AI Strategy, Enterprise Adoption & Turning AI Into Real Business Impact | Benjamin Dowd | AI Accelerator Podcast

AI is everywhere but very few organizations are actually turning it into real business impact.

In this episode of the AI Accelerator Podcast, host Matt Zembruski sits down with Benjamin Dowd, CEO of The Phoenix Firm, to explore what it really takes to move from AI hype to execution.

With over 20 years of experience advising enterprise leaders across Canada, Central America, and South America, Ben shares how organizations can modernize, automate, and scale using AI in a way that delivers measurable outcomes not just ideas.

As a Certified AI Consultant and former Senior Banking Executive, Ben brings a unique blend of financial expertise, strategy, and hands on implementation experience. His work focuses on helping leaders bridge the gap between ambition and execution, designing AI adoption roadmaps that actually work in the real world.

Together, they unpack how organizations can build AI strategies that drive clarity, control, and competitive advantage while avoiding the common pitfalls that keep companies stuck in theory.

In this episode, Benjamin reveals:

◼️ Why most organizations struggle to move from AI ideas to execution
◼️ The difference between AI hype and measurable business impact
◼️ How to design AI strategies that actually deliver outcomes
◼️ Why governance and AI literacy are critical for success
◼️ The role of intelligent automation in scaling operations
◼️ How leaders can align AI initiatives with real business goals
◼️ Why enterprise adoption requires more than just new tools
◼️ The importance of change management in AI transformation
◼️ How to build clarity and control in AI driven environments
◼️ Why data driven decision making is at the core of AI success
◼️ The biggest mistakes organizations make when adopting AI
◼️ How executives can lead confidently in an era of intelligent transformation
◼️ Why operational excellence matters more than experimentation alone
◼️ How AI can create adaptive and scalable business systems

Key Learnings

✔ AI success depends on execution not ideas
✔ Strategy must be aligned with measurable business outcomes
✔ Governance and AI literacy are essential for sustainable adoption
✔ Intelligent automation enables scalable transformation
✔ Change management is critical in enterprise AI initiatives
✔ Data driven decisions are at the core of AI enabled organizations
✔ Leaders must bridge the gap between vision and execution
✔ Operational excellence matters more than experimentation alone
✔ AI requires both strategy and hands on implementation
✔ Organizations must move beyond hype to achieve real impact

💬 Benjamin’s Most Powerful Quotes

“Organizations don’t fail because of lack of ideas they fail because of lack of execution.”
“AI is only valuable when it creates measurable business outcomes.”
“Strategy without implementation is just theory.”
“Clarity and control are what turn AI into competitive advantage.”
“Leaders must move from ambition to operational excellence.”

Follow Benjamin Dowd

LinkedIn: https://www.linkedin.com/company/thephoenixfirm
Website: https://thephoenixfirm.ca/
Spotify: https://open.spotify.com/show/5fHRe53AqHuVS3YimmIZv1
YouTube: https://www.youtube.com/@ThePhoenixFirm-h8j

Follow Matt Zembruski

Website: https://leadingaiagility.com
LinkedIn: https://www.linkedin.com/in/mattzembruski/
Facebook: https://www.facebook.com/mzembruski
Instagram:

Transcript

SPEAKER_00 0:00

Welcome to the AI Accelerator Podcast. I'm your host, Matt Zembruski, founder and CEO of AI Agility, where we help organizations build superhuman workforces. Today I'm joined by Ben Dowd. Ben's a certified AI consultant and former senior banking executive who now serves as CEO of People Focused Enterprise AI. With over 20 years of leadership experience spanning North America, the Caribbean, Latin America, Ben has guided organizations through major transformations at institutions like Scotia Bank and beyond. Today he helps enterprise leaders move from AI curiosity to measurable execution through hands-on training, operational transformation, and fractional chief AI officer services. And there might be even more there. We're going to find out real soon. Ben, welcome to the show.

SPEAKER_01 0:49

Matt, thanks so much. That sounds like a very long uh you know more about me than I do. But it's great, it's great to be here. Absolutely. And uh, you know, in the world of AI now, it's it's very, very different from what I was doing for the rest of my career, but absolutely thrilled to be in it, no question.

SPEAKER_00 1:08

That's fantastic. And so, so Ben, let's let's dive right in to let you, you and I got a chance to meet earlier, but for our audience, a lot of corporate executives, CEOs, et cetera. Um, um, you know, you spent 20 years in banking and financial services and in a lot of leadership opportunities you've had there before pivoting to AI consulting. And AI is obviously the rage across the world right now, but I know you you and I share the passion for people in that AI. As much as it's a technical rev technology revolution, uh, there's there's people at the center of it. So, what was the moment where you realized that AI was going to fundamentally change how organizations operate and you know made you really decide to go all in on serving people through this transformation?

SPEAKER_01 1:55

Uh yeah, so it's actually been going on for a few years now, uh, where the availability of AI has been growing and growing, and uh the use of it has been growing. Shadow AI, of course, as many employees are using. Um, and why? Because they can see that their productivity is going up and up and up, their output is going up. And so, you know, as I as I work on the customer side in particular, uh, for my entire career, working with the people, um, you know, how do we actually use the technology that's now available to benefit the the end user and benefit the employees themselves? And so a lot of decisions were being made that I could see very, very clearly in various organizations that I worked with to invest primarily in the IT side because it could do this now. And so typically, from an IT perspective, that was always the first, the first mover. Like, let's go to IT and let's make sure we invest. And you know, as you as you talk to many organizations, they're absolutely willing to invest, um, but they have put their money aside on the IT side of the budget um and and not on the on the people side of the budget as needed or the operations. And so this for me was really an eye-opener. Um, that yes, AI is here, it's here to stay. Um, when I entered the workforce, email was already being used, uh, the internet was already being used regularly. Um, and you know, frankly, we haven't seen any major shifts in our operations since that time. We've we've you know made it better and better as time goes on, but it's still functionally the same way it was being done, you know, 20, 30 years ago. Um, and so with AI, though, you can see very clearly that it will and should shift operations very significantly. And of course, as you and I talk about, what does that mean for the people component of it? Because I don't want folks to be concerned about well, what what's next for me? What am I going to be doing? I, you know, I used to sell uh horses for transportation, but now it's all cars. Uh, what do I do? What do I do? You know, that was that was in the past, and so now it's it's the same sort of anxiety that we see out there, and it's about okay, how do we help the people?

SPEAKER_00 4:12

Yeah, so let's lean into that a little bit more. I know you have some experience in um doing this fractional uh chief AI officer role, right? Which is a lot of companies that don't have that role in there at all, especially mid-market companies. Um, but a large enterprise, a lot of enterprises uh don't have it either. How would you say leadership, whether it's fractional CAI, um uh chief AI officer or another role? How can leadership understand transparently what's happening with their workforce? As you say, like this technology is coming in to major shift, to put people at the center and really empower the people with this technology. Like, what is what do leaders need to see, or how do they see that to really get into that?

SPEAKER_01 4:56

It's a great question. Um, what we're seeing as as you alluded to is the shadow AI and the availability that's there for employees to use to get the information they're looking for, to speed up their output and make life that much easier. It doesn't replace them by any means, but it does make them superhumans. Um, and so as that's going on, if the folks at the top are not um actively working towards this in a governance fashion, how can it be used? What can be used, what can be shared and not shared, the employees are going to go in that direction anyway. And we know they already are. It's amazing that to see that. And instead of being negative about it, we can actually be very, very positive because all the employees are doing really is trying to increase their output. What they're trying to do is move things further along at a faster rate. Who wouldn't want that? And so, from the executive perspective, as we sit around the table, again, it's it's that understanding that this is not just an IT structure. IT cannot uh structure the operations of the organization, they cannot structure training that goes on for the operations um within the organization and so on and so forth. It goes on and on and on. The the technology is there, yes, but then how it gets used, what gets used, when it gets used, all of that needs to be defined well. So in the fractional space, um, first of all, why do I do that? Well, I I enjoy working with many organizations. As sitting as at the at the executive table in in the financial services, um we were accountable for the um the final product in many, many countries. And so you're defining then how is banking looking, what what direction are we going in, and how does that relate to our goals um for through you know risk, for example, um treasury, uh our operations, customer, customer experience, and so on and so forth, right? And so, as to, you know, regardless of what you do when you're at that table, you have to answer many questions and look at it holistically. As a chief AI officer, again, the importance and value of having that full perspective around it, then uh what I need to do is obviously keep myself up to date, not only on what the organization is doing, but what AI is even out there. Should I be concerned about you know this new model that just came out? Should I be concerned instead about this? What's happening here? And you know, frankly, Matt, we can only do that with so many organizations within one enterprise, because it's staying very, very much up to date on what applies to them, because otherwise they're just hearing a lot of noise that's out there. So that's where I you know really fell in love with it. And what I wanted to do was be at that table still, looking at it from all of those perspectives. Because now, like I said, in that fractional role, I sit at the table and listen to okay, what direction are we going in? What is it that we need to do that to remain competitive? And I can offer that insight that says, well, according to artificial intelligence that we're seeing, here's a lot more information than they ever had before. Or they may just say, okay, Ben, this is the direction that we want to go in, no question. But how does AI fit in? What can we do? And that's also where we need to make sure that we have the AI culture now fully embedded within the organization itself. Well, those are some items that I speak to. And for many, many organizations, it um answers the questions and concerns that they have, because otherwise, where do you get that kind of talent within the organization? Not an easy answer.

SPEAKER_00 8:50

Yeah, it's not an easy answer, and it's moving really fast. Even for you and I who are right at the bleeding edge of it every day, there's just so much moving. It's challenging for us and our teams to stay on top of it. We certainly, you know, are several steps ahead of our clients. So to be able to bring that knowledge as quickly and transparently to the clients, real time or near real time, is a challenge, right? It's a challenge for everybody out there.

SPEAKER_01 9:12

Well, then we have to stay on top of it, right? Like every day there's something new. Um, and and I know the same for you. We, you know, we have to um find what speaks quickly to us so that we're aware of it. But again, in that fractional role, it's it's putting the pieces together to the organizations that I'm supporting. How does it fit to you? How does it fit to this and what what's being done? Because there, like I said, there's there's so much noise that can be out there. And you'll hear about, okay, you know, now what about this new model that it just came out? What's gonna do? What's gonna do? And and that's because maybe they heard the news on the train on the way into the office. Um, but to be able to say, you know what, yes, absolutely, this can apply. Here's what we need to be considerate, or we need to consider and be careful with. Or, you know what, not even gonna apply to you. Don't worry about it. When there's something that does come up, you're gonna hear it first from me.

SPEAKER_00 10:08

No, that's so let's let's talk about because the news is out there, the media is out there, there's always different stories, right? And it's uh it's very, very challenging to to know what's right or are or what's a myth, what's reality, right? Out there. What are some of the what are like one or two of the biggest misconceptions that you see that that leaders often are are um struggling with because they maybe they've been they misheard something, as you said, on the way to work, or maybe through the grapevine of the corporate world, uh, et cetera. Like what are what are a couple of the misconceptions that you think are out there with AI right now?

SPEAKER_01 10:42

The first one that comes to my mind, Matt, is is is as we talked about the shadow AI piece uh as being a negative. And uh from a governance perspective, it can be, it very much can be. If they're using the wrong models, if information is being shared that shouldn't be shared or where, um absolutely, that needs to be well defined. So if I don't have governance within my organization, I I should be concerned about shadow AI. But as we talked about, the other side of it is why are the employees doing it? It's because they actually want a better end product, they want a better result. And that should speak for the organization itself. Like who wouldn't want that? That's exactly what we want. So I would say that's one misconception is that shadow AI is only a negative, and we need to be strong about how to you know shut it down. I would say, first of all, you will not be able to shut it down. That that's it, it's it's very much out there and will continue to be out there. It'll be a job unto itself to continue shutting everything down. You need governance that goes with it. Um, and so how do we build that governance to make sure that it's it's proper? The other piece I would say though, that misconception is is really, and this is kind of the um very beginnings of of uh of AI, as we move from you know, generative AI into agentic AI, and then how that functions, if I'm using a generative AI model to give me very specific, up-to-date information, just for example, checking the weather uh for today in this particular city, that's not generative AI. You do not want that to be generative AI. If it's using uh the the internet to grab that information, fine, great. But again, to understand what is generative AI and how does it produce what I'm looking for? So, what areas might I want that to fit within my organization versus what do I need exact specific information now? So, working with many accounting teams, generative AI is not really going to get you very far until you start to project forward. But if you're actually looking for today's data, generative AI isn't going to do that. Um, versus other models that you could use. So again, it's that that shift that uh you know, we're we're we're now Gen AI. It may sound good, but how is that actually impacting your organization? Because at the end of the day, if you're using generative AI that hasn't been trained properly, it hasn't capture the right information or the right data, um, and and that has not been wrangled correctly, um, then it will produce an end result that folks will consider to be hallucinating, right? It's not even uh proper. Look, it's garbage. So let's get rid of it. Well, it's not really garbage, it's it's doing exactly how it's been trained to do it. So was it garbage in? Because then you will get garbage out. And so I think that that's another misconception out there is what is AI going to do? And and then having to help organizations understand that it needs to fit into the operation. It is not the operation unto itself, it needs to fit in. It's a tool that goes with it that makes things uh get faster, more efficient within the organization.

SPEAKER_00 14:05

Yeah, very well said. It does need to fit in. And we we you and I share the the knowledge and understanding and truth that the AI transformation is really a people transformation within organizations, right? And it's it's it's a balancing act, which I know you have a lot of experience in. You're balancing um what are what are what do leaders want for the AI transformation? How are they going to measure that success? What's the maybe it's ROI, maybe it's something else. So I have a two-part question for you. What is it that you found that you think leaders ultimately want? And then once they know they can get that from an AI transformation, they they lean into it more. And then how do you measure that impact throughout the organization as you start to get engaged with the clients?

SPEAKER_01 14:47

Well, you know what, that's very interesting. That's a great question, Matt. And and and really, it's kind of how we start so many of our conversations with organizations. It's what's taking your time today? Uh, what's what's really exhausting you and is not necessarily related to what you're trying to be your output. Um, and so you know, very often we hear, well, I I really want to do more golfing or I need more vacation time. Uh, I'm I'm here, you know, 17 hours a day. And it's like, okay, well, that ROI may not actually be uh achievable. Um, but you know, being able to share with them, okay, this is where we can go with it. Um what I find with many organizations that yes, they want the efficiencies, uh, that they want to be able to um stay current, um, stay um competitive across across their their industry, um, while they know that so many others were already using AI, they're already going in that direction. Um, and we know that you know more than 75% of the businesses are already going in that direction. Whether or not they're using it correctly is a different story, but they're absolutely on the way. Um, and so the ROI that they're looking for is really that efficiencies. And then what we need to be very careful with, though, is that people side of it. And I would say the the twofold is is one, if our ROI is expected to do this, whatever that X is, don't peel off the people first. Your ROI will be a reality once it's actually implemented and seeing it working, right? And so if you peel off the people first, but you don't achieve what you're actually looking for or need to get, you actually put your organization in the campus. And so start small, start small and be able to see how it works. How is this helping one particular organization or one particular department within an organization? And that's the other side of the people to because really as we start small, we can define who is going to be using it. We can we can look at who can who are my champions within the organization, who can then be uh the the spokespersons that I need for my organization because yes, I'm gonna go in this direction, I absolutely need this, but who can who can really get that sound out there and and be willing to work with the various parties that are needed in order to make it work properly in that department? Start there and again start small so that you have people that are willing to try it and get it going and keep moving in that direction, and then after you see the results, okay, now what we see is how can I then apply this to the various departments that I have, and then you start to see it expand significantly. I can tell you, Matt, very, very few organizations that I see are at that expanded point yet. They're still at this small scale trying to make it work, and it's not necessarily working yet. And again, garbage in is garbage out that needs to be trained correctly. And this is what you and I do. We get right down into the weeds with the data and make sure that it's getting the right output. But that has to happen first, and then they see the ROI in that small space, and then okay, how can I apply it here? Once you have that, okay, more funds go into that annual budgeting so that we can actually put more into uh in into artificial intelligence as a tool within my operations. The piece about that though, and having that championship team and the those um the folks that are going to be sharing this information right across the organization, the the the key for them is that they they need to have that new culture because AI as a culture is not just using a new tool, it's thinking in a different way. Now that I have a tool that can make it do this and this, um, how can I, if whatever I need to do, how can I start to think now about using that as a piece in the puzzle that is gonna make the workflow work even better? So I mean you and I do this on a regular basis as we work with organizations, but it's it's okay. Let me look at your workflows, let's let's see how it is. But then it's not about okay, well, let's put AI here and the workflow basically stays the same. No, it's not gonna work. We basically need to throw out the box. We often say, you know, is think outside the box. No, no, throw it out, just gone. And that way you just need to think new, and that's a culture shift, isn't it, within the organization that everybody needs to be willing to think new. If I'm gonna do exactly the same way I've been doing it for 20, 30, 40 years, and that's not gonna change because I was the one who invented it way back when there's that we we we often struggle with that to be able to say, you know what, here's another way of looking at it and thinking about it. As that comes, you know, this so well, the conversation often goes into why are we even doing this? Why do we have this as part of our workflow? Where did this come from? Why did it get designed like that? Yep, absolutely. Every organization is the same, and so it's a matter of question do we need to keep it? What do we do with it? And those questions are so very, very valuable. And I would say that is really the new AI culture that needs to be ingrained into the operation so that now as you consider all of it, it's not just, oh, here's an AI tool, plug it in. No, it's thinking differently.

SPEAKER_00 20:19

Yeah, it's a very you you explained that very well, Ben. And I want to, I want to wanna double click into it a little bit more as well, because you know, you and I have a lot of shared experiences with uh with clients. And so if you if you take that, so if you're gonna if you're gonna look at what an existing process is and then potentially you know throw out the box and start over again. So you have a whole bunch of processes, like this particular department or business unit, they're responsible for delivering these outcomes, right? So again, uh uh two-part question. You know, do you think that uh the the managers or leaders of these business units are are becoming, as we shift the mindset, I help them shift the mindset, they're becoming more more outcome focused instead of more process focused. And then when the processes do change, is it who is authorizing those changes? Do you find that it's like the senior leadership, mid-management, the people doing the work? Does that vary by company? So that's sort of the two parts more outcome focused, and who is who is um who is approving the these uh changes?

SPEAKER_01 21:25

I would say definitely the the outcome needs to be monitored more carefully. Um, as we have now a new tool in our operation, and perhaps our operations and the workflows have been adjusted. So as we as we build the culture that now uh redesigns the process itself, what we need to make sure of is that the output is exactly what we're looking for. And we need that measurement right there. Um, we have to build with human in the loop, human on the loop, however you want to express it, um, so that they are now the ones that are no longer just. producing but they're overseeing it it's that oversight piece that absolutely needs to happen um built many many um uh uh agents uh for for organizations that perform a function and my my question always is as we go through this and define the workflow where is the human in the is it is it just at the end or is it middle is it a few places as we go through why because I need that check to be there to make sure that at the end it is what I'm looking for what I need right and so yeah there's there's pieces where now those employees who were doing all of this in the past now they're suddenly experts they're the ones who are looking at it to say is that correct and being actually willing to ask that question to challenge it to say this isn't correct or it doesn't look right and that's where the human needs to be right there right in there. At the end product too the AI itself needs to be trained so that when it knows it's been no let's say I produce whatever it is that I'm that I've been asked to produce if that needs to be changed in any way and I can tell you and give you a very specific example I built one that um crafts um replies to emails okay so you have to read it with the data of the organization et cetera et cetera it's a customer service operation basically through emails and it will craft the right email and then it sends to the human to read you know the staff expert that says is this correct here's here's the original email this is the reply you tell me is this exact it's gonna save you 90% of your time no problem. But if the output is not what you're looking for and it's not even addressing the issue it needs to be changed. Well then the AI now needs to know that it's been changed. So I I typically work within if if I need anything above a 25% change in that output then that needs to retrain the AI. So now that becomes my new base model for how it can reply to that type of question. So that AI needs to get better as time goes and the output is exactly what I was looking for. And maybe eventually you can get it so that it just sends it out and no one needs to look at it. Frankly we're not there yet and I don't know that we want to be there. But having that human in the lib is absolutely critical.

SPEAKER_00 24:15

Yeah that's fantastic again very well very well described because I know it's done a little bit differently in all different places uh Ben so I appreciate that explanation uh let's talk about as as we're beginning to wrap up a couple more questions for you you know what what's your one piece of advice for senior leaders out there especially CEOs you're you're leading the organization it's ultimately up to you to decide how much you're investing in your people in your technology etc what's your one piece of advice for the business leaders out there who feel like maybe they already missed the boat or maybe they're already way too far behind like what what what what would you say to them?

SPEAKER_01 24:53

Yeah you know what that's a very um a very good concern and and we see it a lot right across all organizations and anyone who's running it is where do I need to be where am I in comparison to my competition and it's it's very valid it's a very valid question. I would say you're never too late to get started but it's important to get started and to uh be well educated and and understand how this will impact not just your organization but your competition also and what are they doing as well um so that you can you can basically get on the bus. That that's absolutely critical because back when and I've only heard this I wasn't this was not my reality back when that you know folks didn't want to adopt the internet in their organization. No it'll go away it's just a fad it'll go away and then it was email I don't want to adopt email now it'll go away um well that's the same that we're seeing with AI where a lot of those the the thoughts around it well yes it's here now but it's not going to change what I do and it it's gonna you know go away. No, it's not and so okay how do I then get started? And as we look at this what I often see across so many organizations is they put it into the hands of IT. I've said this many times even even just now it just goes into the hands of IT to say you run it for me. And IT can't because it speaks to every single piece of the organization and how it functions. And so I would suggest then flatten the organization to an extent or have the the team that can interact right across as needed. In my role um in in the executive world with with financial services one of my greatest acts was to be able to build relationships with so many different departments that I'm not accountable for, but I know when they need me or I need them, there's a good relationship there. And so it's understanding all of that within the organization and building those relationships and making sure they gel and that they're they're they're solid absolutely critical because that's exactly what AI is doing. We are talking about all of our operations and how they speak to it, the risks that can exist right across what is the actual output? How does that impact what is the ROI that we're looking for that's where you know having that understanding that this is not just one department I can't assign it to IT I can't just assign it to HR. I have to look at it holistically and set up a whole new team that is going to branch right across all of that. That that's where I would say please get started absolutely that's what we do we're here to help always um but to make sure that those you have representation of those who are your champions and are willing to work for that common goal that the organization has. Yeah I love that so important it's it's everybody it's and and to summarize it in my own words you know the only thing you can really do wrong is not taking action like you want to lean into it you know collaborate across your leadership team this this affects every uh individual in the organization uh so put together your plan your strategy etc and uh but start moving start moving and and you know what I said Matt was that basically it's never too late to get there and I and I I need to correct myself because the reality is 2026 honestly now is the time to get started there's no question because by 2028 if you have not already implemented AI you will no longer be in business yeah sadly that will not be the time to come to the table and if you do at that stage it will be extremely expensive to try to catch up to your competition that doesn't work that way so yeah I think the time is coming if you start now fantastic I I I agree Ben Ben this has been a great conversation really enjoyed all the insights everything that you shared how can people reach out to you if they want to learn more about you your company all the great all the great things that you're doing out there to serve absolutely peoplefocuspro.com that's where we're at um please reach out happy to uh happy to assist in whatever way we can and uh of course also connect with us uh through Facebook same people focus pro um people focus enterprise ai as well and uh yeah we're we're we're out there willing to help wherever we can fantastic Ben thank you so much again for for being here and for all the insights that you share peoplefocuspro.com will make sure that people if they're driving in their cars they can hear it but when they come back and uh and look at it online we'll have that included in the show notes as well to make it easy uh for people to reach out I know you're on LinkedIn as well because we're all on LinkedIn getting it done.

SPEAKER_00 29:30

Um yeah thanks again Ben and and for those of you out there listening if you got value from this conversation like and subscribe to the podcast leave us a review share it around the world so we can uh expose more of this uh goodness and if you're ready to move from if you're ready to move your organization or anyone else who's leading an organization from AI curious to AI powered with really documenting the ROI along the way visit us at leadingaiagility.com and until next time remember people plus ai equals superhuman I'm Matt Zembrosky go make it happen thank you