B (2:54)

Yeah, really important.

A (2:55)

Absolutely. Frank, 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?

B (3:12)

No, Great question. And I have a running joke that executives don't really buy AI, right? They buy faster revenue, lower cost, better expenses, experience, reduced risk. Right. So I always coach the teams to reframe this and think through this in more 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 then AI to really affect those, those business outcomes? So example of reframing, you know, client came to us, hey, hey, I need to have AI in customer service. And we said okay, well what does that mean? Let's reframe that. Is it around reducing meantime resolution? Is it boosting csat? Is it T itself deflection? Is it reducing headcount, lowering cost? And then once you have those business value maps, you can now go back and say, hey, here's where 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.

A (4:27)

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 thing. Where's the value in that technology as far as 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?

B (5:00)

It's funny, they're 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 and, 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 or 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 unlock. 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 client said, hey, we need to migrate off our current HR platform. We said, okay, let's understand that some more. You know, we went in, we mapped their employee journey. We realized that they could get most of the value, the business model just by standardizing some of the requests on the existing platform and then in 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, these, these journeys. A very important part of the solution space.

A (6:53)

Thank you. Appreciate that. Customers do like, oh gosh, I need that new tech because it's, 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 H R I S 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?

B (7:35)

Yeah, I believe high performing enterprises will feel really orchestrated, right? Where work flows to the right person or even AI agent automatically. And really every one of these steps is, is assisted by AI. It's going back to hr. Imagine an employee onboarding request where the request approvals, access, training, all flow automatically assisted by AI. And that whole kind of onboarding and new hire experiences is best in class. Again, that's a great example of invisible AI, but yet orchestrating a really complicated set of processes around that. So I think our solution approach again centers around three core capabilities, right? Really understanding these native workflows and how to embed AI, how to leverage the operational data for real time insights that guides those processes. And then lastly is 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 one time transformation project. I think this is a new ongoing way of working.

A (9:06)

Thank you. I really appreciate you highlighting some of those things. High performing enterprises I believe will be well orchestrated. 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 workflow is embedding 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.

B (9:42)

Yeah Brian, thank you for having me.

A (9:44)

Bye for.