability. You know, no longer in kind of quiet defiance of the boards, but at the, at the request of their boards. Because we do face a more fractious and volatile world for you, obviously someone who's lived in hedge funds and effectively trading houses. When you piece all this discussion together, do they suddenly become the potential powerhouses then given just how much information and asset footprint they have? And also they're not actually contrary to some sort of visions. They are quite far forward on AI when it comes to things like drilling a well, for example. I mean, does something, does this supercharge their journey?
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I don't think they're at risk. I think they're much more Supercharged because information is an advantage for a trading company. And you know, obviously we can't change the geopolitical landscape. We can't change the decisions that are made. We just need to manage and adapt around them. And I think having a fully optimized AI trading desk helps us. Having a fully optimized operating model underneath us helps us become quickener and gives us much more of a logistical advantage for sure. You know, having access to sort of global shipping routes and storage facilities and refineries at an instant is obviously much more powerful for us.
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Does this sort of supercharge the NOCs, you know, asset backed kind of capacity?
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Yeah, look, it does. I mean if you look at what I mean, AI has given us confidence from an individual to an organization to a trading firm to even ANOC to really, you know, the capabilities now are endless. We can be a player across the life cycle. You know, the NOCs have got into trading okay. There's no reason they can't get into the logistics. There's no reason they can't get into building massive paper desk. There's no more reliant on going to hedge funds or going to asset managers. They can do everything themselves. And I think that's something that AI has given most of the trading companies and especially NOCs is much more of a clear revision of that actually. We don't need to be so reliant on anyone anymore in the same ways that a trader doesn't need to be reliant on waiting for information from various sources. He can have all the information himself, thus giving him sort of, you know, a vision of what else is capable, what else can I do. And I think that's, that's the beauty of AI from a trading perspective. It just gives you the, the epidural of power in, in terms of what is possible, what is next. And I think that if you look at all the players within the, the life cycle of a transaction, I think we're going to start seeing maybe some merging of industries. As I said at the beginning, technology companies are now looking for trading companies to source direct energy. If you look at trading companies, they went and started acquiring. Instead of outsourcing their paper trading to funds, they built their own paper desk and now have an army of data scientists all using AI. If you look at noc, they built their trading desks and now they're looking at much more interesting ways to finance by looking at stablecoins. Stablecoins is enormously attractive for us, but obviously you know, we need to be slightly mindful that, you know, we never would have started this business without our banks. Our banks are enormously important, especially when it comes to rolling credit facilities. But you know, they're facing their own battles in terms of, you know, this disruptive technology has tsunami. Our industry and we are on a back foot, foot because you know, we're governed by roles and regulations from governments. So it's an eclectic mix of moving parts that does affect the commodities industry. You know, financing, you know, we would love to use stablecoins and I know that there are various commodity traders that have digital asset desks. It's not public but you know, for them it's an asset which is making money. So why shouldn't they hold it as part of their treasury? But obviously they can't optimize it in terms of using it to settle. But that's coming. That's absolutely coming. Hello, I'm David Hunt, founder and managing director at Hyperion Search. Founded over a decade ago, Hyperion Search has helped organizations from major utilities to startups recruit their leadership teams and key individual contributors to accelerate both their growth and the energy transition. Our three main verticals are renewable power, energy storage and the mobility. The energy transition and the talent that delivers. It has been our passion since day one. To find out more, visit hyperionsearch.com or listen to my Leaders in Clean Tech podcast. Available on all platforms.
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We had Zodia Markets on Nick Philpot. You know there are, there are bits and pieces of it, right?
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A
It does work actually. I mean if you, if you use stablecoins as a primary and on the back end of it, you still doing your financing with the banks, it does work. Okay. It's, I think the misunderstanding is that I want to use it, I can't use it. You can use it. You can use it for day to day settlement. Okay. Obviously I can't say who is using it. I'm not really, that's not my business. But it's being used because it's 24 hour settlement because you know, you can't.
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B
Well, it takes three weeks to set up a US denominated bank account.
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A
Exactly.
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B
I mean we're solving clear and present problems and especially at the moment when the US dollar has been weaponized. We had Jonah Van Bordon talking, talking just this final bit and obviously I think this might trigger some people reaching out and wanting to kind of get your views on this because we haven't, we barely scraped the surface of the defi piece which as we, I sort of keep alluding to, seems to, I think it's sort of going to have its day. And I keep referring to on podcasts, but I love this idea of the technology fallacy, which is technologies change us as opposed to in reality, cultures change and then suddenly the technology has its hour when it meets the culture's needs. And we're probably at one of those inflection points where actually, you know, we, you know, there's so much complexity out there, there's such speed that actually now things like defi AI are just required to be able to synthesize and manage all the data out there. A big challenge in all of this is obviously the people piece. We can set aside for a moment what it's going to be like to, you know, how you're going to train your next generation when that next generation isn't hired because there's no middle and back office. But who, where you've seen this done well, who can champion this kind of change within an organization? Because quite often this can kind of be, well, oh, I want to hand this over to my, my cio, right, or the CFO or whomever. Yet this is a holistic all of company change and it's one where, you know, there are dead ends, there are expensive bills that reproduce nothing. There's a lot of kind of buy in and leadership. Like how have you seen this start on a road that might lead to success?
- [36:06]
A
I think, well, I'm not going to use the word. I think I know that really, you know, change really only happens when there's someone above you that really enforces it. But in order to enforce it, you need to understand and believe it. So, you know, having a CEO, your C suite basically need to be very articulated in terms of what's happening in digital assets. You need to be very well versed on what AI does and what AI can bring. Because if not, if your COO or your CFO or your CEO doesn't really understand it, what you, what's going to happen is that you're going to hire a CIO who's going to be the most articulated, well structured digital asset person, person in the market. You feel like you've hired the best person for the job, but that poor individual is probably going to spend the next two, three years educating the cfo, the CEO and the COO or the chief risk officer whatnot, what the benefits are. It's going to become more of a sales pitch of adoption. Now I think that's where the problem sits. Now if you look at most trading companies, the people that know most about AI the people that most know most about how, you know, the stablecoin market works or how digital assets have completely changed the operating model are usually the people that have the smallest voices. So it will be the people in, you know, from tech, it will be the people that have just newly come straight out of university in the last sort of two, three years. People that have already been using AI technology to improve their day to day life already have a very sort of wide spectrum of how I can use AI to make my job easier, thus how do I improve the operating model. So for me, I think you need to start at the top. Now if there is an absence of this knowledge, which there probably is at the sort of CFO COO level, then obviously you call the consultants in. And I think the, but you know, when you call the consultants in, it's still not calling the consultant sends a message that, you know, we are lacking the information that we need within the C suite to execute the decision that that's a plain hard truth of it is. But then execution still needs to happen. So I think from the C suite down, it's going to be very, very difficult to get adoption because you, you know, there are still unfortunately people that don't want you to penetrate their empire of people that they're looking after. There are roles which will be affected. So it's a very, very sensitive place to start. So I think that, and I know there are some new commodity traders which have just come up where they probably have much more advantage because the CEO used to be a digital asset guy or the CFO was more defi native and the coo, you know, has been a crypto trader. I think having that kind of exposure and bringing it into the commodity space is what's needed. So right now, you know, we are seeing commodity companies looking for more digital asset experience because it's very easy to teach the commodities industry to anyone, right, Given a bit of time. But having someone with a digital asset background come into the business and run parallel, an operating model which we could adopt, I think is the key. And I know there has been one or two trading companies that have hired a, you know, a chief AI. And I think in the, in the, in the sort of headhunting space, you're going to start seeing chief head AI officer, heads of digital assets. They'll be, you know, the, I think the COO will be a hybrid of that because the COO right now is managing processes and managing people. Does that sound like something you need and digital asset AI model? No. Your next COO should understand digital assets, should understand AI As a bare minimum. As a bare minimum, your CFO should really. Okay. The CFO obviously has very good relationships with the banks. Whenever trading company hires a CFO, that's usually one of the main sort of DNAs. But I think the next CFO you're going to hire should have exposure to stablecoins, have exposure to the new defi world, you know, should have it should sit down that interview and articulate what a world would look like in defi. Not banks. Banks will get there. Same with your chief risk officer. They should be talking about what AI tools they're using to optimize data. If you look at your chief legal officer or your chief compliance officer, it's not about what operating model I built at so and so Trading House is. How have I name me some success stories you've executed in your previous company using AI model.
- [41:22]
B
Yeah, and it's fascinating that swap as well, we've sort of, in the space of two years, we have gone from a world where I'm slightly bashful that my law firm uses AI, you know, and oh gosh, do we put that on the RFP to now? I mean, frankly, just on the personal level, dealing with personal lawyers and other aspects of my life. I wish they did, you know, I wish they did use AI because all I'm going to do is run through their draft through AI and pick out the risks. Right. I mean, like it, it's sort of the great democratizer.
- [41:55]
A
Yeah.
- [41:56]
B
But it's also kind of the, the interest, the curiosity to use it. And you're right in the, in the, in the headhunting world, you know, that's why our technology practice actually is increasingly reaching out to organizations outside of the commodities world for this kind of talent, particularly as you say, from kind of digital asset traders and so on. But we're just at the start of this journey and part of the piece of work that we're doing with Longitude, that's going to be a survey for the C suite that will be rolled out at the DFT Global Commodities Summit in Lausanne and hope to see you there and hope to see other listeners there is actually just to try and take a bit of a snapshot about where that investment is going and what the thesis is today about what, what might change. Because I think, you know, over the course of a couple of years of doing this, we're going to quite see there will be some trends and some changes and it, and it seems to me at the moment AI is talked about kind of discreetly, you know, oh, well, let's talk about AI for analytics. Let's talk about AI for surveillance as opposed to sort of a broader, as you, I think, as you say, actually we need to get away from. It's just technology.
- [43:09]
A
Yeah.
- [43:10]
B
You know, and they can't live in silos. This is actually how are you enhancing but ultimately changing your operating model and leaning in on the various competitive advantages. You have to participate within that, otherwise someone else is going to eat your lunch.
- [43:27]
A
Exactly. I mean, also, you know, what does, what does success look like once you've adopted it and at what stage and how do you measure it? I mean, you know, just go back to what you said. Lawyers, obviously before, you know, you would go to a lawyer to seek advice. Now obviously the first step is before you do that is you go to an AI model like ChatGPT or can you ask the question?
- [43:50]
B
Yeah.
- [43:51]
A
And you keep asking the question and then you, then you say, you know, what is the lawyer going to say? And then, you know, when you get the, when he goes to the lawyer, he's using the same model, but you still.
- [44:01]
B
Well, if you're lucky, they are. But I mean, it's just guild work.
- [44:05]
A
You know, you still have a lawyer there. Right. The physical body of a lawyer. Yeah. So it goes back to what you said earlier. AI will be adopted, but you still need the physical trader. You will still need them. It's not going to wipe that out.
- [44:21]
B
Well, this is where you're, you're, you're relying on, you know, judgment. Right. And this is where actually the short term trader, it becomes less valuable than the long term originator.
- [44:33]
A
Yeah, right.
- [44:33]
B
The relationship, the big calls, the big bets, the judgment. Right. The CEO's judgment about, okay, who are we going to go with? And in a finite world of finite resources, how are we going to deploy that? So I don't, I think this is a fresh and wonderful world for judgment. I think it's a pretty negative world for kind of guild work. Right. If ultimately my lawyer can charge me 400 bucks an hour to put stuff into a boilerplate. Well, I kind of, I hope to heck and I hope, imagine many of our listeners do as well, that all gets aied away because that's not, you know, that's not fair.
- [45:10]
A
Look, I think that you will get more digital asset aligned C suites coming through. At the moment. They're at the bottom end. They're coming through the technology part. They're now starting to make a presence within the ops world and in the middle office world. And they're not quite, quite reaching the C suite yet. So I think, you know, it's coming up from bottom up to the top when really if you want to move quickly and efficiently and you want changes done immediately in order to be relevant and, and quick and powerful in this market, you need to start at the top as well and meet them in.
- [45:49]
B
The or Just, I think is, you know, you've got to be curious come what may, right? Have a few chat bots on your phone and just try and figure it out a little bit.
- [45:57]
A
Right. Well, you know, Paul, I, I, I got a trading book, okay, which I've had now for seven years. And I can tell you I have a department, I have six departments which no one works in. You know, I, I, every Sunday I put in my positions on my bot. I, I put the percentages I want to make and the frequency I, I want to execute. That's front office. Then the next department is, it runs my position and P and L and my risk. That's my second department. Then I have my financing, which is linked to my wallet, which then covers all my positions, whether I'm taking leverage or not. That's finance. And then I have reporting which puts together a report and sends out to the people that have deposited money into.
- [46:45]
B
The fun God makes me, you know, I, I use, I use Chat GBT to currently pick out which tile goes in which bathroom. So, yeah, anyway, one thing I, I.
- [47:01]
A
Want to add on Chat GPT and I, I just, because this bit's important for compliance, right. ChatGPT still keeps all your data, all.
- [47:11]
B
Of it, even if you use, even if you use the sort of Forget.
- [47:17]
A
Yeah, version. Yeah, it, it keeps everything. Now the difference with GRO is it doesn't, so that's another sort of area in commodities. I, I, a lot of people in commodities using ChatGPT and you know, that's great, but I think your, your legal and compliance behind it need, there needs to be some restrictions as well in all AI products because effectively what they're doing now is, you know, they're building a profile of you in the same way that you stick a picture up of yourself and say, you know, create an image of, of what you know about me, which is a recent trend. Right. In the same way that I could go into an AI model and say, give me everything I need to know about this particular trading company and it will give me information that was never readily available in Web two.
- [48:09]
B
Yeah, well, I'll leave it on that. So the freaky experience I had on the flight home for the Middle east yesterday was. I was asking about. I forgot what it was. It was a particular commodity and just out of interest. And then it said, do you want me to put this into a format that follows the HC Commodities podcast? And it doesn't know that I do that. Right.
- [48:32]
A
There you go.
- [48:33]
B
There you go.
- [48:34]
A
Yeah.
- [48:34]
B
Anyway, well, Aaron, it's been a real pleasure having you on. It's. I know you know our colleagues well, and.
- [48:41]
A
Yeah, you know, great bunch.
- [48:42]
B
Yeah, great discussion. I hope that we can. I hope we can have a part two coming up shortly and, and sort of what I want to do is, is take this and expand it into that defi world, because I think there's a lot to talk about there.
- [48:54]
A
There is a lot to talk about. And I, I, we should definitely do it because I think this is a subject which is out too often and it needs to be really ripped open and explored because people are wondering and people do want to know.
- [49:09]
B
Yeah, well, let's, let's pencil it in. But, well, great to talk and, yeah, look forward to having you back on.
- [49:15]
A
Thank you very much.
- [49:18]
B
Thank you for listening. To find out more about HC Group, our global offices, and our expertise in search within the commodities sector, please visit www.hcgroup.