Welcome to Corazon 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.corazon.com-flashbrand. Welcome to the Digital Executive. Today's guest is Frank Palermo. Frank Palermo is the chief operating officer of New Rocket, where he helps guide the company's growth strategy and strengthens its position as a leading advisor in digital workflows, AI, and enterprise transformation. He brings decades of experience building and scaling technology and consulting organizations with a career that spans software engineering, enterprise platforms, cloud data, and AI-driven services. Frank is known for combining deep technical fluency with clear operational vision and for helping clients translate modern technologies into meaningful business outcomes. Well, good afternoon, Frank. Welcome to the show. Thank you, Brian. How are you today? Awesome. I appreciate it. Appreciate it. You're making the time. We're traversing one time zone today, your New York, and Kansas City. So I appreciate that. Making the time, Frank. And Frank, jump into your first question. Your background spans software engineering, enterprise platforms, cloud data, and AI. How does this technical range shape your approach as a chief operating officer, especially as AI becomes a cross-functional priority? You know, it's interesting. I kind of look at this as become bilingual in a way and in tech and business. So I think the advantage of this experience is you can really press your test ideas, press your test strategy against what's actually buildable, what you can get in production. I think most importantly, it's grounding these tech ideas in business value. I still view technology as an enabler of the business functions. So in the past, leading engineering teams, for me, has always been about channeling the enthusiasm of new tech things, even in the AI era, right? To really force them to think through business outcomes, to force them to think through value realization. So on team shows me a demo or pitches an AI idea. I really start to ask them to pivot to think more about data quality, about latency, about performance, about operational support. It's not just about the demo. It's really about how does this now integrate into existing businesses. So leveraging your technology understanding in your past, I really sharpened judgment around what actually can provide business value. Thank you. And I appreciate that. It's not just looking at the novelty of AI or a new emerging tech. You really want to make sure that it integrates into the business and it makes sense and supports the business goals. Like what you said earlier, you're granting the technology into the business value. I thought that was really interesting. You're really important. Absolutely. For many leaders struggle to connect emerging technologies like AI automation, workflow intelligence, with business outcomes, executives really care about, what do you bridge that? How do you bridge that translation gap for clients? No great question. And I have a running joke that executives don't really buy AI, right? They buy faster revenue, lower cost, better experience, reduce risk, right? So I always coach the teams to reframe this and think through this in more of these business terms. But yet, there's a lot of experimentation. There's a lot of top down mandates that are coming. How do we use AI? But I really think it's so critical to reorient the customer on business outcomes and how do you apply that AI to really affect those business outcomes. So example of reframing client came to us, hey, I need to have AI and customer service. And we said, okay, what does that mean? Let's reframe that. Is it around reducing mean time resolution? Is it boosting C-sad? Is it T-itself deflection? Is it reducing head count, lower and cost? And then once you have those business value maps, you can now go back and say, hey, user automation and AI assistance in that workflow can really move those needles significantly. So I like to think that the best AI solutions are when AI is invisible, right? So if AI is invisible and it's focusing more on the delivery of these business outcomes, I think that's much more valuable for organizations. Thank you. And I do appreciate that. What you said executives don't buy AI or emerging tech, but what they do focus on is that growing or protecting that revenue, maybe regulation, business outcomes, that sort of goes thing, where's the value in that technology as far as it's aligning with the business? So again, I appreciate that. And Frank, at New Rocket, you're shaping strategy around digital workflows and AI-driven enterprise transformation. Where are you seeing the biggest gaps between what companies think they need and what they actually need to modernize effectively? It's funny, there's still very much in a platform and tools mindset. So we frequently meet organizations and they've bought all, they're involved in all the AI platforms. But they haven't really thought through their basic foundational issues like our fragmented processes or inconsistent data, no clear product owners within the organizations. And so a lot of times they just think, oh, I need a new tech platform and they want to pivot to the next model. So I think it's really about getting back to thinking about these platforms and the technology as enablers. And really the first thing we think about is where's the real value in lock? And what we find is this is typically embedded in how the organization is working. So we really get into the context of those workflows. We really understand what's behind the business intent and you really need to do, I think persona and journey mapping and really understand what those day-in-the-life journeys are to identify those efficiencies and then think about how does data really become the enabler of these workflows. And then after all of that is done, now you can get to this point of now, where do I apply AI? It's really hard for AI to be successful if it's amplifying a broken or inefficient process or it's amplifying poor data quality. So one example just in the HR context, we were born in a clinic and said, hey, we need to migrate off our current HR platform. So we said, okay, let's understand that some way. Now we went in, we had mapped their employee journey. We realized that they could get most of the value of the business, just by standardizing some of the requests on the existing platform and then the layering in AI, intelligent routing and knowledge management on top. So to me, modernization is less about buying the tools and more about aligning workflows, the data and the people around these journeys. These journey is a very important part of the solution spaces. Thank you. Appreciate that. Customers do like add attached any that new tech because they think maybe it's going to improve their metric or their business or something. But I love how you help them reframe and look at what really is the business intent here and where are you going to provide most value in that example with that HRIS system that you looked at. That's absolutely just spot on. I think when you have someone with a different set of eyes looking at something, you might be able to look at some alternatives. So I appreciate that. And Frank, the last question of the day, looking ahead, how do you envision AI and digital workflows reshaping the modern enterprise? What capabilities will define the high performing organizations of the future? Yeah, I believe high performing enterprises will feel really orchestrated, right? Where workflows to the right person or even AI agent automatically and really every one of these steps is assisted by AI. It's going back to HR, imagine an employee onboarding requests with a request approval access, training all flow automatically assisted by AI and that whole kind of onboarding and new higher experiences is best in class. Again, that's a great example of invisible AI, but yet orchestrating a really complicated set of set of processes around that. So I think our solution approach in centers around three core capabilities, right? Really understanding these native workflows and how to embed AI, how to leverage the operational data, right? For real time insights that guide those processes. And then lastly, it's more culturally where we believe that employees that co-create and work alongside AI to really amplify their productivity. I think there's a lot of misinformation around AI as the replacement for the human worker. And really in my mind, it's all about amplification and this kind of co-working model. So I think that the winners, enterprise winners will move fast but responsibly. And that means governing data and the AI use, but investing in skills and continuously learning on these workflows rather than just treating this as a long time transformation project. I think this is a new ongoing way of working. Thank you. I really appreciate you highlighting some of those things. For performing enterprises, I believe will be well-ordestrated as you stated. They do move quickly but prudently. And a couple things I want to highlight. We talked about really these high performing organizations having native workflows and betting that AI in there. But the human and machine co-creation I think was really important. That's what I took away for that better output. There's a lot of misconceptions about how AI is coming out to take everybody's job. So I really appreciate that. And Frank, it was such a pleasure having you on today and I look forward to speaking with you real soon. Yeah, Brian, thank you for having me. Bye for now.
