Paula Rivera:
Welcome to The AI Factor, the podcast where we unpack how AI is reshaping business, one conversation at a time. I’m your host, Paula Rivera, and on today’s AI Amplified episode, we’re talking to our partner community and doing a deep dive on how best to drive results through agentic AI and analytics. These aren’t just buzzwords, they’re the engine behind smarter customer interactions, faster decisions, and more value for our partners. Joining me are two experts from IntelePeer who live and breathe this every day. Mack Greene, Senior Vice President of Solutions Engineering, and Aqeel Shahid, Senior Vice President Channel and Alliances. Let’s kick off with a quick look at what’s happening in AI this week before we dive into today’s topic.

So as you all know, ChatGTP now comes with a memory which remembers style preferences, instructions across chats. AI tools are starting to behave more like co-workers than calculators, remembering preferences, adapting to users, and even suggesting next steps. Mack, if your AI assistant could remember one thing about you, how you work, what would you want it to know?

Mack Greene:
So Paula, literally when you were saying that question, it actually made me chuckle out loud because somebody I’m dating went through a standard list of questions and one of them was, “Hey, what’s in your browser history?” And as a guy, I just had to pause for a minute, but I was okay. I would say that memory function is critical. I wish it would remember to ask me, “What do you want me to be right now?” Because oftentimes I’m actually in there customizing it and giving it special instructions to work on a particular project or help me think about this, or my kid just walked up and needs help with her homework.

And it’s this eclectic mix of things where I need it to be this chameleon and just adapt to the background, so to speak, of where I am in that moment. And I oftentimes forget to go in and change that. And so I do waste a moment because it is taking my daughter’s chemistry homework as the basis of a response that’s giving me on a project that is completely unrelated. And you’re sitting there scratching your head, it’s like, “Well, is this thing hallucinating?” It’s like, “No, I set it up wrong.” So my answer would be, remember to ask me where I am right now.

Paula Rivera:
I love that because I too have that problem. And it’s funny when I’m using AI just kind of “for fun,” inevitably everything’s coming out professional because I mostly use it in my workday life. So I absolutely love that, and I think someone very soon will probably start doing that. Aqeel, if your AI sidekick could take one task completely off your plate, what would it be?

Aqeel Shahid:
Yeah, certainly not as cool as what Mack came up with, but, for me, it would be just taking the stuff that really is repetitive stuff that eats up a lot of my time. Like for example, putting together reports, basically combing through spreadsheets, identifying patterns, creating executive summaries, if all that can be completely, entirely automated that would be amazing because the number of hours I spend looking through all that stuff, which would be cut down quite a bit and would certainly help me. But other than the persona stuff that Mack talked about, that would really help me out.

Paula Rivera:
I have to say I agree 100%. I find myself sometimes doing tasks where I’m like, “This is so repetitive, why hasn’t this been automated yet?” So I think AI, as great as it is, it has a little bit of catching up to do, but once it does catch up, it will be even more of a force to be reckoned with. So thank you guys. Let’s start with some of the basics. Agentic AI refers to AI systems that can make decisions, take actions, and learn from outcomes with limited human involvement. But how does that actually change the game of the business? Mack, how is agentic AI different from traditional automation or AI models we’ve used in the past?

Mack Greene:
One thing on agentic AI, I agree with the definition you just gave I, because that term has been so amorphous as it’s been used almost, in many cases, overused in what we’re talking about. But if we take the definition as you stated it’s the ability to make decisions and move through an action. And that is what we are seeing manifest itself in the industry. It’s not just, “DO I understand what this user wants to do. Can I do an interview and ask them about certain things?” It’s being able to collect that knowledge, understand it in context, and then apply it to a system of workflows or processes that somebody may have and the AI implements it. The one part that’s still being worked, it’s that sort of learning as you go.

You talked a little bit about that memory function in the first question. We have to think long and hard about that as AI engineers because you don’t want AI to remember that, “I was just talking with Paula and now Mack is on the line, and I’ve confused those two conversations.” Paula’s conversation should be private to Paula and AI should manifest that workflow. But then when I get on the phone, it should also maintain that same level of privacy in that conversation with me.

Now, there may be certain things that happened in the dialogue or the way that I speak versus the way that you speak, and maybe AI does a little bit of better job with me than it does with you. And so right now we are taking those learnings, we’re anonymizing them, and then we’re putting a human in the loop so that we can feed it back into AI and have it learn and function better going forward. But I would tell our audience the key takeaway is agentic AI allows you to actually manifest real workflows, not just route people to a certain place or answer FAQs, but actually understand the problem, interpret the solution set, and mechanic the solution set for somebody live and in real time.

Paula Rivera:
I love it. I love it. Can you give us a real world example of how agentic AI works inside a business process?

Mack Greene:
Sure. Think of the most common thing that we all go through, right? You’re at soccer practice with a kid and you get that little beep on your phone, you go and look, and there’s a text message reminding you that you’ve got an appointment in two days to take little Timmy off to the dentist. And you’re realizing, “Well, hey, I’m at practice for the tournament. We can’t make that appointment.” And it’s 6:00 P.M. in the afternoon or evening. The only thing you do is write reply back and say, “Cancel, or, “Can’t make it.”

You can’t actually engage or call the office because the office is already closed. So imagine if agentic AI was behind that text message and you could reply back, “Hey, we made the next round of the tournament. We need to reschedule.” And that AI, one, could congratulate you for the success of your family and the team, but then work through options on getting that appointment scheduled live with you in a text message as you sit there waiting for practice to end. And so it empowers things that are maybe using AI in some construct, but allows you to move it forward in a much more elegant and connected way to meet clients where they are in the moments that they’re trying to solve something.

Paula Rivera:
Elegant connectivity. I love it. I love it. Aqeel, what makes the shift to agentic AI so important for companies looking to scale or improve their customer experience?

Aqeel Shahid:
Yeah, I mean, I think the big thing is as the consumers are evolving in this space, patience is not something that is a gift anymore. We want solutions, we want them fast, we want them now. And I think what really is happening now with solutions that are coming in the space that offer these agentic AI solutions, that it really removes the bottleneck of manual processing that often delays customer service or customer issue resolution, right? When the AI solutions can handle the routine analysis, escalation routes, and allow the human agents to focus on complex problem solving, relationship building, that really improves that overall response time customer satisfaction, and allows now for these human agents to go really focus on these escalated issues. And therefore they’re fresh, they’re focused. And then the modern conversational AI solutions really don’t feel robotic anymore. It maintains the context across the interactions, can hand off seamlessly to human agents when needed, and just creates this holistic, unified experience, which obviously leads to a better agent experience and customer experience as well.

Paula Rivera:
Nice. So we have elegant connectivity that leads to a human-like experience. I love it, you guys. You’re giving me a lot of great words to use as I move forward in my life.

Aqeel Shahid:
Exactly. That’s what we’re here for, Paula.

Paula Rivera:
I love it. So agentic AI can only be as good as the data that drives it. And that’s where analytics come in. Let’s explore how these two work together. I’m going to start off with Mack again. From a strategy standpoint, Mack, how do analytics make agentic system smarter over time?

Mack Greene:
That’s a good question. And not to get too heavy on the wordplay, but I do want to borrow a little bit about what Aqeel just said is that human-like experience. And if we think about our own experiences with let’s say customer service or support, it’s oftentimes an effort of last resort because you’d rather find that answer on the web or you might rather find that answer on an app. But to pick up the phone and call, let’s say, or to go do something, you’ve exasperated other self-help things that are out there that are probably not AI or other experience. And so you’re maybe in a position of frustration, you’re potentially in a position of certainly encountering some challenge, again, that you couldn’t solve for yourself. Data makes us so much better in that because it allows us to focus in on the elements of that experience that matter.

Some of it gets into a higher level, things like sentiment analysis, how is that end user expressing how they’re feeling? But most importantly, it allows us to understand how the system’s being used, where it should be used and the effectiveness of its use. And when we can put those three legs of a stool together, we’re able to go create very powerful solutions. And we take these human-like experiences that Aqeel just talked about, and we turn them into an ambassador experiences where people are actually happy to engage and talk, and it creates more brand loyalty, it creates more awareness of other things that a particular practice or firm may be doing, and it connects the dots in so many more ways than we’ve ever been able to do before.

Paula Rivera:
Wow. I love it. And I love AI as an ambassador. I don’t know if I’ve ever heard it described as that before. Again, a term I will probably coin as my own. So I love that Mack. Thank you. So Aqeel, what kind of analytics are most valuable for partners to surface when making the case for these solutions?

Aqeel Shahid:
Yeah, when partners are obviously engaged in these conversations with their customers, the big thing to Mack’s point, again, is really looking at what is that intended outcome that the organization is trying to solve for? And so when you’re looking at it from a CX lens, you’re looking at it as far as from an analytics perspective, how long does it take for you to resolve that issue? So the time to resolution metric. What is the cost per interaction that is happening when a customer calls in or when you’re making an outbound call to a customer for that agent? What are some of the satisfaction CSAT scores that you’re basically holding your organization accountable to before and after implementation? I think those things are important so the partners can help identify a baseline as well as kind of a goal or where they’re trying to get to.

Obviously you want to be more predictive and you want to be able to use the analytics to basically look at what the resolution is going to be today, but also predict on what problems they’re going to solve for ahead of time. But keeping an eye on some of those key metrics are critical. The other thing I want to say as well is that partners, as they’re working through the solution designed with their customers, showcase things like, “Okay, if I’m going to implement a conversational AI solution, how does this capture the rich interaction data? Not just what the customers asked for, but how did they feel? What value did they really get out of it? What is it that the customer was really hoping to accomplish when they ask those questions? Where did the friction occur?” And this all creates a goldmine of insights for continuous improvement. So I think being engaged, being able to identify those key metrics are critical in order to prove ROI and success in a project like this.

Paula Rivera:
Excellent. I love that. And you said something that I think is so important that a lot of people don’t think about. It’s having a baseline to start with. And I think people just kind of jump on in and then they’re like, “Let’s talk KPIs.” And I’m like, “Well, if you don’t know where you’re starting, how do you know where you’re going?” And I think it’s what you just said is so important for partners to be able to explain to their customers, “Listen, let’s establish that baseline so that way we have a clear path towards what your KPIs might be.” I totally appreciate that. Mack, are businesses prioritizing real-time analytics differently now than a year ago? Which I’m inclined to say is yes, because within the past year, well two years really, things have changed so much. Could you shed some light on how they may have changed?

Mack Greene:
Sure. No, absolutely they are. Every business wants to have every touch with their customers or their patients be a positive one. And the reality of it is that you have to distribute that across many, many different levels of staff. It could be somebody in a call center, it could be somebody at the front desk, it could be a nurse in the exam room, it could be a doctor making a follow-up call. And there’s so many ways right now, specifically with data in AI, that we can go back and look at conversations and learn a lot about them. And to Aqeel’s point, and I’m going to go back in time a little bit, we all probably remember the rubrics that our teachers would give us, probably starting somewhere in high school and probably saw a lot of them in college. But they were effectively frameworks on how to do something, how to get to an A.

And we are actually able to take those constructs, train AI on what they are, and then have AI go and listen to everything and do so in a secure and private fashion, but then push feedback to us. And so that whole needle in a haystack to find the really good conversations or find the conversations that need, let’s all call it some coaching, some feedback, AI gives us that capability. Imagine if you knew that your doctor had a backup there that’s going to double check that every protocol got followed, that every follow-up question got asked, and that you can walk away safely and securely about that diagnosis. And that’s part of an ecosystem that, again, is that ambassador, so that whenever you touch that healthcare practice, that system understands you as a patient and your uniqueness and is reacting to you in that way with your follow-up appointments.

They understand perhaps you’re not in a good place health-wise and you need to get in and it can get you onto a wait list and can manage that wait list so that you’re able to go see that practitioner face-to-face like you need it as you work through your journey. Or it’s just again, something mundane as, “Hey, I got my bill and I don’t quite understand why the patient responsibility is so high. Can you help me connect the dots?” And all those things in between. So. again, that human-like experience where we can connect things in a way because AI can run behind the scenes and keep that engine going constantly and provide a elevated level of care and an elevated level of experience.

Paula Rivera:
I love it, and I think it would be fair to say an elevated level of insights that a year or two ago weren’t really readily available as they are today.

Mack Greene:
Oh, absolutely, absolutely, absolutely.

Paula Rivera:
Excellent. So agentic AI and analytics, not just an innovation story, it’s really an opportunity for customers and for our partners. Let’s talk about what the channel needs to know. Aqeel, what are you hearing from partners? What excites them and what confuses them about agentic AI and analytics? I’m going to jump in and say the word agentic may be a key point of confusion. It would be interesting to hear if partners are hip to agentic AI or if they’re like, “What is this agentic AI and how is it different?”

Aqeel Shahid:
Yeah. What’s interesting is AI has become such a big buzzword. You can’t go a few minutes into any conversation anywhere, let alone within an organization without AI being used, right? It is insane. Everyone’s talking about it. Not a lot of people know where to start and what the differences are. So the challenge I’d say that, obviously, a lot of partners are faced with is, “Okay, great. AI, great, how do I start? Where do I begin? What can I really do?” So I guess the exciting part about this is that there’s a ton of opportunity. There’s a ton of greenfield opportunity for partners to really go out there. The market is demanding it, conversations are happening in boardrooms, leaders are asking for, “Hey, how do we use AI to help get better, more efficient, go out there and really streamline processes, help improve efficiencies?” All that fun stuff.

And so that is all great. And so from a partner community perspective, I think that’s a real opportunity for us to go leverage that and be able to really grow the overall wallet share and be able to have these conversations and provide something that’s unique and really solves a critical problem in the organizations that are evaluating these options. So that is critical, but you’re right, there’s still a ton of confusion. What is agentic? There’s a lot of these buzzwords that are floating around the space right now. So confusion often stems from understanding the difference between traditional automation and true AI agency. Many partners really struggle to articulate when AI is actually making decisions versus following rules, as well as being able to really even start a conversation with a customer. And so even when you talk about conversational AI, a lot of people think of chat bots.

Well, okay, that’s one component, right? They’re still thinking of rigid menu-driven interactions when true conversational AI can handle natural language. Remember previous conversations, as Mack mentioned, right? Adapt its communication style to match the customer. There’s a lot of those things that are around there. And so there’s definitely a ton of opportunity not only for the customers that these partners are talking to you, but even for the partners themselves to really get around the solution, learn more about it, make themselves knowledgeable, make themselves be those true, trusted advisors for the organization and help them navigate through, I would say, in that early life cycle right now where people are exploring kicking tires with AI and how they can use and deploy and be able to leverage the ROI associated with it.

Paula Rivera:
Oh, I love it. I love it. Let me ask you a question. Right at the end there you used that term trusted advisors, which I love. What resources and what support does IntelePeer provide to help our partners succeed and truly become trusted advisors for their customers?

Aqeel Shahid:
Yeah, that’s a great question. And, again, certainly we make sure that we are here to support our partners in every stage of their conversations with their customers. A true trusted advisor really is that subject matter expert for their customers. With the pace of technology at the speed at which things are evolving, there’s no organization that has somebody that can keep up with that pace, to learn and be that expert on their own. And that’s really where these trusted advisors come in. They’re essentially the SMEs that understand the market landscape. They understand the different players in the market landscape, who has what strengths, what weaknesses do they have, what is the best solution given the scenario that they they’re trying to solve for. And so they really are bringing in a true value to the end customers from a decision-making perspective and allowing them to really focus on the core aspects of their business and leverage the expertise that trusted advisors have to navigate them through the waters.

And so it’s important for trusted advisors in order to continue being trusted advisors, is to leverage the support system that’s in place. For example, at IntelePeer, we really have the support system in place to be that subject matter expert, especially for a advisor that’s still learning how to navigate the AI waters. With folks like Mack and his team, us bringing us in early in the sales stage, so we can come alongside them, join forces with them, lock elbows, and be able to go into these opportunities together to leverage the expertise that we’ve developed and allow them to use that, use cases that we’ve seen, problems that we’ve solved, things that can really help from an ROI perspective.

Again, they don’t have to go build it on their own. They don’t have to recreate the wheel. The wheel already is created and we’ve now been able to see success around it. And so we want to make sure that we have those resources available and then whatever elements they need from white paper perspective, marketing perspective, things that really allow from a conversational starting perspective as well. We make sure that those resources are available for our partners to leverage so they can use those to start those conversations with executives within organizations, especially around this AI journey. And as they’re getting ready to embark on this journey to help them navigate accordingly.

Paula Rivera:
I love it, and I love how you and your team work to really help the partners succeed. I believe I heard somewhere along the way that you actually will allow partners to “shadow” us-

Aqeel Shahid:
Correct.

Paula Rivera:
… as we go through a sales process so they can see, “Hey, this is how you talk about AI, this is how you would sell AI. This is maybe some of the questions customers have.” And that kind of helps give them a degree of comfort around that whole process of effectively selling something that they may not be 100% up to speed on. Is that something you could provide a little bit more color on?

Aqeel Shahid:
Yeah, absolutely. I mean, again, this is us being, as a new technology as it is, a lot of partners don’t really know what the motions are. So yeah, we’ll bring our partners along the journey with us into opportunities where we’re already currently engaged. Or an opportunity that maybe that a partner has found that may be a good fit for us, but they’re not sure about it. “Well, let’s go. Let’s get in there together,” and we can really go through that process alongside with them. So, again, they don’t have to go be that subject matter expert. We’ve got them covered through the process so that they can see exactly what it is, and if it’s a brand new opportunity that we’ve uncovered on our own, but the partner brings some key attributes, like, for example, if it’s in healthcare vertical, the partner really focuses in that vertical and understand the challenges faced in the organization, they can now come alongside us to help.

Paula Rivera:
Love it. And every time I talk to you, I’m always impressed about the fact that it really, truly is a partnership. We’re working together to achieve one objective. And, I don’t know, that makes me happy. So kudos to you and your team. I love it. So I’m going to turn to-

Aqeel Shahid:
Hey, we’re only as good as our partners.

Paula Rivera:
I’m going to turn to Mack now. Mack, how should partners be positioning these solutions with their customers?

Mack Greene:
Oh, wow. That’s kind of a wide-ranging question, but maybe I want to double click on what Aqeel just said, which is understand that the support is there and there is a reality in the marketplace that the AI transformation is happening. So if their customer is not engaging in a dialogue with them, then either two things are happening. They’re talking to somebody else or their customer’s competition is talking to somebody else, and their business will be at a disadvantage. And if we take that concept of trusted advisor, that trust is based upon certainly what Aqeel described, but being at the forefront and helping their customers maintain their businesses, leveraging the latest and greatest techniques. And not just experience, but it drives additional revenue, it takes cost out of the business.

And so when you put, again, those three things together, it is a whole nother thing. We have a lot of engagements coming to us from people that aren’t traditionally talking about automation. They’re experts on security or they’re experts on infrastructure, or they’re experts in other elements of their customer’s plan or their solutions. But the reality of it is is that they need these solutions to maintain the competitive edge. And so they should just simply be pushing it that way because if their client isn’t using it today, their client’s competition is and their client needs to stay ahead.

Paula Rivera:
So appreciate that, and I love the fact of it’s such a salient point. If your customers aren’t talking to you about it, they’re talking to someone else. So start the conversation. If they’re not having it with you, you have it with them. I think that would be key takeaway.

Mack Greene:
Absolutely.

Paula Rivera:
Excellent. So let’s boil this down to what really matters. If you’re a partner navigating AI and analytics, what should be top of mind? I’m going to stay on Mack now. What’s the number one thing you want partners to understand about agentic AI?

Mack Greene:
That it is a useful and thorough tool to help their clients move to a higher level. And I don’t want to lean too heavily on what Aqeel said, but again, just to double click on it, that support umbrella or that support envelope is there. They don’t need to be the experts. They need to continue to do what they have been doing all along, which is maintaining that level of trust and being an advisor to their clients. And we’ve got the mechanics and the mechanism and the expertise to help them come in, understand a scenario or a set of use cases, do the appropriate discovery and help them lead that conversation to a place where hopefully there’s a synergy between the solutions that IntelePeer has to offer and where their client is looking to go.

Paula Rivera:
I love it. Aqeel, from a go-to-market perspective, what’s the smartest first move a partner can make?

Aqeel Shahid:
Yeah, I think the smartest move that partners can make, obviously do what Mack said, come in, and, one, make sure you’re leveraging your resources. There’s a ton of resources that we have, make sure you’re asking and leveraging that. But the other big thing is don’t try to boil the ocean. I think the big thing a lot of partners sometimes do is that they over promise and they’re trying to solve everything at once. That’s not a good way to do that. So I think the best thing a partner can do is really start with a pilot program focused on one specific measurable pain point, right? Don’t try to solve everything at once. Then by just focusing on one specific thing, you can prove value in a narrow use case first, then expand.

This obviously builds credibility, creates concrete ROI stories for future prospects and sets you up for success because, again, with emerging technology, like what AI has to offer, the last thing you want to do is go down a path where you’ve set unrealistic expectations. The customer doesn’t get the ROI that you were hoping to accomplish because you have such a large scope of what you’re trying to accomplish. Scope kicks in, obviously, and Mack, you can relate to that, and it doesn’t prove to a great experience for anybody involved. So it’s critical to just start small, fix that, test that, then move on to the next and so on, so forth.

Paula Rivera:
Excellent. So besides boiling the ocean, which we all know is impossible, Aqeel are there any other common mistakes or missed opportunities you’re seeing that partners should avoid?

Aqeel Shahid:
Yeah, I think the other big thing that I sometimes see is that sometimes partners will look at the overall solution as far as opportunities they’re concerned of from an AI perspective and just one specific element. They’re not looking at all the other components that they can leverage, such as analytics and data. For example, if you’re looking at conversational AI, they basically approach conversational AI just like a chat bot. Very often I’ve had conversations with the partners and they go, “Yeah, you guys are providing a chat bot solution.” Like, “Well, no, that’s only one component, and there’s a lot more to that,” right? And so you get too focused on the deflection rates, how many calls can they avoid, rather than the quality of the conversation, the customer satisfaction that it’s basically providing. And then obviously that leads to a frustrating experience where customers feel like they’re trapped in AI loops because all you’re focused on is deflection rather than the other components.

I think the other thing that I see from my perspective from a missed opportunity is that they’re not leveraging the conversational data being generated because there’s a lot of data to what Mack mentioned earlier that is being generated. Every interaction is creating insights about the customer intent, the pain points, language patterns. And partners aren’t necessarily mining this intelligence to improve both the AI and human interactions. So those, I think, are critical elements that can really be avoided if they really start out the journey with a proper end goal in mind. And, again, going back to the fact leverage, the resources that are available, because that’s what they’re there to do is to help you through that journey so you can have the best experience possible and showcase not only what the trusted advisor has to offer, but also what the providers have to offer in this space as well.

Paula Rivera:
Nice. Mack, any common mistakes you’d like to point out that would help our customers help our partners as they move forward?

Mack Greene:
I want to say no, outside of being overly cautious. And I think that’s a little bit in what Aqeel was saying is that there are many, many firms that we actually are encountering that are saying, “I’m not going to use it in a customer facing solution because it’s not ready.” And we literally have millions of calls that say otherwise. And it goes back into that continuum of where is your client and where is your client’s competition and the viability of their business? Imagine if 50 years ago your accountant said, “Eh, I don’t need a calculator.” Imagine if 30 years ago somebody said, “Eh, I don’t need the internet. It’s not ready.”

Imagine if you were trolling around Times Square at the turn of two centuries ago and saying, “Eh, I don’t need an automobile. This horse and this buggy is going to get me wherever I need to go.” We’ve seen transformations on a multitude of different levels out there, and the people that are up on the top and riding the wave, drive to a higher level of success. And others are just simply caught by the wave and tossed onto the beach. So I’d probably say the biggest mistake is just simply not embracing the technology and looking to move forward and finding ways to move forward.

Paula Rivera:
Wow, you just put me on a beach, which is so appropriate for Friday afternoon.

Aqeel Shahid:
I know. I know, right? Exactly.

Mack Greene:
Actually, you guys sent me home from the beach because I was standing here there with my cigarette lighter, expecting the ocean to boil and realizing I probably should go home.

Paula Rivera:
Oh wow.

Mack Greene:
I hope you enjoyed the stay.

Aqeel Shahid:
That’s too funny.

Paula Rivera:
I’ll send you my horse and buggy and you can ride that home.

So before we wrap up, I like to do a rapid-fire round of questions. And these are just some fun lighthearted questions to get to know you guys a little bit better than your titles and a little bit more than all the great information you’ve provided this afternoon. So I have three questions here. I’m going to ask them of both of you. Answer as in-depth as you would like. It could be a one-word answer or you could expound upon your thoughts. We’re kind of open to both. But the three question, what’s one AI myth you wish would disappear? If you could use AI to predict one thing in business, what would it be? And one word to describe the future of AI and analytics in the enterprise. Mack, I’m going to start with you. One AI myth you want to disappear?

Mack Greene:
That AI agents hallucinate all the time.

Paula Rivera:
Okay. If you could use AI to predict one thing in business, what would it be?

Mack Greene:
Five stock picks that I should transfer my portfolio over to right now.

Aqeel Shahid:
Yeah, that’d be amazing.

Paula Rivera:
Yeah, I think we all was that.

Mack Greene:
And I should add predict successfully.

Aqeel Shahid:
Yes. That would be amazing.

Paula Rivera:
Yeah, not the next bankruptcy.

Mack Greene:
No, no. Yeah.

Paula Rivera:
And one word to describe the future of AI in analytics in the enterprise.

Mack Greene:
Transformative.

Paula Rivera:
Transformative. Nice. Okay, Aqeel, on to you. One AI myth you wish would disappear?

Aqeel Shahid:
I think from my perspective, the big AI myth I wish would disappear is that the AI will replace human workers entirely. The reality is it augments human capabilities and handles a routine tasks so people can focus on creative problem solving, but would never replace human workers.

Paula Rivera:
I like that. And I used to work for a company that had one of these huge think tanks where people would sit around with their cigars and their brandy snifters and pontificate on the future of the world at large. And one of the gentlemen there, very smart guy, used to say, “It’s going to create a lot of new jobs we never thought about.”

Aqeel Shahid:
Exactly.

Paula Rivera:
And a lot of those jobs would be jobs that are just using AI in unique ways. It could be using AI to help you as a caretaker. So yeah, I like that. I think for headlines and click bait purposes, of course we’re going to take the scare tactic, but I think you’re spot on with that Aqeel. All right. If you could use AI to predict one thing in business, what would it be?

Aqeel Shahid:
Well, besides predicting the great stocks I should invest in, I would say probably customer churn risks. So be able to identify in a predictive way what my churn risks could be so I could get ahead of it and be able to create some real value with the three to six month runway as opposed to being reactive.

Paula Rivera:
Oh, I love that. And I haven’t really heard a lot of people talking about that, but I bet you’re onto something there, Aqeel. Okay, last question. One word to describe the future of AI and analytics in the enterprise?

Aqeel Shahid:
I would say symbiotic because I think the most successful companies will be those that seamlessly blend AI capabilities with human judgment.

Paula Rivera:
Excellent. I like that quite a bit. So gentlemen, we are finished for this afternoon. I want to thank you so much for joining us. This has been a real treat talking to you. I always walk away a little bit smarter. And today I definitely have a few more phrases to add to my nomenclature. So I want to thank you both for joining me this afternoon.

Aqeel Shahid:
Thank you for having us, Paula. I appreciate it.

Paula Rivera:
Thank you. Mack, thanks for joining us.

Mack Greene:
It was absolutely my pleasure. I thoroughly enjoyed the conversation this afternoon. Thanks for having me.

Paula Rivera:
Wonderful. It was so great to have you guys again. Thank you. So agentic AI and analytics aren’t just powerful on their own. They’re exponentially more valuable together. As Mack and Aqeel have shown us today, they represent a major opportunity for businesses and partners alike to deliver proactive, personalized, and profitable experiences. Big thanks to our guests and to you, our listeners. If you found this conversation helpful, be sure to follow The AI Factor wherever you get your podcasts. Until next time, I’m Paula Rivera-