Welcome to Coruscant Technologies, home of the Digital Executive Podcast. Do you work in emerging tech, working on something innovative, maybe an entrepreneur? Apply to be a guest at www.coruscant.com forward slash brand. Welcome to the Digital Executive. Today's guest is Ron Schreiberg. Ron Schreiberg, a seasoned business development leader with over two decades of experience serving Fortune 100 clients in technology adoption with a focus on the convergence of cybersecurity, risk, IT, asset management, HR, and AI. Ron is leveraging his expertise in driving strategic initiatives, building the C-suite relationships, and delivering innovative AI first client solutions to enhance new rockets offerings in the banking, financial services, and insurance sectors. Previously, for 13 years as Senior Director, ServiceNow Financial Services at KPMG, Ron developed and implemented client solutions that drove efficiency, automation, and risk avoidance for Fortune 100 clients. Well, good afternoon, Ron. Welcome to the show. Thank you, Brian. Really appreciate you having me today. Absolutely, my friend. I appreciate it as well. You're hailing out of New York City. I'm in Kansas City, so we're just an hour apart, but sometimes it's hard to make these things work. So I really appreciate that. And Ron, if you don't mind jumping into your first question, you've spent over two decades working with Fortune 100 clients across cybersecurity, risk, IT, and now AI-driven solutions. What key experiences shaped your journey to where you're at today? Well, Brian, I have a very unique story I wanted to share as kind of a backdrop. And it happened very early in my career. I was working for a family business in the field of electrical contracting, and I just won a contract with a municipality within the city of Boston. See, I wanted to substitute some specified equipment that saved cost and improved experience. I was challenged with, you know, the substitution of a digital street corner call box equivalent for what they called as an analog game well system that had actually been in use for roughly 145 years since the early 1850s. And in order for me to receive approval consideration, it required months long submissions of documentation, schematics and design reviews. And once all that was completed, I was finally invited to begin the testing phase. And now, mind you, I'm in my 20s, and the testing was to be done in the city department lab among some of the most senior fire department leadership. 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 be back if you have me Some re several weeks later I return 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. 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 I just appreciate your story of being vulnerable, telling it how it was in 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 challenging. So I appreciate the story, 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? 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 costs, 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 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. 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, it's more efficient processes, but you did talk about how you 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 in a loop. And ultimately that human needs to be there for that final decision to make sure everything is correct. Cause 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 AI delivering the most immediate value and where should organizations be more cautious? Yeah. So what we're seeing is really AI is delivering near-term value in 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 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 treat AI as a governed enterprise capability rather than a collective of pilots, they're 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 kind of where we're seeing it. Thank you. And I do love this. I talk to people from all across the spectrum about AI, and I love getting into this here is risk compliance financial services. But you did talk about AI being really augmenting humans down financial services, which is great. Right. 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? 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. and 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. And 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. Thank you. Really appreciate that. But, gosh, AI, there's so many different use cases today that it's already been applied and 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 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 point to point out here is 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 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 thank you so much Brian really appreciated the opportunity have a wonderful day bye for now
