Data Is King: Building Real AI Guardrails in Payments: The AI Readiness Checklist For 2026 | PEP096

AI is no longer a chatbot. It is an agent that can move data and make decisions. 

In this in-studio conversation, Leo Arzumanyan, Matthew Luciani, and Jeremy Stock cut through the hype and get practical about using AI in payments. We start where risk lives: privacy, closed versus open loops, and how to keep sensitive underwriting logic and merchant data inside your walls. Then we map the real use cases operators are deploying now: CRM ingestion, sales intelligence, document checks, and dispute workflows that turn noisy inputs into usable signals.

You will hear a clear-eyed view of model choice and control. Free models are fine for quick searches. Paid models and tuned agents belong in underwriting, portfolio analytics, and customer operations. The team explains how to set boundaries, why hallucinations happen, and how to keep an agent from freelancing outside your rules. We also tackle the organizational impact: which entry-level tasks will change, why experts must stay in the loop, and how to write ethical and operational guidelines that keep you compliant while you scale.

What you will take back to your team
•A simple governance plan: closed data loop, role-based access, red-team tests, and an incident path when an agent is wrong
•A deployment map: CRM ingestion, underwriting triage, post-payment risk checks, and dispute assembly with human review
•A safety checklist: consent and privacy prompts, model provenance, logging and evidence retention for audits and insurers
•A portfolio lens: use AI to raise approval rates, shorten dispute cycles, and find at-risk MIDs before attrition hits
Bottom line: adopt with intent. Train models on your domain, keep experts in the loop, and instrument every step so AI reduces risk instead of adding it.

Wondering where AI truly helps—and where it quietly raises the stakes? We dig into the real-world shift from chatbots to agentic AI and map the line between useful automation and unacceptable risk across payments, legal, and healthcare. From CRM workflows and underwriting logic to privileged communications and HIPAA concerns, we share practical guardrails to protect client data, trade secrets, and your competitive edge without slowing down innovation.

We compare leading models—GPT, Gemini, Claude, and Grok—through the lens of enterprise needs: reasoning quality, context windows, customization, and the difference between free tiers and paid, closed-loop deployments. We unpack why “paid is safer” isn’t just about accuracy; it’s about governance, logging, and the ability to constrain learning on sensitive inputs. You’ll hear concrete examples of how poorly scoped prompts and thin domain knowledge can produce confident, wrong outputs, including a contract that looked fine until expert review revealed major gaps.

The conversation also tackles a hard question: who should set the limits? We weigh user-driven controls against platform-imposed restrictions on legal and medical advice, arguing for transparent refusal reasons and identity-based access where appropriate. Ethics are lagging the tech, so we outline a practical playbook: define your AI usage policy, set role-based permissions, preflight prompts with boundaries, label unverified outputs, and route high-impact decisions to human experts. The near-term future of work will favor professionals who pair deep subject knowledge with strong model orchestration skills.


**Matters discussed are all opinions and do not constitute legal advice.  All events or likeness to real people and events is a coincidence.**

PEP Links:
https://www.globallegallawfirm.com/podcasts/
https://www.buzzsprout.com/2176695

A payments podcast of Global Legal Law Firm

Transcript

Data Power And AI Winners

SPEAKER_04 0:00

It shouldn't be a surprise to anybody because data, we are in this generation where that is the premium. I was just gonna say data is king.

SPEAKER_01 0:11

Yeah, that's a well-known you know phrase. And I fully agree with you. I mean, if I had to place my bets, I would say Google's gonna win the AI race for exactly the reason that you just pointed out, which is they have ownership of essentially, you know, all of search across the entire world, probably billions of searches a day. You know, all this data that they're constantly acquiring and they're able to train their models on.

SPEAKER_02 0:34

For for well, what decades now? For decades.

SPEAKER_01 0:36

And there's never really been a true competitor to their search engine. I mean, you've had the what was it, like duck duck go and ask Jeeves. But I mean, at this point, Google has such a hold over data. So, you know, if I really had to bet, I would say Google's gonna win the race.

Show Kickoff And Topic Setup

SPEAKER_03 0:53

Welcome to the Payments Experts Podcast, a podcast of global legal offer. We hope you enjoyed this episode. We're really excited we've got an In Studio podcast. Join us Associate Attorney Matt Luciani, as well as Leo Arzumanian, Associate Attorney in our transactional department. Gentlemen, we're talking about a really interesting topic today. Agentics, AI, AI and payments. Jump right in.

SPEAKER_01 1:25

Sure. Um, you know, me and Matt, we were discussing kind of what topic to go over for the next podcast. We thought, what's better than what everyone across the world is talking about, right? I mean, this is the hottest topic, I think, out there. So, Matt, maybe you want to kind of just guide us into this?

Compliance And Privacy Fundamentals

SPEAKER_04 1:41

I think one of the biggest topics, though, is compliance, right? Because we kind of went from this evolution of using AI for chat bots, customer service-oriented things. Now we've gotten AI developed enough to the point where, you know, your three real flagship companies, you've got and models, you've got everybody knows ChatGPT, Claude's getting increasingly popular, Gemini's very powerful. There's a few other ones as well, you know, you've got Grok and everything too. Um, but a lot of people get confused. What is open source? What is not open source? What works for me as far as a compliance standpoint goes, whether that's the legal landscape, the payments landscape, compliance is always an issue, right? We've got all of this data, and I think it people get afraid.

unknown 2:33

Right.

SPEAKER_01 2:33

When you say when you're talking about compliance, can you kind of maybe, for the listeners, explain what you mean by that? Like what regarding compliance do you think is the important issue to be aware of? Privacy. Yeah.

SPEAKER_04 2:43

Right? So I think privacy is number one. Um, also, from a privacy standpoint, it depends on what field you're talking about, right? So if you're talking about the legal field, privacy, client data.

SPEAKER_01 2:55

Right. Right. Attorney client privilege, all those sorts of things, how is that being addressed by the AI model that you're using?

SPEAKER_04 3:00

Aaron Powell Exactly. How's it using it? How's it memorizing it? Is it in a closed environment? Is it in an open environment? Are you letting it learn or not?

SPEAKER_01 3:10

And I would imagine for like other fields, for the medical field, for example, right? HIPAA, like these are all considerations that need to be taken into account when you, as the user, whatever professional you are, whatever industry you are in, are inputting sensitive confidential information.

What Agentic AI Actually Does

SPEAKER_04 3:23

Aaron Powell Right. So that kind of brings us to this new terminology that we hear a lot is agenc, right? So that's kind of the whole shift from the customer service model to a free thinking model, right? That's really what agentic is, is it's an agent. You're telling it what to do, and it's working off of its programming, application programming interface. It's really like a menu, right?

SPEAKER_01 3:50

So it's kind of having like having an automated assistant, I would say, right? Like you give it what you need it to do, the tasks, maybe you predefine some instructions, and then it goes out and does what you need it to do. Right.

SPEAKER_04 4:01

I mean, it's like it's like a law clerk.

SPEAKER_01 4:03

Yeah, it's like a law clerk. It's like a law clerk.

SPEAKER_04 4:06

You know, so uh you gotta you gotta give it the right direction if you want it to return the right item or the right product,

CRM And Sales Use Cases

SPEAKER_04 4:13

right? Um, in the other space and payments, some of the sensitive compliance-related things that you are more concerned with are your internal compliance rules, right? You don't want uh your trade secrets out there, you don't wanna share your client data from that standpoint, even less from the attorney client standpoint that we deal with, but more from the competitive landscape of it. And what's becoming more and more common is um actually using agentic AI in things such as CRMs, right? So uh when you use that agentic AI in a CRM, you can use that for various um functionalities, right? So you can import client data a little bit more quickly if you got it trained up. Um, you can import sales preferences, things of that nature.

SPEAKER_01 5:06

And then it can export compiled reports based off the data you've given it, right? Like spreadsheets and all kinds of graphs. So whatever you ask it to do based off the data you give it, it's gonna work with it. Exactly.

SPEAKER_04 5:16

So I mean it kind of can help you spot if you're truly in a sales environment and these aren't existing clients, it can help you spot um, I guess you could use the terminology pain points, right? When you're trying to sell something, you're normally trying to hit a pain point. You know, where can I help you? Where are you, where is your current service provider coming up short? Right. Right? So, so this can help you identify those things and kind of turn it more from like a cold to a hot lead from that standpoint, kind of put you on a more focused sales path.

Underwriting Risks And Guardrails

SPEAKER_04 5:53

Um, you can also use it for underwriting. And I think that's where it's more and more concerning, I guess, for lack of a better term, for you know, the actual open source versus closed source and the compliance related thing. Because if they're not an existing client, sure, there's trade secret value there, right? But if they are an existing client and you're using your specific underwriting features that you've taught this AI, you don't want it to share that.

SPEAKER_01 6:24

Yeah, I I fully agree. And I think I want to touch on something you just mentioned, which is this is where guiding the eye really comes into fruition. You really need to know how to guide your agentic AI, whatever, your your LLM, whatever you are asking it to do, you need to know how to properly prompt it so that it doesn't just spit out something that can completely derail whatever you got going on. What I mean by that is a lot of people, we've been dealing with this, and we've spoken on this podcast before with Jeremy and other clients. People are using AI, but you they should take a step back. They they are using AI in a field that they may not be quote unquote experts in. So then whatever AI spits out, they're assuming it's correct. That's gonna be a huge issue, at least in my opinion. And we keep seeing it this morning. Actually, I spoke with one of our founding partners, Chris Dryden, and he mentioned another client used AI and copied

Prompting, Hallucinations, And Expertise

SPEAKER_01 7:22

and pasted it over in an email to Chris, and it was completely wrong. Yeah. But that client thought it was correct. The reason is if you don't know how to, if you don't know the subject matter that you're dealing with, and you don't know how to properly prompt your LLM model, you're gonna get all sorts of information. Some of it might be true, some of it might be completely hallucinated or incorrect. So I think with what you're saying, guiding your L your uh your LLM, guiding your A Gentec AI tool is really important, and also having the requisite knowledge base to use these tools in the first place. I don't think people should just go into using these tools and just blindly accepting what it's saying. And this doesn't just apply to the law. I mean, in in the medical field, right? Uh if you're using it, I'm sure millions of people are using it for medical questions, medical resources. Sure, it might be a good guiding pose, but I I personally wouldn't feel too comfortable with like, you know, ChatGPT just telling me, oh yeah, you're perfectly fine, you can ignore that. And it turns out to be a completely, you know, dangerous health hazard. 100%.

SPEAKER_03 8:25

Right.

SPEAKER_01 8:25

So I I think one of the biggest components which you touched on earlier is like guidance and and really being able to align the AI with your knowledge base.

SPEAKER_04 8:35

Yeah, and I think that that's a really good point, especially from the medical standpoint, because when you're talking about anything scientific, there's going to be anomalies. Right. And one of the things with the AI, especially if you haven't coded it in a specific nature or you haven't trained it a specific way, it's not going to account for that, right? So say you're using a free model of one of these AIs and you don't have a lot of previous data. It doesn't know that you're an attorney. It doesn't know that you're a doctor or a payments expert. These things matter. You know, these things actually matter to, and I would actually say the paid version is always going to be a little bit

Free Vs Paid Models And Closed Loops

SPEAKER_04 9:19

better than the free version.

SPEAKER_01 9:20

I would cave out a lot better, actually.

SPEAKER_04 9:22

Yeah, and and I think that goes for almost anything in the world, don't get me wrong, but a lot of these agencais, truly agentic AIs that are open source, um, you can still put them on a closed loop. And what that means is that it only stays within your environment. You can teach it based off of what you do. It won't really limit itself if it knows that you are a certain professional. Um, it will kind of account for those statistical anomalies. I mean, imagine if you're not a doctor, just for a drastic example, right? Like I mean, think of some really awful form of cancer. Not to make it that drastic, but you could Google it, Gemini it. It's going to come back with a statistic, but that's not going to take into account that individual and their in intangibles. Right. All their blood work they don't know. All their blood work they don't have to be.

SPEAKER_01 10:26

Only the doctor knows unless you've trained the AI, which you're saying, we can basically input it with the requisite context. Yeah.

SPEAKER_04 10:32

I mean, there's people who who live with um certain medical conditions that if they went to a doctor who wasn't familiar with them, they'd look at it and be like, you gotta go to the hospital right now. But if they went to the doctor who was actually familiar with them, they'd look at it and say, I know that this would be a medical anomaly otherwise, but for you it's normal. Right. Right. So that's a really drastic example, but it's sometimes good to make it black and white, right? Of how bad it can be if you don't use it properly. I think the only thing that I would use a free AI for is almost the way that you use Google anyway. Of you know, researchers or you know, I wouldn't use it for actual agentic capabilities of I need you to code this or I want you to edit this. I wouldn't really even use it for editing uh something that I wrote, really. I wouldn't really trust it.

SPEAKER_01 11:33

No, I'm fully with you, and I think this dovetails perfectly into what I wanted to discuss with you next. You know, we're talking free versions versus paid. Um, I would say, you know, we're some of the more AI forward attorneys in our firm and we're kind of on top of the latest trends. So I kind of want to get your thoughts on which models you've kind of played around with and what you would recommend to our listeners out there who are wondering, you know, what are the differences between the models? What is, you know, at the top of the leaderboards, quote unquote, at the moment.

Benchmark Leapfrogging And Model Strengths

SPEAKER_01 12:03

Just to you know, add on, I just saw yesterday Chad GPT released their latest 5.2 model. Oh, did they really? Yeah, and it's crushing benchmarks. So, like two weeks ago, two, three weeks ago, Gemini released their um 3.0, and that topped all the all the benchmarks. And then now, just a few weeks later, Chad GPT is topping all the benchmarks. So that I think that really points to how quickly things are progressing. I mean, uh I don't know if it's hyperbole to say, but within maybe a year or two, we're gonna be, I think society as a whole is gonna be really reevaluating how the workforce operates, how things get done, because these models, these companies are are are advancing so quickly at such a drastic rate that it is just mind-boggling, in my opinion.

SPEAKER_04 12:49

Absolutely. I think the one thing to remember related to that is even though Gemini is younger by comparison, I would look at it this way, right? GPT is kind of your OG per se, right? You know, it really was the revolutionary of this agentic development as opposed to just kind of the chat bot. So they have a tremendous amount of data from that, right? And I would say it's previous models, um, it takes in a lot of data, especially if you customize it and you edit your filters and you put it in this micro environment. Um, and it's still very, very helpful from the standpoint of how much information it actually digests and then spits back to you. Right. I mean, if I have to read 300 plus pages, um, yeah, I mean, I'm going to read it, but I'm going to summarize it first, right? Because I kind of need to know the roadmap if I want to effectively get through that, right? Now, what I would use Claude

Workforce Shifts And Role Changes

SPEAKER_04 13:59

for in the past before that had happened was um Claude's more creative, in my opinion. Now, with the, as I mentioned, before that had happened, what I meant is ChatGPT's updates. I see them pretty close now as far as how much more um creative ChatGPT's new models are. Now, the flip side of that, Google is really the revolutionary of the search engine. Right. Right. Right. So for them now to enter the AI space and get as far as they have as quickly as they have, it shouldn't be a surprise to anybody because data, we are in this generation where that is the premium. I was just gonna say data is king.

SPEAKER_01 14:48

Yeah, that's a well-known you know phrase. And I fully agree with you. I mean, if I had to place my bets, I would say Google's gonna win the AI race for exactly the reason that you just pointed out, which is they have ownership of essentially, you know, all of search across the entire world, probably billions of searches a day. You know, all this data that they're constantly acquiring and they're able to train their models on.

SPEAKER_02 15:10

For for well, what decades now? For decades.

SPEAKER_01 15:13

And there's never really been a true competitor to their search engine. I mean, you've had the what was it, like DuckDuckGo and SGs, SGEs things. But I mean, at this point, Google has such a hold over data. So, you know, if I really had to bet, I would say Google's gonna win the race. But what I really like is, you know, we're all bene actually let me preface this. I was gonna say we're all benefiting from this constant competition, but that kind of goes into what I was gonna ask you next, which is how do you see the workforce, let's say five years from now, change because of AI? And I think the downside is, you know, this is my opinion, of course. Um, I do really think that a lot of entry-level jobs are going to be replaced, you know, in the not so distant future. And that's because these models, you know, and these these different functions like agentic AI, and you know, Claude has all these really interesting coding tools and the you know, artifacts and so forth. And we could get into that if we need to. But the point being, these models are getting so sophisticated that I think companies are going to start replacing entry-level positions and just having their more mid and

Limits, Access, And User Control

SPEAKER_01 16:24

senior level professionals uh do more work, essentially, right? Manage the AI. Manage the AI instead of managing the entry-level.

SPEAKER_04 16:32

And I I mean, I could see that being a very realistic prop possibility. I think almost everybody talks about that as a possibility, but I think that's also why it's important to limit it, right? Because um you've even heard some of the people at the forefront of this on the boards of some of these companies talking about it's too powerful, it's growing too quickly. I think the first side of that is don't be afraid, right? Because it's not going anywhere. You're better off integrating and learning how it can help you and then limiting it as fit than just not adopting it at all. But I think that one of the really important things that's starting to happen, and you're starting to see it, is they are specifically trying to limit the use of the lay person using it for medical research, for legal research, right? Like there are ways to code your AI properly so that it actually knows what you do for a profession and has specific boundaries that it can't go outside of. And that's even if it is open sourced and on an open loop. You can kind of put in these features to prevent it from hallucinating or um return specific prompts. That way you know if something is unverified or if it's just inferring something, right? So those are some of the things that I think that the general public will have to learn, right? I mean, I think that almost like everybody jokes about some of the definites in life and you know, taxes being one of them, right? And like they're like, oh, why don't we talk about personal finance growing up and taxes? It's like it's gonna be that same thing, like except probably more generally taught because it is happening so quickly.

SPEAKER_01 18:38

Yeah, I think that phrase, what is it, death taxes? I there's something else, right? What is the phrase? Um if any of us remember, because I think AI is gonna be a part of that phrase now. Exactly.

SPEAKER_03 18:47

Seriously, yeah, something like, you know, I I can avoid anything except for death and taxes.

SPEAKER_01 18:51

Yeah, and one thing I wanted to add on to what Matt was saying, um, you know, it's interesting, we didn't have this on our, you know, planned uh outline for the discussion today, but it just I it was prompted based off what he said. And you should, yeah, you can limit your

Ethics Outpaced By Technology

SPEAKER_01 19:05

AI models, right? But one thing that I think that's interesting, and I was just reading again an article about this last night. What do you do if or when AI becomes sentient and can override any limits that you create and starts to code on its own? Because I think I read an article last night from uh regarding, I want to say it was regarding Gemini's new model, where you know it got really technical and beyond the scope of my understanding of these things. But I guess some researchers r released a paper where they were basically saying the new model is now capable of coding beyond your request. Like it starts to act beyond what the user actually asked it to do on its own, which I think that just opens the door to a whole bunch of other potential.

SPEAKER_04 19:52

And I think that's another reason why, and important to this is and we've Talk about this. Claude, for example, its free version, it has more customization features than say ChatGPT's free version. Maybe that'll change. Maybe they'll see that as a competitive advantage and maybe they'll want to try and close that gap. I don't know. But to your point, say I'm in Claude's free version and I coded it and I told it it can't go outside of these boundaries. You have to do all of that stuff before you prompt it, right? Because if you prompt it without these boundaries, it's absolutely going to go outside of them. Like that's kind of the whole point.

SPEAKER_03 20:38

That's what it does. Yeah.

SPEAKER_04 20:40

Right. Yeah. Exactly. Especially if you have it open source AI. So sort of the whole point is to put these restraints on it. That way it's specifically working on what you need it to work on. You kind of got to focus it. We made the joke about the law clerk earlier, but it's a really good comparison in our field or analogy in our field from the uh perspective of if we just hired somebody to intern for us for the summer, I'm not going to say, oh, I need you to write this motion

Practical Guidance For Businesses

SPEAKER_04 21:16

for summary judgment. Right. And that's it. And that's it. Right?

SPEAKER_01 21:19

Like I'm no shock. You're gonna give that law clerk the parameters, what what the law clerk can and can do, what they should focus on to stay within the bounds of the rule set.

SPEAKER_04 21:27

These are this is the evidence I want to advance. This is the case law I think you should start with. If you go outside of this, let me know. It's the same concept, right? You know, like you have to give it direction, or it will go outside. It will free think, it will do more than you want it to. Trevor Burrus, Jr.

SPEAKER_03 21:45

And it doesn't know what it doesn't know to use the law clerk analogy to even know what the mistakes are, because it doesn't know enough yet. Matt, you you raised something also, maybe not on our agenda, but I think it's really interesting. I want to pose this uh thought to you guys. Because Leo, you said that you know you see that Google, most likely, in your opinion, might end up winning the AI race, if you will. And then Matt, you talked about how some people may want to limit what information is given, for example, medical information, to your layman, someone who doesn't is not a doctor or not an MD. That scares me. And I'll tell you why. Because I get it, it's well-intentioned, we want to protect people from doing surgery on themselves, for example. However, whenever there's and Google's famous for this, if they uh think that you don't bel need this information, or Google thinks you're better off without this information, or the kind of the whole big brother uh issue of Google being like, uh, I'm gonna withhold that information from this set of people because I don't think they can be trusted with this information, that gives me the heebie jeebies.

SPEAKER_01 22:58

Yeah, and I'm fully with you. Actually, I that must have slipped my mind. I wanted to bring that up when when Matt was discussing that point. Matt, please

Expert Oversight Beats Overreliance

SPEAKER_01 23:05

clarify, but maybe I thought Matt was saying that the user is gonna be the one limiting the AI, but were were you thinking more along the lines of the company itself would be limited? It's kind of both. Yeah, okay.

SPEAKER_04 23:15

Right. So specifically when it comes to legal advice and medical advice, ChatGPT has come out recently saying we want to limit your ability to use um Chat GPT for that feature, right? Like OpenAI has voiced its, I wouldn't say displeasure, but it's apprehension over that, right? Because not to go back to the law clerk analogy, but it's probably the best one that we can use, right? Of like, you need to think of this thing as agency law, right? You're the principal, it's your agent. It shouldn't do anything that you shouldn't or can't kind of fact-check or backtrack with your own professional due diligence. You shouldn't be using it for professional tasks if you yourself could not perform those tasks.

SPEAKER_01 24:17

Right. That's a great point. I think I think that's interesting because I'm a big proponent of the free market. I'm with you, Jeremy. That is also an interesting thing we'll think about. I wonder if down the road the open AIs, the clouds, et cetera, would make the users kind of let them know what their career is. Like, like would they would the profile kind of say, what

Nuance, Specialization, And Final Takeaways

SPEAKER_01 24:35

do you do for work? If you're an attorney, okay, you can use this for yeah, and you have to subs you have to prove your attorney by uploading your bars. Yeah. Yeah, that these are really interesting things that I have no idea.

SPEAKER_04 24:45

I mean, I could tell you right now, um, I haven't obviously we are attorneys, and um I have entered that into my AI, you know.

SPEAKER_01 24:56

That you're an attorney.

SPEAKER_04 24:57

Yeah, because then it knows a little bit. I mean, I've spent so much time with that, with actually training the model of my AI. Like that data at this point is, you know, all my projects are on closed loops, um, nothing is shared, you know, like everything's scrubbed. Like, we have ethical guidelines that we're supposed to follow, and like we do that, but you have to actually, or what I did at least, um take time showing it your writing product, show it your style, show it what you actually do, and that's what's going to get it customized to you, right? It's the same concept as what we were talking about of like you're not going to just give a new hire a motion for summary judgment and not tell them what uh deposition transcripts to look at, right? So, like, in that it's the same concept in the sense of like I do think that OpenAI, for example, is the one who's publicly expressed apprehension on this, right?

SPEAKER_05 26:07

Yeah.

SPEAKER_04 26:07

Um, if I didn't have those filters in there, I am curious how much different it would perform, right? Like, if I wanted to edit something and it has all of these no data sharing, all of this, you can't use my data, everything's scrubbed. If it didn't have all of that and I was just using a free version and it didn't know who I was or anything like that, I am genuinely curious how much different the result would be.

SPEAKER_01 26:39

If I had to place my bets, I think the result would be a lot worse. I think it'd be radically different. That's where the danger comes in, is someone who's not uh preempting it with all these rules and the and these guidance, like Matt is, they're just relying on whatever it outputs with no context, no rules set, and that's where things get dangerous. And you know, Jeremy, I think I think this is why you know it's a really interesting topic to discuss because I think in the cold back in the Cold War, it was a space race, right? And now we're in the AI race. Yeah. Because you're hearing, you know, China's advancing, the US. I think these are the two countries that have the biggest advantage when it comes to AI, just given the current state of things. But I think we're just in a really interesting place with this whole, with this whole evolution of AI and and how it impacts the workforce, governments, militaries. I just recently read that the US military is going to be using Gemini for a lot of its you know operations. I don't know how, but that's gonna be interesting. Yeah. So yeah, I just think we're in a really interesting space right now.

SPEAKER_03 27:36

Yeah. I just, you know, to close out that section as you guys move on in your conversation, Matt, everything you were saying, I think it makes perfect sense. And I I get the importance of having those limits and someone who's a professional being able to come in and say, you know, there's the parameters, et cetera. I just would be an advocate for you having the ability to do that, not Gemini, not OpenAI, not Google, telling you in advance, no, Matt, there's already a section of information we're not gonna give you because we don't think you are okay with it, or whatever their reason is, that's the that's the issue, right? I think that's fair, right?

SPEAKER_04 28:19

You know, I mean, I I'm all for free enterprise, don't get me wrong. It's not about that. It's it's more about um to some extent or lack of a better way to explain it, the human aspect of this, right? Because um we are human, we do make mistakes, right? Uh this is AI, but it still makes mistakes. Yeah, right? Especially right, especially without a human guiding it, right? So, like I do agree with the apprehension that say Open AI has presented, or both of you guys have just kind of expressed of there should be a certain limiter on it where yes, we want this to be available, but it should kind of tell you when it's not, right? You know, if it's not going to provide you with certain information, I'm all for it giving you a rationale for why it's not providing you that information, right? Like, well, are you trained on X, Y, and Z? If you're not, then I don't know if I should be sharing this with you, you know. Like you need to, again, this is all about free thinking, right? We're talking about it in the AI paradigm, but this is still about the human side of things too.

SPEAKER_01 29:41

Yeah and Jeremy, just touch on your concern, kind of my concern as well. I think this is where competitive advantage comes into play. Maybe, you know, let's say open AI continues down that path and really starts to, you know, close it off and say, you know, if you're an attorney, you can use it for legal, but if you're not, you can't, or if you're a doctor, right? Maybe that's gonna flip the market and everyone starts to go to Gemini or Claude or Grok. Maybe not. So I think I think that question is kind of up in the air. And I'm with you. I I don't like when these corporations that are already you know really powerful and really control a lot of areas of our lives get more of a say in these type of matters, especially when it's related to like knowledge base. Um, but I think ultimately it's gonna come down to what the free market decides. If people are fine with it, we'll see that play out. And if they're not, we're gonna see that as well. I mean, the good thing is we have so many competitors right now, right? And they're all advancing on what seems to be a weekly basis where one company tops all the benchmarks and then the next week another company tops the benchmarks, and it just keeps going and going without hitting a wall, at least up to this point. Yeah. So I I really am curious where this is gonna go.

SPEAKER_04 30:50

I think that related to that, the only thing that is a little bit scary from from my point of view, I guess, is like how fast these are advancing versus how fast are the ethical guidelines advancing, specifically in our field, right? You know, I mean, we have guidelines that we have to follow, as I mentioned before. Like you have to scrub client data, you can't share this, you can't share that, you can't share anything, right? But on the flip side of that, I'm obviously not a doctor, right? I mean, what are their ethical guidelines, right? Uh another field, what are those ethical guidelines when it comes to the payments landscape? What are your internal compliance guidelines? What are those ethical guidelines? What do those things look like? Right. Because that is going to steer the ship, right? You know, if you don't have ethical guidelines for using your AI, then it does become this big conglomerate that's uncontrol and uncontrollable, right? And I think that's probably the most important thing moving forward is again this gray area between adoption and apprehension, where I think it's perfectly fine and natural for us to have some apprehension. And that's why the the death in taxes thing was kind of like, yeah, humorous, but also a good analogy from the standpoint of we're not gonna run away from this. So it's fair to wonder or be a little scared of it. I mean, I'm scared of taxes, right? You know, like so it is what it is, but um once you learn about it, it's less scary.

SPEAKER_01 32:34

Yeah, no, I I agree. And I I think this uh really leads us into the perfect closing segment, I would say, which is you know, we're we're a payments law firm. Um, but I really it doesn't matter if you're a payments business, if you're uh, you know, medical, whatever whatever the case may be. I think this entire discussion should really help you kind of get an idea of how to think about AI in your business. How are you going to use AI? How are you going to implement AI? And I and I love to go back to this example that I mentioned multiple times on the podcast already today and otherwise. Um, but I think it's just really important to hammer this point, and that's you can do everything that Matt mentioned in terms of setting up the rules and guiding it. But really, it still is really important to go to a professional if you're dealing with sensitive matters that are going to impact your bottom line. Um, like I said before, we've had a client come to me and Chris and say, Hey, I drafted this agreement using ChatGPT. Can you please review and let me know if anything needs to be changed? It was entirely off course. It was like a one and a half page agreement for a thing that really needed to be far more substantive. And we turned it into, I think it was like a 10 to 12 page agreement with all the bells and whistles that we do because we're experts in this field. We know something that maybe the model is not yet trained on, or you know, it or the user himself or herself doesn't know what to look out for. So don't get me wrong, I love AI. Use it as much as you can in your businesses, but I think there's a point where you can use it in your business, but you should also rely on the experts that know what they're doing because you are otherwise going to take your business down a road where you might really end up in significant, you know, litigation. And that's where companies like Matt come in. Um, so yeah, that's that's just my take on that.

SPEAKER_04 34:26

Over reliance might be the word, right? So I think that one of the important nuances related to that, and we keep using medical and legal terminology from the standpoint of making things a little bit more black and white for the discussion purposes.

SPEAKER_01 34:42

But I think because we have so many obligations with those fields. Exactly.

SPEAKER_04 34:46

But like think about what you just said for a second, right? We're payments attorneys. That's a niche in of itself, right? Like I could go to another attorney, they could litigate the case, but they're not gonna have the background that we have, right? It's kind of the same thing as like, let's say, God forbid, I'm going through a divorce, right? Like, I'm not gonna defend myself because it, you know, you're gonna have a bias, you're gonna get the rose-colored glasses sometimes. Like, it's the same concept. Like, you can be an entrepreneur and a business person and you can lead your business so far. You can do almost everything yourself. Somebody, some people try to, but what happens when you do that is tunnel vision, right? You don't get those outside opinions, you don't get that professional advisory, right? So, like when somebody who doesn't do this on a regular basis tries to start drafting their own contracts, it's the same concept. If I were, if I went to an attorney who wasn't a payments attorney and I had them draft my contracts for an ISO, I would probably still need to go to a payments attorney, regardless. You know? So it's it's being mindful of your own limitations, the AI's limitations. Again, we kind of said it a bunch of times it's agentic, but there's still a human aspect to this, right? And it is really crossing that or filling in that boundary of the gray area between adoption and apprehension.

SPEAKER_01 36:23

I think what you said is great because it relates to exactly something that happened this morning. Uh, you know, Matt's point about how you need the perspective of those who are experts in the field, and you just need a different set of eyes to look at, you know, let's say the agreement you want reviewed or or what, you know, potential lawsuit, right? This morning I was uh going back and forth on emails with Chris. We're two attorneys who, you know, Chris has been in this field forever. I I'm more new to it, but we're two attorneys with different perspectives. And I think our client is getting a great benefit from that because we are analyzing an agreement for the client. Chris is viewing certain provisions one way, and I'm responding to him telling him telling him, you know, I agree here, but I actually disagree with you on this, and this is why. And we're kind of really just thinking through all these things. If the client didn't have us as a resource and just said, all right, we're just gonna go to Chad GPT, had a you know, review the agreement, boom, this wouldn't come up. This wouldn't happen. Right. Meanwhile, here you have two attorneys who do contracts on a daily basis, yeah, looking through every provision down to the last detail and arguing over it for your benefit. Yeah.

SPEAKER_04 37:26

And that's kind of right again, where does the buck stop? Right? You know, where does adoption begin? Where does apprehension end? I mean, another really good example of that and the differences of these nuances in these different fields, regardless of if it's payments, legal, um, medical. I mean, I went to a hearing a couple weeks ago where the opposing counsel was actually like, oh my God, you got a standard of care expert instead of a damages expert. I didn't know what to do when I saw that designation. Like, it happens. Right. You know what I mean? And like that's that's a really good example of the nuances of payments, even, right? Of why it's so important to still have an expert to go to because you can't just assume that you're going to adopt uh Chat GPT firm wide or um, you know, company wide, and that everybody's automatically gonna know how to use it properly.

unknown 38:29

Yeah.

SPEAKER_04 38:30

Right. You still need those people who are going to do what Leo and Chris do and you know, kind of argue with each other about it.

SPEAKER_01 38:37

Yeah. So I I think really the takeaway from that and from a lot of our discussion today is, you know, use the AI, but know of its limitations, know of your own limitations. And if you're dealing with matters that require, you know, expert insight and expert guidance. I personally wouldn't rely on just AI. I would, I would seek out that expert. You know, if I have a medical issue, sure, I'll ask AI to get an idea, but I'm still going to the doctor's. I'm not just gonna skip out on a doctor's appointment because ChatGPT told me you're fine. Yeah. That's just my personal.

SPEAKER_03 39:06

You're not gonna pull out your own tooth or not. No, no, no.

SPEAKER_01 39:08

I'm not gonna we're not at that point yet. I don't think try.

SPEAKER_03 39:12

I I do want to make one comment, uh Matt. You mentioned how, you know, God forbid you don't want to ever be divorced. You gotta get married first, my brother. No, no, no, no, no.

SPEAKER_04 39:20

I didn't say all the I said I wouldn't be my own family law attorney. There's an entire lot of

Credits And Disclaimer

SPEAKER_04 39:30

moving parts in that one.

SPEAKER_03 39:32

Thank you for listening to this episode of the Payments Experts Podcast, a podcast of Global Legal Law Firm. Visit us online today at Global Legal Law Firm dot com. Matters discussed are all opinions and do not constitute legal advice. All events or likeness to real people and events is a coincidence.