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Ron Schreiberg (Guest) (4:17)

Well, the testing part proved the most challenging for me and as they say, third time's the charm. And it took all three tests to finally get it to work. The first test was met with the fire leaders gathering around with audible laughter and dismissive content. Well, I plug everything in, I flip the switch, smoke, then fire. Actual flames. They offer me a goodbye chuckle as I packed up the equipment. And as I leave, I ask, I'll be back if you'll have me some re engineering. Several weeks later I returned for a second test and fewer leaders gathered this time, but the same antics persisted as they did during the first. Again, I plug everything in, I flip the switch. This time just smoke. To be fair, I learned from the first test. I disconnected power before reaching flashpoint. Let's just say this wasn't the sort of result you wanted when presenting to the second oldest fire department in the United States. I was up against a mountain of resistance from age bias, perceived knowledge deficit, and unproven digital technology to replace an analog technology. Again, I packed up in defeat and unsure. But I asked, I'll be back if you will have me. And really, what I learned from that valuable experience was that human nature leans us towards adopting technology. No matter the perceived resistance, technical challenges, or even the grumpy attitude of a soon to retire fire chief turned fire lab leader. The reason for this is really the desire to enhance our lives and our experiences through technological adoption is far greater a force than the fear of change.

Brian (Podcast Host) (6:01)

Wow, amazing story. And it goes to show your persistence. Obviously working in a small family business and you go to a municipality like the city of Boston and when you're replacing antiquated equipment like that, you're under a lot of pressure to make things work. And, and I just appreciate your story of being vulnerable, telling it how it was, or your early 20s and up against some very senior folks that had a lot of experience, at least in the fire protection area. And it was, it was challenging. So I appreciate the story of the backstory on it, honestly. And Ron, at New Rocket, you're focused on delivering AI first solutions in banking, financial services and insurance. What are the biggest transformation opportunities you see in these industries right now?

Ron Schreiberg (Guest) (6:49)

Yeah, that's a great question. Thank you, Brian. Really the biggest opportunities I see is that the goal isn't necessarily more technology, so to speak, in business terms, it's really about fewer breaks in how work gets done. So modernizing end to end workflows, not adding point solutions where cost reduction, speed and control actually show up. And so there are really four themes I see. One is AI creates value when it scales judgment, not when it bypasses accountability. And so we prioritize AI that augments decision makers in risk operations and services while keeping humans responsible for the outcomes. The second is risk and compliance are really becoming strategic advantages, not just regulatory obligations. And so continuous technology enabled controls reduce cost, they improve transparency and, and ultimately strengthen the regulator confidence. Third is the data and governance determine whether AI becomes a multiplier or a liability. And without trusted data lineage and ownership, AI cannot safely scale no matter how advanced the models are. And lastly, fourth, this is an operating model transformation, not a series of pilots. So organizations that treat AI as a governed enterprise capability will really pull ahead. And those that don't are going to stay stuck in experimentation mode.

Brian (Podcast Host) (8:24)

Thank you, I appreciate that. And you're absolutely right. I've been in technology a long time and we see a lot of people, I've been asked, well, just throw more technology at it, that's going to be the solution. And it's not always the solution. You talked about that. Really, in some cases it's more efficient processes.

Ron Schreiberg (Guest) (8:42)

But you did talk about how you

Brian (Podcast Host) (8:44)

are leveraging AI and some of that research, risk and compliance, looking at controls, et cetera. But at the end of the day you got to have that human and a loop loop. And ultimately that human needs to be there for that final decision to make sure everything is correct. Because at the end of the day, humans are responsible for the outcomes here. So I appreciate that. And Ron, AI is rapidly being adopted across financial services. Where do you see AI delivering the most immediate value and where should organizations be more cautious?

Ron Schreiberg (Guest) (9:12)

Yeah, so what we're seeing is really AI is delivering near term value and financial services where it augments people, strengthens the control functions and improves operational efficiencies. The fastest and the most defensible returns are coming from risk and compliance, as I mentioned before, especially in the areas of fraud and AML augmentation, also back office automation and employee productivity tools. Right. We see this with Copilot and the use of ChatGPT and other models, but these are the use case cases that are leveraging the existing data sets, really helping preserve human oversight and align well with regulatory expectations. And so by contrast, right. Financial services need to be more cautious in the areas where AI operates autonomously, so directly impacts customers or scales without strong data and governance foundations. And I might give you an example in terms of like autonomous credit decisions, customer facing generative AI and even decentralized AI pilots introduce heightened regulatory, reputational and fairness risks, often without unclear accountability. And so as mentioned earlier, the bottom line is that financial services organizations that create AI as a governed enterprise capability rather than a collective of pilots that are going to realize measurable value today, those that don't, that do, move too aggressively in autonomous or customer facing use cases. Without strong governance explainability and data readiness, risk regulatory scrutiny will be increased, slow adoption and erosion of trust among stakeholders like customers and shareholders. So that's, that's kind of where, where we're seeing it.

Brian (Podcast Host) (11:01)

Thank you. And I, I do love this. I talk to people from all across the spectrum about AI and, and I love getting into this. Here is risk compliance financial services. But you did talk about AI being really augmenting humans now in financial services, which is great. And the biggest concern you're seeing is in the fraud and compliance area. And I think AI can certainly augment humans to do even a better job. Again, human in a loop always, of course. So again, I appreciate your insights. And Ron, as we look ahead to the future, how do you see the convergence of AI, cybersecurity and enterprise platforms shaping the future of financial services maybe over the next decade?

Ron Schreiberg (Guest) (11:43)

Yeah, I think, you know, we're clearly at a precipice of AI. Definitely beyond hype and pilots enterprises are finding real value in the use cases. The ones we've mentioned about now think of AI as a fuel for acceleration. Right. The speed at which cybersecurity enterprise platforms are moving is Already astonishing. I think I'd leave you with five observations on this and that is the future bank is going to run on intelligent secure platforms and definitely not disconnected applications. That's to say, AI, cybersecurity and enterprise platforms are converging to become the core operating foundation of the institution. The second would be AI creating advantages when it's embedded in how we operate, not bolted on as experiments. And the true value is going to come from scaling judgment and control access across the enterprise, not in isolated pilots. Thirdly, I would say cybersecurity is no longer just defense, it's become a continuous control layer built into every workflow. So security, identity and resilience must be designed into the enterprise platform, not added after the fact. We've seen that in the past decade and the challenges that have resulted. Fourth, the trust will be engineered through data governance and explainability, not just brand reputation. And as AI becomes pervasive, transparency and accountability are just as critical as innovation. I'll leave you lastly with a fifth thought, which is this is an operating model transformation disguised as technology shift. Financial services organizations that align AI, security and enterprise platforms under strong governance are going to move faster, manage risk better, and outperform their peers.

Brian (Podcast Host) (13:38)

Thank you, really appreciate that.

Ron Schreiberg (Guest) (13:40)

Dash AI.

Brian (Podcast Host) (13:41)

There's so many different use cases today that it's already been applied and are

Stassi Schroeder (Tell Me Lies Podcast Host) (13:46)

I'm your host, Stassi Schroeder. Welcome to Tell Me Lies, the official podcast. What's the most unhinged thing of season three?

Ron Schreiberg (Guest) (13:55)

Steven because he's so evil, I do

Brian (Podcast Host) (13:57)

think he is misunderstood.

Ron Schreiberg (Guest) (13:58)

You see, everyone faces consequences. It's intoxicating.

Stassi Schroeder (Tell Me Lies Podcast Host) (14:01)

The writers just know how to trick you.

Ron Schreiberg (Guest) (14:04)

There's always a twist in this show, so nothing you would expect.

Stassi Schroeder (Tell Me Lies Podcast Host) (14:07)

Tell Me Lies, the official podcast now streaming and stream the new season of Tell Me Lies on Hulu and Hulu on Disney

Brian (Podcast Host) (14:16)

is being applied in some of these last couple industries and I talked about that on another podcast. I won't go into that. But beyond hype and pilots, I agree with you. AI is, I think almost mainstream people are trying to get their, their, their mind wrapped around it in some organizations, but it's certainly going to be a game changer. But you did talk a little bit about cyber and I think that's an important, important point to point out here is these because these platforms are being so interconnected, as you mentioned, I think being connected as a one operating system of your organization, you've got to deploy cyber and AI more in those control areas. Control points to be proactive against cyber risks and intrusion. So I I appreciate, again, your insights today. And Ron, it was such a pleasure having you on today, and I look forward to speaking with you real soon.

Ron Schreiberg (Guest) (15:08)

Thank you so much, Brian. Really appreciated the opportunity. Have a wonderful day.

Brian (Podcast Host) (15:12)

Bye for now.

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