The Role of AI in Digital Transformation – Digital CXO Podcast EP93

Hello, and welcome to the digital CXO podcast. I'm Amanda Razani, and I'm excited to be here today with Frank Fawzi. He is the CEO of in Inteper.

How are you doing today? Doing well, thank you for having me, Amanda. Good to meet you.

Happy to have you on our show. So tell us about Intel up here and what services do you provide? Yeah, happy to do that.

Uh, I'm excited to be here as well. One of my favorite topics talk about is intel up here, the business we're doing and what we're doing for our customers, uh, the companies we've been here steering our customers, the vertical that we serve, which are financial services, healthcare, insurance, utilities, uh, retail logistics, transportation for over 21 years. Um, top here is a sizeable company with, uh, thousands of customers that grown very rapidly.

Uh, we have, as one of our core values is to delight our customers. And in turn, as we've, uh, built that, uh, concept of how to deliver better customer experience to our customers, we focus our services and our products and our solutions, and how can we help our customers do the same to the consumer, to the consumers that they're serving. Uh, and really obviously over the, over time, this story did not start with ai, but it started with high scale, reliable, uh, mission critical communications between the business and its, its users as cons, consumers.

And over time, as we built more innovation and automation and our capabilities moving, uh, uh, the, uh, capabilities that, uh, more recently in, in, uh, adding, uh, uh, Jared ai prior to that I would, uh, call classic AI and all of doing that, they, they aim, the goal of the business is how can I help our enterprise customers be more efficient, being able to deliver better customer experience or patient experience in healthcare to their end users. Wonderful. So AI seems to be at the center of everyone's minds these days.

It's advanced very rapidly generative AI at the last couple of years. So, uh, what are your thoughts as far as, um, where we are right now with AI in the enterprise? Yeah, so tech waves happen every 10 to 15 years.

Uh, I really do believe this is massive tech wave, but one thing about tech waves, they tend to follow, uh, similar patterns, that there's definitely a hype. Um, and you'll have a lot of players starting to jump into the market, and then eventually the market, um, sifts through the different vendors and, and, and players in market and comes out with a set of, uh, providers that can truly deliver the business outcomes and the value that the technology promises to deliver. If you can't do that, if you cannot deliver business outcomes, this, you know, AI is just purely a technology.

If it doesn't serve the needs of the consumers or the customers that we serve, and in turn their consumers, then, then it's, it's not, uh, effective today. I would say that, uh, you know, having seen these tick waves, um, from back in the nineties, uh, with the, uh, with one of, with my, uh, last, uh, or early one of my first, uh, uh, venture backed firm and then onwards is every one of them fall a very small pattern. Today we're, uh, we're at the, um, cusp of moving from the early innings or early adopters, we're jumping on the technology, uh, where, where they're excited about the potential to having to validate that you can deliver that potential, you promise it to deliver.

So now you, Gardner refers to that as the, uh, uh, in this phase as the, uh, trough, trough of disillusion mets. I refer to it more as the, uh, opportunities to validate your solutions to, to the, to the consumers. So as a result, of course, uh, then with the customers that we have and built over the last, uh, several years as we've been, uh, delivering AI solutions prior to generative ai, and more recently over the last, uh, 18 months or so with generative ai, the key is what are you doing for me?

And what value delivering? What's the ROI, what's return on investment on the investments that they're making in our solution? How could our solution be self-funding early on?

So I think that's really where we are, uh, at this point. I think the, uh, uh, this is what I've noticed also though about this cycle versus the last few cycles is the, the time elapsed is a lot faster. Uh, it took several years to go from when the internet started, if you are thinking about Netscape and so on, and all the way until we got real commercially viable applications and uses for it.

And similarly with the fiber wave of the nineties, it took several years to get to that. I really do believe that this cycle is much more compressed. Uh, we've seen the move from hype to, to this, uh, uh, point of, uh, needing to, uh, you know, have a proof points of validation and, and about four quarters, um, versus other cycles that might've taken several course to get to this, or several years to get to this, uh, uh, to this point in time.

So, so that acceleration in the cycle is actually a good thing. 'cause I think as a result, uh, I anticipate in the course of 2025, every single customer, uh, if they're working with a, with a, an ai uh, provider to help them improve their customer experience, they'll be looking for real tangible outcomes. And if they're not, they're not the early adopters, but they're more in the middle of that adoption cycle, they'll be looking, looking at how can they deploy those validated solutions that can deliver the value so they're not left behind their competition, that, that cap competitors of the competition that has already deployed it.

Yes, this technology is moving very fast, and it seems like at the center of any digital transformation initiative, AI is a big player. So with that, the, the high demand for ai, there's a problem though with the GPU chips. Uh, so high demand, but low supply of, of necessary, uh, GPUs.

So what, what are your thoughts on this and do you have any solutions? Uh, we, you know, so there's a really, there's, so this, this, this cycle of, of supply and demand getting out of each other is not unusual at these early stages of every tech wave. We've seen this, I've seen this personally.

I think we all see this in different tech waves where you get, you get a situation where the supply gets ahead of the debate or the divide gets so that the supply, eventually they come, uh, together. Uh, we at Antelope, we're, we're not in the infrastructure layer, we're consumers of that infrastructure. So obviously we value the availability of adequate GPUs and adequate, uh, ai, um, models that, that can be available to us, uh, to, to make, to build the solutions.

We are much more so at the, uh, at the solution level of delivering, uh, that, uh, value and capturing that, helping our customers capture that value of, of, of the underlying, uh, technology such as the, uh, the, the chips and hardware itself, uh, as well as of course the foundation model and, uh, models and, uh, uh, the other, um, the other technologies, uh, such as vector databases arrives and so on that come around them. Uh, I, I do think that, uh, markets will take care of that problem and, uh, uh, despite eventually equalize, uh, but the key here, the key key here, because I, while GPUs are short supply and you don't want to get a situation where Spike gets ahead of the demand, those applications that we're building and delivering to our customers are creating real value, are really important, incredibly important, so that it could eventually batay that level of balance between supply and demand. So you mentioned, um, the healthcare industry and, um, it's not the only one that I'm seeing this, but, uh, I'm hearing a lot about copilots and AI agents that, that are, um, helping the staff and, and also the customers and improving the, the experience on both ends.

So from your experience, um, where do you see that going in the future? And, um, are there any roadblocks business leaders are facing when they try to implement these types of tools? Yeah, we, we operate, uh, in several, uh, fairly regulated industries.

Certainly healthcare is being one of their financial services, um, uh, insurance and, and so on. So those industries obviously have their own, uh, set of requirements and governance above and beyond what a normal any other business would expect, uh, to be able to use, uh, AI and deploy ai, be able, uh, to make sure that, that the AI solutions are secure, are accurate, and so on. We've, um, so speaking to healthcare specifically, and I, let me focus here on what we're seeing a lot of demand, which, which are multi-location healthcare groups, dental groups, MRI groups, um, you name it, uh, gi et cetera.

So we're, we're seeing significant amount of, um, of, of, of interest and demand and, and success in that multi-location. Why is that The case is a lot of these multi-locations need to standardize around a certain consistent communication between them and their patients, um, and, and do and, and be. And, and so think about a use case, like simple use case.

You know, we call your doctor, you call your dentist, you call your, uh, mark Lincoln, you wanna schedule scheduling is a time consuming, uh, element of interaction between a patient and a business. Well, imagine if you can take that out of the, uh, work of the front of worker and move it to, uh, a digital bot and AI agent that can, um, do a lot of the scheduling, changing its schedule, cancellations, reminders, and notifications. That's what we do.

And by taking that workload away from the, uh, the clinics a front office worker, they can now become much more focused on the interaction that they have with the patient as they walk through the door, uh, rather than be be on the phone, uh, responding and, uh, to, uh, an inquiry about a schedule or a change or something like that. That's the value we're creating for our healthcare part, uh, healthcare customers. Um, and certainly whether it confines of, of course, the privacy and HIPAA and, uh, all regulatory, uh, requirements within the healthcare, but scheduling is a really great application for that.

Uh, I would go into other ones such as, uh, insurance information collections, bill payments and others, uh, by taking a lot, a lot of these, um, repetitive, uh, and I would say, uh, somewhat mundane tasks away from, uh, the p healthcare practice, we can allow the practice to provide higher value to actions with their patients, uh, which, which obviously is ultimately useful for the patient, useful for the practice, and creates better engagement of their customer and patient experience, uh, without having to add a lot more folks, uh, in the front office, uh, to engage, uh, the customers as they look at, uh, support with those tasks, uh, use cases that I described. Absolutely. Well, if there was one key takeaway you could leave with our audience today, what would that be?

Um, you know, this is, this technology, uh, this technology and tech wave is, is massive. It will impact every single aspect of every business we operate with as consumers. The fact that, uh, uh, obviously Apple recently just rolled out the GPT capabilities, the iPhone 16, uh, has got put in the heads of every single consumer that uses Apple.

I'm sure other Androids so will do the same. All the fact that we're all gonna get much more comfortable with attracting, with AI agents, and as we get comfortable attract and accept accepting of AI agents, that's going to force, uh, force businesses to accelerate the adoption of the AI agents, AI customer experience and patient experience over the next 24 months, much more so than just us, the vendors, uh, explaining the value proposition, uh, that we are doing today to our customers. So I'd really truly see, uh, an an influx of, uh, use cases, demand and opportunities, uh, in this market for both the technology vendors as well as for the, uh, customers that can leverage this technology to help improve their delivery of their, of their customer and patient experience.

Wonderful. Well, thank you for coming on our show and sharing your insights with us today. Thank you, Amanda.

Pleasure meeting you. Thank You. All right.

And thank you to our audience. Stay tuned. There's more.