AI Is Breaking Banking’s Scale Advantage

Jim Marous (00:11):

According to PwC, the biggest competitive advantage in banking right now aren't based on scale, it’s speed. The new report that data just released shows that generative AI is reshaping the balance of power across financial services, and the banks that are most likely to succeed are those who move the fastest and define the next area of growth.

Jim Marous (00:37):

In fact, 58% of banking leaders believe generative and agentic AI will be the single most transformative force in the industry over the next three years, and 55% already consider it their top investment priority more than any other sector in financial services.

Jim Marous (00:58):

What's truly disruptive is that AI is leveling the playing field. Smaller, more agile organizations now have access to the same intelligence, decision-making power, and client insights that once reserved only for the biggest financial institutions.

Jim Marous (01:16):

Speed, not size is becoming the key differentiator, and this shift is pushing banks from asset growth to more of a client-centered growth where relevance, responsiveness, and rapid innovation drive real competitive advantage.

Jim Marous (01:33):

Today, I'm joined by Sean Viergutz, Bank and Capital Markets Advisor Leader at PWC to break down what this transformation means for leaders right now. We'll explore how banks can redesign operating models, build new capacity, and turn AI from a cost-saving tool into truly a driver of client value.

Jim Marous (01:55):

So, Sean, before we start the podcast, can you introduce yourself to our audience?

Sean Viergutz (02:00):

Sure. I think you mentioned Jim, I'm a partner at PwC. I look after our banking and capital markets, business on the advisory side. I've served largely the banking industry my entire career both as a consultant, but also as a practitioner, having spent a period of time at what was once SunTrust Bank in corporate strategy there.

Sean Viergutz (02:24):

I focus a lot on money movement, wholesale banking but have worked in just about all aspects and areas of banking from operations to strategy, to front office, and I'm very pleased to be with you here today.

Jim Marous (02:39):

As I mentioned in the introduction, the thing that I found to be most interesting in your research and the thing that really hit home, and we're seeing it more and more, is that speed is more important than size going forward with financial institutions, and AI becomes actually the transformative and performance lever independent of size.

Jim Marous (03:01):

That's a major shift from everything banking has ever been built on in the past 50 years. Can you walk me through what's actually changed to make speed a bigger, more important variable?

Sean Viergutz (03:15):

I think it's going to become the most important variable. I'm not sure it's quite surpassed scale just yet. I think it's forward-looking, the article we talk about. I would say scale has been the moat in banking as you're well aware, Jim, for forever.

Sean Viergutz (03:37):

And so, those that have had the largest discretionary dollars to invest in technology, to invest in acquiring customers, to invest in all of the different areas that drive a competitive advantage have typically come from the largest banks that have had that scale.

Sean Viergutz (03:58):

What we're seeing and what we're continuing to expect and forecasting here is a bit that speed and being able to address a client's needs and become the bank that offers hyper-personalization, the bank that leverages and harnesses the power of AI and intelligent automation more efficiently than others will effectively have a what we would like to describe as a front end and back office, no middle office type function.

Sean Viergutz (04:28):

Can you go straight to offering nimble products and services? You can enter new markets, you can do partnerships with interesting fintechs kind of on a moment's notice because you're able to harness your infrastructure differently than others.

Sean Viergutz (04:43):

And so, do you really need, as an example, do you want to modernize your technology or rip out an old application, do you need 1,000 to 10,000 to 20,000 person offshore centers when with the ability to do coding and infrastructure replacements with a much smaller team because if you're able to harness AI to write code for you, to test that code, to deploy that code, it doesn't require the massive investments that we've seen today.

Jim Marous (05:17):

It's interesting because it's not just the organizations that are smaller that’re being able to do it themselves, but we're seeing that more and more of the third-party partners, the solution providers out there are providing that kind of scalability as well.

Jim Marous (05:34):

I mean, we don't have to go back more than five years to realize that the biggest changes are that now, the solution providers are making it so you can build composable solutions that really move the market really quickly and make it so that, again, AI is the foundation for a lot of that, but a lot of the dynamics as we look at it, we have partnerships now that can make it so a financial institution can put in place a brand new digital account opening experience or an onboarding experience in three months.

Jim Marous (06:05):

We used to think about these things as being yearlong projects, if not longer, and organizations are actually rebuilding their core. And are you seeing that speed and the ability to scale with AI is maybe a component of resilience where we always thought of resilience being based on fraud and risk. And what does this mean for a $2 billion community bank that's competing with the big guys?

Sean Viergutz (06:33):

Yeah, I do. I do see nimbleness, agility (and when I say nimbleness and agility, I mean that in terms of your infrastructure and your technology) as absolutely being an element of resilience going forward. I think to answer the first part of that, yes, we've absolutely seen software providers, solution providers already move to this more nimble, agile infrastructure and solution set. And I think those clients that have already moved or started selecting those packages really stand to benefit the most from this new technology.

Sean Viergutz (07:12):

Because all of those solutions, these headless cores, et cetera, all require a bank and a finance institution to have understood their data sets and organized in a way that harnesses the data before you can implement those, so does AI, and so does this new technology really requires you to understand and harness data. So, if you're able to do one, you're able to do the other is the logical conclusion there. So, that's one piece of that.

Sean Viergutz (07:41):

Look, I think you started off the podcast with a very astute point that the largest global banks have made largest investments in this technology, and they're harnessing benefits from it. So, two are the neobanks. So, even below that $2 billion threshold that they've been able to start from a blank sheet of paper, and thus that gives them some starting power.

Sean Viergutz (08:02):

In the middle, what does it mean for the $2 billion bank and up in that kind of community bank? The answer to me is pretty simple, it gives them a chance. It gives them a chance to modernize their infrastructure and the technology that they've already been indebted to in a way that doesn't break the bank, if you will.

Sean Viergutz (08:26):

Each one of these community banks has made investments, whether it's in a core that's a SaaS solution, some level of infrastructure, some level of software, and they too need to modernize. Now, it may not be at the same scale of some of the largest banks, but for them, it still represents a very large investment and a time suck from people that need to be focused on the market, and this allows them to do that.

Sean Viergutz (08:50):

The other thing I would tell you is the community banks have made a competitive advantage of theirs as being feet on the street. I know Jim, I know Jim's business' needs, and thus, I'm best positioned to serve them.

Sean Viergutz (09:02):

Well, I think the other thing that these banks need to be aware of is that may not be the case in the future, because as data becomes more freely available and other larger institutions that may not have a physical presence in that area are able to understand something about small community bank's customer set, they're going to have those targeted hyper-personalized solutions whether that's to a commercial client, to a corporate client, or even to the normal retail client.

Sean Viergutz (09:33):

So, this is not a moment to sit and watch, this is a moment to really understand, start to play with, start to empower your employees to harness this technology because it's very much the same as the internet was, that Excel was, that moving past anything that was analog into digital is. We're moving past analog/digital into this kind of embedded world, and AI's only going to make you get there faster.

Jim Marous (10:00):

It's interesting, it underlies your entire report, it underlies everything that I'm seeing in the marketplace as well in that there's a gap between what can be done and what's actually happening or what's actually being deployed, what's being focused on the back office as opposed to those that are being focused on the outward experiences and engagement.

Jim Marous (10:25):

From your own personal perspective, and you work with organizations of all sizes that reach out to you – how important – and it's kind of a loaded question, it's an easy one to answer in a sense, but at what level of importance and what differentiates the organizations that can versus those that do?

Jim Marous (10:46):

The thing that we see often is that leadership and cultures may be more important than the technology itself, because you can't buy yourself out of not deploying things correctly. What do you see in the marketplace and what differentiates, 1, $2 billion community bank from another or one mid-major financial institution from another, from a perspective of actually being able to do what's possible?

Sean Viergutz (11:15):

I think it's a great question, and I think you partially answered it yourself, Jim, around leadership and talent, but I'll take a step back because I want to hit on that point. But I think there's the evident AI index that sits out there, and I think what's interesting about that is you have a smattering of relatively different sized banks making market progress against harnessing the power of this new technology.

Sean Viergutz (11:40):

I think of our clients that we work with, those that are making the most progress in doing not just talking about, have really done a couple of things. One, it's a leadership imperative whether that's at the board or that's at the op-co/ex-co, it's at their table and it's being discussed routinely. So, that's one.

Sean Viergutz (12:03):

Two, there's a defined strategy around it. There's a lot of institutions that we work with that start with, "Hey, can you walk me through the use cases? Can you tell me where I go and deploy AI to get the biggest bang for the buck?" And that's kind of the hammer looking for the nail.

Sean Viergutz (12:19):

And while that may provide immediate impact by hitting the one or two things, it doesn't create the groundswell cultural shift that is really necessary to make sure that AI and harnessing that technology is a lasting thing that has staying power within an organization to get the multiple effects of next use case and next use case and next use case.

Sean Viergutz (12:43):

So, I would say leadership, focused on it; second is having a defined strategy that harnesses the bank's strategy before so it's not a wholesale rewrite of the strategy, but it is alright, now we have this new, game-changing, generational type technology, how do we execute faster? What are the things that we might do differently now that we have this other variable to address?

Sean Viergutz (13:07):

And then the third that I don't think get's talked about enough, Jim, is talent. I think if you look at the companies that are out there behind some of these LLMs, there's been a real war on talent, like in terms of acquiring and attracting with packages never seen before. And I think that just goes to show that those that really understand at the deepest level what these technologies are capable of understand that at the core, it's the talent and the individuals that drive these models.

Sean Viergutz (13:39):

And so, I think the institutions and banking and capital markets companies that understand that as well and go find that talent that is going to be a champion of this technology, that is going to find a way to infuse it within their management layers, and thus, in their employees and that finds a way for their operating models to be such that it harvests and empowers employees to do more with it and not do a hub and spoke controlling function, are those that are going to continue to find success building on each other.

Jim Marous (14:18):

It's interesting because that was one thing that really came out of our research that 90% of the bank executives say the winners will be those who invest in capabilities they currently lack, yet I believe it was only 25% see workforce reinvention as their top strategic priority. Is that a disconnect? What am I missing there?

Sean Viergutz (14:39):

I think it is. When we went through the data, to me that stood out just as a stark data point that wow, one does not equal the other, and there's a miss there. It also stands out to me, which was pretty mind blowing, Jim, that if 90% thinks they don't have the capabilities necessary for tomorrow, I'd like to know who that 10% is, and have a conversation with the board. Because it's a bit like saying everything that's ever going to be invented has already been invented, I don't think anybody's ready for what's next.

Sean Viergutz (15:10):

And so, yeah, I do think it is, and look, I think there are some and there's been quotes from some very (and we don't mention client names as a firm) – but look, there's been quotes from some of the best CEOs that have run some of the largest financial institutions, very much zeroing in on the fact that talent matters.

Sean Viergutz (15:29):

Talent matters and making sure that management and some really talented management understand the power of this technology. It's very hard to do anything and make sure that there's a pervasive cultural shift within an organization if the leadership itself doesn't understand the power of a tool or a technology or buy into the strategy. So, I think it really all starts at the top.

Jim Marous (15:55):

It's interesting, we also see, and it's the underlying talk, is that every single employee at every organization (not just banking), they're looking over their shoulder because they're worried about what AI is going to do to their job. And if organizations don't make every employee at every level aware and help them move forward in a way that in their mind at least secures their position, they're going to be out there either looking or not performing at their peak.

Jim Marous (16:29):

And it amazes me how we at all levels of the organization forget that it's still a business that's driven by humans. And every human says, “Yeah, I love your talk about digital banking and using AI, but the other part of me is scared to death about what that means.”

Jim Marous (16:45):

If we don't make human transformation part of the equation, the human experience is going to lack, and therefore, when you're working with customers, when you're working at new initiatives, when you're working at innovation, all that fails as well. It's a crazy thing that seems so logical, but it somehow gets thrown under everything else that's very technology-based.

Sean Viergutz (17:11):

And here's the difference, I think, between good leadership and those that have embraced this conversation around AI versus those that are the hammer looking for the nail, and we've got just the cost cutting approach and how do we find efficiency.

Sean Viergutz (17:26):

One, on the let's just find efficiency in the hammer nail basically looks at a function, says, "Hey, how do we take 30, 40% of our workforce out of this area?" And that's very hard to do without breaking the chassis. The other says, hey, this is a one center generation transformative technology, let's harness it, let's figure it out.

Sean Viergutz (17:50):

And actually, it's interesting there's a professor out at Stanford who does a great job of providing a great example at basically any corporation, they're empowering the employees to say don't treat AI like a search engine, treat it as a teammate. You have a deliver, we have your job. Ask it, “Hey, if you were going to do this job, how would you do it differently? How might you do it more effectively?” Ask, kind of play off each other.

Sean Virgutz (18:15):

And so, in that instance, you're not competing against AI, you're treating it as a teammate, a leverage point, something to learn from, something to get better at. And so, the more you get better at your job and the more value you drive from this technology and this agent, you are going to use it more. and it's only going to make you more effective.

Sean Virgutz (18:35):

And thus, it's less around, “Hey, how do I do more with less, it's around how do I do more with the same amount of people because now I have not just a thousand workers going to 500, I have 1,000 workers with the power of 2000 to 3000 to 4,000 to 5,000 because I've got these agentic teammates there.”

Sean Viergutz (18:53):

And I think those are the institutions that have cracked the code on this, and have moved to the North Star of providing not only efficiency, but then creating a culture of adoption and not a fear of what this technology can do.

Jim Marous (19:11):

Sean, that is so insightful the way you put it, and it's interesting because it's the missing link. Unfortunately, banking traditionally, as long as I've been involved, which is almost a half a century now, but the reality is financial institutions tend to quantify that next cost-cutting move without looking and saying this whole generative AI, agentic AI, AI in general is really a workforce enhancement tool, and we need to communicate that across the entire organization, otherwise, everything we're trying to achieve, there's going to be people trying to poke holes in it behind our back.

Jim Marous (19:56):

We've seen this in so many different ways, and I think your perspective on that was really new to what we've talked about in the past. As we move on, talking about bank leaders, bank leaders think that generative AI and Agentic AI as the most transformative force in the industry, I think it was like 58%. Not only is that not surprising, but when you look at it, I'm concerned because I'm not too sure if they know the difference, number one; and number two, I'm not too sure if they really know how to implement the different tools.

Jim Marous (20:34):

What do you see as the future of both generative AI and agentic AI from your definition point, and are we getting to a point where we can actually leverage that so the consumer benefits as opposed to simply the bank?

Sean Viergutz (20:50):

So, I don't disagree with your observation, I think people use the terms (I watch it all the time) interchangeably, and they're very different. So, maybe just for those listening, we can demystify.

Sean Viergutz (21:02):

Generative AI is the technology that allows us to create, whether it's images, text, et cetera, generate, generative AI from prompts, prompts that are done by prompt engineers, AKA humans. Agentic AI is the orchestration of tasks, jobs, generative tasks, et cetera, research tests, deep research autonomously, like not done, not prompted by Jim or Sean, and I think that's the difference.

Sean Viergutz (21:32):

And so, to me, the organizations that are starting to really get that step function accretion in their organization from AI have moved to the agentic piece. They're orchestrating tasks across the organization, across the middle office, across the back office autonomously with oversight in a responsible AI framework. And that's where I think you're going to find the power of whether it's cost savings or streamlining and removing friction in the ecosystem and achieving the speed that we've been discussing on this podcast.

Jim Marous (22:18):

Let's take a short break here and recognize the sponsors of this podcast.

[Music Playing]

Jim Marous (22:25):

We talk a lot about the back office improvements, how it's used within the finance institution. What are you seeing in the marketplace or what do you expect to see in the marketplace where the consumer's really going to get (I'm going to look at the consumer as a small business, the corporation, the customers of the financial institution) – are actually going to feel the benefits of what generative AI, AI can do. When is it going to impact?

Jim Marous (22:54):

I know my financial institution knows me. I'm not too sure if they understand me, and they certainly don't show it on a day-to-day basis. What do you see in the future with regard to the way that differentiation can actually be achieved in a way that a customer feels it?

Sean Viergutz (23:15):

I think you see some of it already, and there are in your mobile phone bank apps assistance that help answer questions and help find the right products and services for you, and they've been around for a little while, and those will continue to get better.

Sean Viergutz (23:30):

To answer the question around what's the timing? I don't have the crystal ball, Jim. I will say it's not going to be as soon as I think the efficiencies and the applications will be for the bank. I think for all the reasons that have been widely discussed within our industry and sector, it's going to start in the back office, in the middle office, and non-customer-facing applications and processes. Just because it's safe, you don't want to do any kind of undo customer harm, and so, there's some things you can do there and find efficiencies.

Sean Viergutz (24:03):

I do think though it will shift very soon within the next year or two if I had to give a date. Like as we start to modernize the infrastructure and the application layers of these banks, you'll start to see this move into these hyper-personalized products very quickly.

Sean Viergutz (24:22):

And I think the quicker that a bank can get there, they have that first mover advantage to get out in the marketplace at scale and offer something that's differentiated, I think we talk a little bit about, I mentioned earlier, analog, digital embedded, hyper personalization. I think a lot of people think we're at embedded and hyper-personalization, and I disagree. I think every industry is kind of the same in my opinion. When you strip away a lot of the different pieces there Jim, I think we all follow.

Sean Viergutz (24:53):

I mean, take the auto automotive industry. You had the Ford Model T, that was the version of analog. One product, no customizations, that's what you got. That's how banking largely was. You had the deposit account, you had the ledger, you went and took a note out back in the early 19th century, that's how you would do things.

Sean Viergutz (25:12):

And then you moved to digital where you had a car and you could get a couple different engine type horsepowers, you could get different colors. And today, I think that's where we are. We're in this digital phase where yeah, you can get a bank account with different flavors to it, you can get a sweep, you can get a loan, and it's got different amortization periods that then necessitated different interest rate, et cetera, et cetera, et cetera.

Sean Viergutz (25:37):

But it's not really personalized and it's not specific to the corporate, the commercial client or the customer. And now, I think the bank that can actually get it to where I already call the automotive industry there, where you can just basically choose just about any color, any customization, you can actually after purchasing the car download software to make it different, you can purchase different services within your vehicle.

Sean Viergutz (26:00):

I think banking's headed there right away, and you'll get this knock-on effect once you can open up adjacent ecosystems whether it's into health services, whether it's into technology media, telco type companies through your banking experience and have these partnerships, that's I think where the power of this is going to come to generate revenue.

Jim Marous (26:24):

So, how do you see … we talk about the modernization of core, modernization of mobile banking, digital transformation, all this. And it's interesting as the industry continue to make improvements, people are rating their mobile apps as really strong, all that, but there's no differentiation. How do you see or do you see differentiation among financial institutions ever taking place to the point where a customer just doesn't think they're moving from Green Bank to Blue Bank to Red Bank?

Sean Viergutz (26:58):

It's a good question. Look, at the end of the day, banking products (it goes, I think a little bit back to my comment before) and services in and of themselves I think when you look at what the remit of the bank is, manage risk and hold deposit safely for a customer and a client. It's the how do you get beyond that remit to a differentiated service?

Sean Viergutz (27:29):

To me, it goes back to the can you open the ecosystem of opportunities and adjacent industries around the customer, that's really going to be the differentiator. I don't know that a customer looks at Bank X as “Oh, they're the ones that know me best and I'm more interested in banking with them because of their products and services.”

Sean Viergutz (27:53):

For example, I'll give you an illustration of what I'm saying. If a bank, as I go and open an account knows that I love to travel and spend 30 days of the year traveling to four different continents and five different countries like yourself, Jim, and hey, I want streaming services and I want to be able to earn points globally and X, Y, Z – and because I open that account and because maybe then I get free memberships and additional points and additional services, if that's the type of experience because they know something about you, and there's an account and there's a service, and then there's knock on services that I benefit from, then that's when I think you start to show up differently for your clients than you do today.

Sean Viergutz (28:38):

But I don't know that any institution – obviously it's a regulated industry, so there's rules of growth. But not every institution's going to make that kind of switch in their head to say, "Hey, we can only go so far, but the benefit to attract customer X and Y may look like partnership ecosystem very differently than it is today."

Jim Marous (29:00):

I couldn't agree with you more. I think it's those that can move fastest to know what I want maybe before I even know it or will partner with me and what I'm going to call (and it's strong word because it's not used exactly the same) – in an empathetic way that says the more you know me and understand me, and the more you develop services around the way I am, the less likely it is that I'm going to search out that other organization that I hear can do some of those things.

Jim Marous (29:33):

Because right now, I talk about the fact that we've all developed our own open banking solutions where we use multiple institutions to serve what were our very simple needs in banking at one point, but it become more involved, more from the way they do business, maybe the way they open accounts, maybe the rates they offer, but more importantly, maybe just the way they handle me.

Jim Marous (29:56):

It's interesting, your reports show that only 10% of banking leaders believe that their current technology stack is leading edge. And more than just the technology stack, but I think most financial institutions believe they're still only catching up when not a decade ago, we were ahead of the consumer, ahead of the customer, ahead of the small business, ahead of the corporation as far as what we were offering; now, customers at all levels kind of know what should be able to be done. What obstacles are in the way of financial institutions catching up?

Sean Viergutz (30:35):

It's funny, we did a similar parallel piece just around a multi shop world Jim. And what was meant by that is like the pace of change in the wave of these new variables coming towards banking leadership and these organizations is unprecedented.

Sean Viergutz (30:54):

Like it used to be, you'd go through the cycle and there was very much the term of like, oh, just got to manage through the cycle, whether that was a credit cycle or some type of geopolitical change, and now these cycles aren't cycling, they're stacking.

Sean Viergutz (31:08):

And so, you've got to build a decision framework, a strategy, a management team that understands the importance of adaptability and nimbleness to manage 3D cycles and make decisions. And I think that's what we've somewhat seen, Jim, is organizations become frozen to some degree.

Sean Viergutz (31:27):

Oh, there's this new technology, oh, there might be a regulatory change; oh, there might be a different person in the White House, so let's wait for X, Y, Z. There might be legislation coming, the economy looks like X, like there's so much to consider. It'd be very easy to say, "Hey, how do we wait?" But I think it's just not a possibility. You've got to start making progress against some of this and investing.

Sean Viergutz (31:52):

And I think making sure you've got a framework that stratifies no regrets, decisions, hey, this is imperative, we're going to go do it, I think it's important. So, I think to answer your question, I just think some organizations become frozen and waiting to see what others are doing and the more that everybody becomes frozen and waits and sees is one thing.

Sean Viergutz (32:09):

I think the other reality is there's benefit in looking for help outside of your organization to moving forward with some of these initiatives, whether it's replacement in technology, et cetera. Because there are firms like PwC that have, I think, done a really nice job of understanding the power of AI and others, but also (and we talk with our banking clients all the time about this), it's not just about using a third-party provider because the power of this is finding a way to harness it internal to your own organization.

Sean Viergutz (32:43):

So, some of this just takes time to make sure that your own employees are harnessing the power and doing for themselves versus being reliant on third parties. So, it's a little bit of a balanced scale here, which is you've got to make progress, you've got to start building wins and modernizing technology, infrastructure, your workforce skills, et cetera.

Sean Viergutz (33:07):

And you can certainly, I'd say expedite and kickstart some of that with a third-party. But ultimately, you also need to make sure that you're doing that on your own and becoming self-reliant and building those skills internally.

Sean Viergutz (33:19):

So, making sure that you are kick-starting, but also then transferring those skills is important to ensuring that you're making progress in this space. And I think there's a lot of institutions that are still struggling with that balance.

Jim Marous (33:33):

So, you don't just present facts in your report, you actually create a three-question, CEO playbook. Could you discuss a little bit about that because you actually take what you found and give suggestions and you give insights and tools for financial institutions. Can you discuss a little bit about the playbook?

Sean Viergutz (33:54):

Yeah. The playbook, it goes back to the framework I just mentioned. It’s a bit what are the things that we should be considering? What are the no regrets decisions we can start making now, and how do I make progress? I think that's really what it's about, there is no silver bullet. There's no, here's the only way to make progress with AI, there's no silver bullet in the way to start measuring success within an organization.

Sean Viergutz (34:20):

But it provides not only tools and a mechanism to make progress, but it also provides tools in our framework for CEOs and boards and C-suite to start challenging how they think about measuring their business performance.

Sean Viergutz (34:36):

Because I actually think, and one of the things that my colleagues and I discuss within the paper is, efficiency ratios are measured as X today. And there's a top quartile, middle of the pack, bottom quartile – that's going to look very different in a handful of years.

Sean Viergutz (34:54):

The efficiencies that used to be top and best class, maybe bottom quartile going forward. And so, it also provides a framework by which leadership teams can start to assess how do we start preparing for what good looks like tomorrow, not just today, and how do we start measuring ourselves against that new rubric?

Sean Viergutz (35:13):

So, there's a little bit of both practical, tactical guides to start getting forward, start getting started and what are some no regress decisions, but also what's a framework by which to measure progress and also measure the business performance in the future.

Jim Marous (35:27):

Essentially, you mentioned the Evident research, and we had the CEO of the company on the recent podcast and the thing that got to me was the fact that people were taking bits of what they found and saying that there aren't returns on AI investments when really what they found was too many organizations are not measuring the results of their AI investments.

Jim Marous (35:53):

You keep on referring back to the measurement and making sure you're keeping measurement tools, knowing your North Star and then measuring against that. It seems again, logical as business 101, but the reality is we sometimes forget to set those measurement parameters to say, "Oh, by the way, how are we doing against what we said we're going to do?"

Jim Marous (36:15):

Finally, research we've done found that only 7% of financial institutions are right now achieving their digital transformation goals. The technology is available, the business cases are in many cases pretty clear, we understand how important it is for leadership and culture to align.

Jim Marous (36:39):

What do you suggest organizations do differently as they enter 2026 to actually move the needle beyond where we are today more than simply, I'm sorry, hitting the tick box to say, "We've done this, this, this, this." What are you seeing?

Jim Marous (36:59):

And maybe it goes back to some of the engagements you have and maybe some of the frustrations you feel when you're meeting with financial institutions, going, "Man, we got to get beyond the basics." But what do you suggest organizations do in 2026 that may be different than what they're doing today?

Sean Viergutz (37:15):

It's a good question, and it's a bit hard to answer because I think some are making the right steps and others are still in early innings. I'd say for those that are in early innings, if they haven't started including the topic of AI in meetings with their board and their ex-cos, and then also asking their corporate strategists, how are we redefining success in three years with this new technology? Start there.

Sean Viergutz (37:46):

Start at the very basics of make AI a conversation within leadership and quarter your strategy because that's what's important. I think those that have moved past that and have started to find maybe they're struggling with seeing the success and the rollout and the execution of that strategy, I think I would ask them to take a step back and say, "Hey, well, how is your management layer one or two below that ex-co really championing AI, and are you doing what we discussed earlier?”

Sean Viergutz (38:21):

Are you just looking for it to be a cost-cutting mechanism or are you really empowering the employees to harness the power of AI as that agentic team that they may work with? How are you finding space and allowing space organizationally for somebody like Sean not to just think about, "Hey, I've got to close my loan and get through the fulfillment process, but hey, I'm going to take time away. I've now been freed up to reimagine this process myself, and so I'm not having to drive the bus while also change the wheels on the bus." So, a little bit of that, how do you create the environment and the capacity to have change within the organization, would be the second thing I'd say.

Sean Viergutz (39:00):

And then the third is for those that have I think really understood and empowered employees to use the technology and they're seeing gains, I think it goes to that agentic AI piece, moving past the generative piece: how do I use it to do my job, ask questions, generate answers to how do I now understand the power of orchestrating across organizations and re-imagining that process to the next level and really implementing it.

Sean Viergutz (39:29):

And then look, part of this is also, I think thinking through and empowering your teams to measure, as we talked about differently. It's very hard to say within, for example, an engineering organization, oh, this isn't working because we still have 30,000 people in our engineering org.

Sean Viergutz (39:50):

Well, if that 30,000 people, and thus the same cost base is now generating outcomes and deploying code and generating 3x lines of code that they did before and modernizing at a faster pace and moving technology layers quicker, then you are doing it more efficiently and it is working, you're just not measuring the productivity output differently. So, it just depends on also how you measure.

Sean Viergutz (40:17):

And I think that would be the thing that I would also challenge the management layers, is really think about how do you measure the business differently so that you can get a pulse on AI then maybe you just measure from the traditional ROE/ROA efficiency ratio metrics that we look at today that may mask some of the value that it's driving, which is hard to do when that's what frankly the markets and investors are focused on too.

Jim Marous (40:43):

Interesting. In somewhat a self-serving way, I suggest that those who have listened to this podcast also tap into some of the other podcasts we've had around the implementation of AI and financial services. We've had great interviews with Ally, which I think is one of the leaders of what's being done in the marketplace; we've had interviews with Galileo and other organizations that really talk about the integration of AI across entire organizations as opposed to making it project-oriented.

[Music Playing]

Jim Marous (41:13):

Sean, the interview's been tremendous, we have to have you back more often because I think that sometimes, it's always good to have somebody that's on the show that I agree with everything they say, and we get along really well with the dynamic for where we want the marketplace to move.

Jim Marous (41:30):

But I think it's a situation where we can't let the train get further and further ahead of us, we've got to bring the whole organization together. You keep on bringing it back to organizationally from top to bottom, inside and out, we got to be pulling the same direction. They can't be a project orientation, it's got to be democratized in many ways.

Sean Viergutz (41:51):

And I think the great days of banking are still ahead of us, but I can't remember how long you've been in the industry, but this is the most fun the industry's been in a long, long, long time. And I think the potential's there, it’s just a matter of whether or not we'll grab it or we're going to be making excuses for the challenges we have that everybody has. So, thank you so much for being on the show today. I really appreciate it.

Sean Viergutz (42:15):

Thanks, Jim. Thanks for having me. I appreciated the time today.

Jim Marous (42:19):

Thanks for listening to Banking Transformed, the winner of three international awards for podcast excellence. If you enjoy what we're doing, we would really enjoy a positive review. Also, check out my recent articles in The Financial Brand and the research we're doing for the Digital Banking Report.

Jim Marous (42:34):

This has been a production of Evergreen Podcasts, a special thank you to our senior producer, Leah Haslage; audio engineer, Chris Fafalios, and video producer, Will Pritts.