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Jim Spignardo
Not all AI being equal. If you're talking about trying to bring something into the organization that's going to be transformational, it should have enterprise capabilities.
Chris Daigle
Where are most people coming to you today and where were they say three, six months ago? Is it the same?
Jim Spignardo
Most organizations are now coming to us with the story of we've purchased X amount of licenses or we've invested in this platform, but we're still not clear on the direction we should be taking. Whether what they're doing or how they're using it is secure.
Chris Daigle
How long until they start seeing growth relief or they start seeing pilots successful?
Jim Spignardo
I think, you know, it's not unrealistic to think that in within six months time frame, you know, they can recoup their investment and whatever tools are using.
Chris Daigle
So let's switch gears a little bit. What are you looking forward to the most or what are you most excited about with what's happening with the tools right now?
Jim Spignardo
There's just so much, you know, I've, I've really kind of leaned into a lot of these things. I'm a big fan of home automation. I really automated the heck out of my house. And so I'm really excited and a little nervous about seeing the convergence of robotics and AI.
Podcast Narrator
Jim Spignardo is a cloud strategy and AI enablement leader at ProArk, helping companies cut through AI hype and build secure, practical workflows that drive adoption, improve productivity and deliver real roi.
Chris Daigle
Welcome to Using AI at Work.
Podcast Narrator
I'm your host, Chris Daigle. Each week we'll be learning how today's business owners, entrepreneurs and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, chiefaiofficer.com has the answer.
Chris Daigle
We give you a simple path forward
Podcast Narrator
where we provide executive and team training so your people know exactly how to safely use generative AI in their day to day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI.
Chris Daigle
Everybody. Welcome to another episode of Using AI Work. My name is Chris Daigle and I'm the host of the show. And today our guest is Jim Spinardo. And Jim and I have been trying to do this for a month and a half at least with some missed connections. But finally we're on for today. And Jim is with ProArk and they are providing technical services for enterprise and lower middle market and above size companies. But his role in particular is cloud strategy and AI enablement for these clients. So today we're gonna be talking about in particular I wanna know like the patterns that he's seeing, the trends he's seeing so that you as a listener can kind of hear how others are generally doing things or where they are on the AI journey and, and figure out where you stand as far as your preparedness and your, you know, like, are you playing the game at the level you should be? So Jim, before we jump in, I always give the guests a chance to let the listener know what they should expect to walk away with today.
Jim Spignardo
Yeah. So hopefully this will be a nice back and forth conversation between yourself and myself, Chris. You know, I love just spending time getting the word out to customers, clients, folks who are just getting started on their AI journeys to have them get a better appreciation for what is this technology going to do to their industry specifically. But the workplace in general, there's a lot of fear, uncertainty and doubt right now. A lot of organizations are still struggling with, you know, what are we supposed to be doing? Are we behind? Are we ahead? Do we even, do we even have to spell AI? So part of that is just hopefully helping organizations understand that it's better to do it right than to do it fast, essentially 100%.
Chris Daigle
There's a lot of people out there that feel an urgency to do it fast. And I'll tell you one of the things that I've noticed a trend with talking to, because we do a lot of like presentations to YPO groups and vistage and professional organizations. And I'm hearing three common, I guess, points of contention when it comes to AI. They want to do it, but they don't understand the risk. So it like can't go all crazy if we don't understand the risk. They want to do it, but they're having a hard time figuring out where do we start. So use case identification, pilot project identification. And the third one is we'd love to get started, but we don't have anybody that can lead this for us. Like we need help. We don't have anybody.
Jim Spignardo
Right.
Chris Daigle
And I would imagine that proarch is addressing probably all three of those to some degree for their clients.
Jim Spignardo
Yeah, absolutely. And so, you know, we have kind of a playbook that can meet customers where they're at in that journey.
Chris Daigle
Okay.
Jim Spignardo
From the very beginning, states, we engage with either prospective customers or existing customers to deliver an executive briefing on AI just so that they can kind of get a sense of where, where the technology sits today. To your point, you know, what things do they need to be aware of from a risk perspective? What types of security tools exist to control this? But also too, what does a successful journey look like? What are the things that we've seen through our own attempts to do this right, as well as working with other customers that lends itself to a more successful outcomes. And yeah, to your point, we can meet customers anywhere they are on that journey, whether it's just beginning to talk to the C suite or the board to. We've been doing this a while, we get it, we're very technical. We just need some help implementing a data platform and connecting to our lot of business systems. Right. So we can, you know, reach anywhere in that journey.
Chris Daigle
Well, let me ask you then, on that spectrum that you just defined, where are most people coming to you today and where were they say, three, six months ago?
Jim Spignardo
Sure. Is it the same Most? Yeah, most organizations are now coming to us with the, you know, story of we've purchased X amount of licenses or we've invested in this platform. Some team or department within our group has convinced us to spend some money but we're still not clear on the direction we should be taking. Whether what they're doing or how they're using it is secure. I would say that's the vast majority of customers right now. They're kind of at that very beginning phase. They're experimenting, they're ideating. We do have a decent set of, you know, I would say maybe 15, 20% of our customers that already have a governance councils, they already have training programs, they're building agents and what they want now is some governance. They want us to come in and go, hey, tell us how to make sure we keep, keep this thing under control and don't lose control of it.
Chris Daigle
So that's something that Pro ARC does.
Jim Spignardo
Yeah, absolutely, yeah.
Chris Daigle
So these, and that's a, that's a pretty good, I guess, percentage of, I would say literate, AI literate or AI enabled clients that you've got working with you. So that's more than what I'm seeing normally, but we're catching people earlier in the journey for sure. I was speaking at an event Yesterday in Salt Lake City called Aqua Con. It was about those who acquire businesses, so private equity M and a family office. And we had a panel on AI and one of the speakers said something that I thought I just took for granted but I, I didn't really look through the eyes of your potential customer. And he said, just because you've gotten some licenses for some people doesn't mean that you're ready for AI. Right. So for those that are listening, I think they probably fall into that, that client avatar that you mentioned where they, they've got something so people are doing something with it. They don't really have optics on what's happening or really a strategy put together. So if a client comes to you like that, you'd suggest the first step for them, their first exposure to Pro ARCS abilities would be that executive briefing.
Jim Spignardo
Typically I would say yeah, because honestly it kind of does a level set it. We don't want to assume any knowledge or any understanding that may not already exist. It also gives them an opportunity to, to in a very, very non risky way that we typically do these for free to build trust with that individ, that company or that individual so that they can see, you know, what we're capable of doing for them. And during that conversation, you know, towards the tail end of that, we talk about, you know, this, the roadmap to adoption and helping them understand what they need to be able to put in place within that roadmap to ensure success. So that kind of makes them pull back and go okay, where are we in that? Where do we need to jump in and what's the next step for us? Right. And that's typically then when we'll engage for some sort of paid engagement with them.
Chris Daigle
Yeah. So what kind of information do you think that an executive needs to see? Because we do an executive briefings, plenty do them. Right. But in order to make them a valuable use of time or because here's what the listeners that are getting started don't want to do. Make the wrong choice.
Jim Spignardo
Right, Yep.
Chris Daigle
So what should they be looking for in that executive briefing? If they're, you know, already engaged or talking to somebody.
Jim Spignardo
Yeah. One of the things you talk about is not, not all AI being equal and if we're, if you're talking about trying to bring something into the organization that's kind of to be transformational, it should have enterprise capabilities. I think you and I talked a little bit before that we're a Microsoft partner so we are, you know, we lean heavily into Copilot because of the fact that it does live inside your data environment, it has and respects your security parameters, and it has the ability to understand the context of your organization, what people's roles are in the organization, the relationships they have with one another, the type of work they're performing. It just makes that transition a little bit easier and can allay them of some of the concerns and risks. But we do talk, I mean, we want to be very honest with them because we understand that there are tools out there that may be more well suited depending on the type of task you're trying to perform. That's not a Microsoft solution. Right. And if that's the case, what are the things you need to be aware of? What risks do you need to ferret out to understand when you go to do this? What guidelines do you need in place for those users? What types of tools can you put in place to make sure you have visibility into the data that's coming in and out of those systems so that you're not creating undue risk? Part of what we give them too, in that is just kind of explaining what general or generative AI is, how it functions, and a conversation around data governance, understanding that, hey, if you want to start out on this journey, make sure you have your data house in order or at least the part of which your part of your organization you're going to apply AI too. At least that part of it has some sort of governance and clarity around it because ultimately that's going to have a very significant impact on the output you receive and the quality of the performance of the AI tools you're trying to deploy. And then we also take a fairly decent amount of time to talk about agents. You know, the different types of agents, big topic assistants versus autonomous agents versus custom agents versus retrieval agents, those types of things so that they can kind of get understanding of. Okay, once we get past this partial productivity tool that we use all throughout the M365 apps, what is it that's possible? We want to expose them to the term Microsoft uses, the art of the possible. That part of the conversation usually is pretty interesting. And you just talked to me, talked a little bit before about, you know, where our clients at. We're finding that clients now are moving quicker through that early stages of general adoption to agent development. Right. I would say a year ago there was still this. Let's just put this in here and let people use it as they see fit and will figure out a strategy. They've heard enough. Now they've listened to their peers or their Competitors that they're now understanding the power of agentic AI and now trying to come up with those use cases and figure out which processes would benefit the most from AI and automation.
Chris Daigle
Well, that happened fast, man. It went from like, I need a GPT license to let's talk about agents.
Jim Spignardo
I know, it's amazing, you know, and,
Chris Daigle
and it's interesting because we're talking to, you know, business owners and stuff who are at that first stage of. Yeah, or maybe they're like, we don't know who's using what, but we want agents. Like, it's, it's. I find it interesting that they have very little context on what it, what it means to have it be part of your day to day, you know, workflow and that sort of thing. They're already talking about like how do we get autonomous agents to run the business? It's crazy.
Jim Spignardo
Yeah. And again, sometimes we have to bring them back down to reality. Right. We have to say, okay, you got to crawl before you fly. And part of that is, you know, we always want to emphasize defining the high value, low effort use cases initially. And that might not be the sexiest thing. It may be a no code agent co pilot chat that can bring some immediate relief to a specific role in the organization. But by doing that, you're going to establish a pattern of success. You're going to be able to share those stories of the rest of the organization and then you can start to dream a little bit bigger. Understanding that during that, during that, that piloted or proof of concept phase, you need to start to turn around and look at your data and go, well, where would we go next? And are we ready based on where our data, you know, how our data is today to go to that next level? If not, let's, let's, spend some time doing that cleanup. Let's document what systems exist, how they interact with each other, what dependencies they have, and let's do that cleanup so that when we get to that stage, we'll be ready to go.
Chris Daigle
Okay, this is good. How much of this is happening simultaneously? Okay, so hey Jim, we got our licenses, but we need help. So certainly get the users trained on safe use of the tools and how to actually just navigate tactically. Are you simultaneously in the process of that? Starting the evaluation of agentic possibilities for workflows and processes and also spinning up like a data analysis or like a data audit and clean team?
Jim Spignardo
Yeah. So part of our smart service, Smart Start services, that's kind of the brand we use, is we'll come in and give them some foundational understanding of the capabilities and features. A little bit of skilling on prompting use case workshops that we run through but at the same time we're typically doing a data risk review. So we're going through or inventorying their information, what's in the, in email, what's in teams, what's in their document repositories and making sure that they're not over provision over permissioned, that they're not sharing externally, that they're using good sound zero trust principles when it relates to identity security. And we do have programs that can help them go from that initial pilot proof of concept phase where we've identified those gaps within the data environment to help them actually start to put a plan in place to take action and, and get some consistency and some clarity around their data. Whether it's changing naming conventions for files or adding metadata, or just archiving and deleting old data. Yeah, you name it.
Chris Daigle
What I tell people is they want AI to come in, they want to turn the switch and like, oh, the problem's solved. Right. And I tell the, you know, interested parties that it's a process and not an event. For those who are listening, what does that timeline look like depending on, let's say it's a lower middle market size company, not an enterprise. I know that that's different timelines. What like if they're ready to get off the starter block, how long until they start seeing relief or they, they start seeing pilots successful?
Jim Spignardo
Yeah, I think, you know, it's not unrealistic to think that in within six months time frame, you know, they can recoup their investment. And whatever tools are using now, they do have to be intentional. They do have to track it, they have to make sure that the use cases that have established are actually being implemented. One thing that we learned pretty early on on our own journey was if we create use cases, we can't, we can't make them an option for folks can't say, well this is how you could do this particular job because we've given you prompts or whatever other tools like it, you know, so we had to go back and go, yeah, when we told you about those use cases that was a mandatory thing. It wasn't a, wasn't a nice to do.
Chris Daigle
Right.
Jim Spignardo
So we, and it's a little bit challenge for some folks who, who have been very traditional in the way they approached work. Yeah, make that flip. But, but you got to keep going back to the, well, you got to keep tracking the usage, you got to Reinforce it over, over time and usually by six months there's a culture of adoption where you've, you're starting to get traction. What I will say though is, you know, we've been doing this for over two years now, but it doesn't stop. It's not, it's not a. Well, we got to some this point and now we can just take our foot off chance, right? We went from 10 licensed users two years ago to now we have 150, which is about 30% of our business licensed. And we also went from, you know, which we, I track the return on investment and produce reports to our executive team, probably somewhere in the neighborhood of about 14, $15,000 a month in assisted value with you know, a couple dozen licenses to now where we have 150 users. This last reporting period, I believe what I was seeing was about $75,000 a month in assisted value, which is almost a million dollars a year. And again, that type of growth could not occur if we didn't track that investment and usage and prove to the C suite that this is worth just putting more people on, getting more licenses for.
Chris Daigle
And how do you go about tracking it? You look at the before state and the resources required to execute the widget to the after state over a period of time.
Jim Spignardo
So nicely enough, Microsoft has quite a few tools that you can use to look at the adoption usage as it relates to the various apps that are being used, the type of tasks that those that are being used in those apps. And then you can translate that to a blended hourly rate. That organization. Now we don't stop there though, right, because that's kind of a qualitative type of assessment. They're using it, but how effectively they're using it. We also within our use cases try to define key metrics. So if we're talking about our help center and being able to transcribe all their calls and meetings with customers and take better quality notes, that's something we want to look at and say, okay, are we reducing the time to actually solve customers problems? Are we finding that the quality of the information we're storing in our ticketing system is better and therefore we're leading to less issues? So we like to track those things too. And again, depending on the role, depending on the use cases, it's important that you do that. And every business is going to have different metrics you want to track because
Chris Daigle
I guess if you're looking at sales and you're like, oh, we saved the sales team X number of hours that's great. But how many more sales did they close because of that? Yeah, you need to be tracking. Yeah, that holistic again.
Jim Spignardo
If you're not tracking it now, stop, pause. Figure out where your baseline is, then pick up your use case and then have something to compare against. It doesn't have to be perfect. It doesn't have to be. You don't have to be down to the nickel or dime. But you want to have a general sense and the. Funny you should mention that because we have done that when it comes to, for instance, responding to RFPs or requests for proposals. We had a certain success rate. We had a certain amount of time it used to take us to respond. And you know, we've. We've created an agent to help us with all that and dramatically reduced our effort. We went. We probably won about 50% of our piece in the past. We're now close to like 80%. And the time it used to take was probably more than 10 days with about three people's labor. Now it's down to about one and a half people in about four days. Right.
Chris Daigle
Yeah. Nice. So those are the types of things that, that any listener should expect. Like that's real. We're seeing something very similar there. Now, you mentioned that you guys started initially with those 10 licenses. Where were those licenses? Was it like you and some enthusiasts to tinker with?
Jim Spignardo
It was probably more of the people who were early adopters. It was definitely some of our consultants or strategic consultants, some of the. Some of the exec team. But when we expanded the first, the first team within our organization, we targeted our, our support engineer team, our help center because a. They had, they have a certain level of technical aptitude. So we know they would take it pretty well. But we also had some really easy, simple, fast use cases to get out the door that could really show some impact pretty quickly for those that aren't
Chris Daigle
necessarily in the technical field or whatever. Where I like the idea of getting it in the hands of the executives for sure. Because if they don't understand what's possible, they're not going to be all in. And yeah, like they need to be getting all in.
Jim Spignardo
Yeah. It's a little bit different for, for some areas we're a technical organization.
Chris Daigle
Yeah.
Jim Spignardo
So the people who are at the top of our org are inherently technical people. For some organizations, that might not be the case and actually might not be the. The route I would recommend because those might be the people who lose pretty quickly.
Chris Daigle
Yeah.
Jim Spignardo
And yeah, I don't want this. This is. I don't even know how to use this. Right. Interesting. So it's just got, you got to gauge that when you're looking at the organization.
Chris Daigle
So how would an organization identify who that champion is going to be or if, or if they should. Because there's. My experience has been at the executive level there's going to be at least one.
Jim Spignardo
Yeah.
Chris Daigle
Hey everybody, we got to do something. Right. But if that one person and let's say they want to be the, the executive sponsor for this effort, the company, they still got a job to do though, so they can't do it full time. How would that individual know where they should start the, the introduction of the conversation without blowing it too soon? By giving it to the, the luddite, the non technical executive who's like I don't understand this.
Jim Spignardo
Yeah. Part of, part of our engagement is we really encourage a cross section of the organization. You know, various stakeholders and business leaders and usually we, we ask them, you know, bring the willing to the room and then see which ideas flow to the top. Right. Which are the best ideas. You know, we go through this workshop of use case scenarios and we, we give send them back with some homework and a workbook to fill out and ultimately we actually even have a rating scale they can use. Find the use cases that seem to resonate and find the people who are going to be the ones who are willing to own it and see it through to the end. And again, don't play special, don't play preferences. Right. If, if this team over here just loves to use it but they really don't have good use cases. Well maybe they're going to need to wait a little while to get, get a little more attention. Yeah. This group, you know, actually has proven that they have something they can, you know, find some really early value out of.
Chris Daigle
So how is your organization distinguishing themselves in the marketplace? Because I'll tell you when I talk to I meet somebody else that's in AI oh, what do you do?
Jim Spignardo
Yeah.
Chris Daigle
If you heard what, what I, how I describe what we do and they heard what you describe what you do and the guys that I spoke from stage yesterday, it's, it all, all seems like we're doing at a macro level. We've kind of figured out a process. It's those, it's the secret sauce kind of stuff. So how are you guys? Like how do you, how do you, what do you think you're doing different than others?
Jim Spignardo
Sure. Yeah. I think big differentiator for us is the fact that we have so much capability across so Many different technology domains.
Chris Daigle
Yeah. Okay.
Jim Spignardo
You know, we've been doing digital engineering and software design for almost our entire existence, which is coming up on 20 years. We have a in house security operations team and security managed service. We have a cloud and infrastructure group that can help you deploy whatever AI solutions you're looking for. In governance, we have a compliance group. So we have a very broad capabilities within our organization. We also have a very deep relationship with Microsoft. So if you're in that universe, and we typically stay in that lane, I mean our digital engineering team does take on projects that go outside of that sometimes. But trying to build up our capabilities and our expertise in the eyes of Microsoft helps because we work with their sellers who then can go out and pitch us to customers. That means a lot of training, internal training, a lot of specializations that we have to achieve and investments we have to make in ourselves. We also are very keen on telling our own customer zero journey so that it's very relatable to our customers. The last thing I would say is we're trying to be very forward thinking in the managed services we provide today, both on support and security level. Unlike a lot of our competitors, we're starting to bake AI monitoring, consulting right into those products so that when customers come to us and say, well, great, you support our infrastructure, what do you know about AI? Well, we also can do that and we can also be there to support you on that journey. So yeah, I mean it's, it's a little bit of everything. It's, it's not easy. But I would say, thankfully right now there is a lot of interest and a lot of work. So we're not necessarily having to, you know, fight people off or, or really kind of get into very competitive situations.
Chris Daigle
Yeah, that's what, as I say, it's not like we're selling insurance. Right. Like people, there's high demand, there's, there's, they're aware of the problem and they're the, they're becoming aware of the solution, but they look around and there's just not a lot of options out there. So good time to be in the AI space for sure. What were some of the challenges initially? Again, you guys aren't necessarily the standard company. You're tech forward. Right. You know, what were some of the challenges initially? Or did you have any with the pilot teams when it came to. Because what I'm looking for here is was there like a change management effort that was required? Was there a cultural resistance to, you know, whatever?
Jim Spignardo
Yeah, no, absolutely. There had Needed to be a change management process. But what I will say, and I think I kind of referenced it already, not everybody wanted to adopt it the same way. Even though we developed use cases and we said, okay, we're going to bring on one team at a time, develop them, develop three high value, low effort use cases, we found people were backsliding and saying, well, I use it when I can, but I'm not using it for that thing. So we had to be very intentional and we had to really bake these tools and these cases into the workflows. We couldn't make it an option. We had to say, okay, this is how this job will be performed now.
Chris Daigle
Yeah, I like that.
Jim Spignardo
Yeah. And the other part is I think we probably didn't give enough attention to how much ongoing training and exposure people were going to need. So, you know, probably, I would say six to eight months into that journey, we decided this is where I kind of came in and actually took that role. We needed someone in a role that was going to be responsible to track the adoption, to make sure that we were providing additional support and training that could be setting up a champion team, establishing our AI governance council. I'll just give you some idea of some of the things we do on a regular basis. We do a once a week copilot tip of the week, which is a new feature capability that goes out to the team. We do a, an AI news briefing which covers news topics in the industry, but relative to how it affects our organization. So it's very, very tailored and contextual. And then we also do once a month a user group where it's a hands on workshop and employees come in.
Chris Daigle
Like a hackathon?
Jim Spignardo
Yeah, sort of. Yep. So this, this, this next week we're actually doing a, a copilot treasure hunt essentially. So we're gonna give them a list of, you know, 10 different things they can do with these tools.
Chris Daigle
Yeah.
Jim Spignardo
And you know, whoever gets to it first is gonna win a prize.
Chris Daigle
But yeah, very cool.
Jim Spignardo
And so, you know, we just gotta keep doing that. And we, we also introduced a AI fundamentals training that all new onboards have to go through now, which is about, you know, three hours of just general AI gen of gen AI concepts, responsible AI topics and then very specific user training on copilot. And then we assess them and rinse and repeat.
Chris Daigle
So are you guys doing a lot of hiring?
Jim Spignardo
Yeah, I mean we hire people regularly.
Chris Daigle
Yeah. So at the different roles, how are people, how prepared are people coming in? Like how much AI skills are they bringing with Them.
Jim Spignardo
Yeah, it's mixed bag. It really is. And I would say you can't make assumptions based on generational either. It's really interesting, especially again because we hire, you know, or at least I'm involved with hiring a lot of technical people. Some are very knowledgeable and like, oh yeah, I've been using this stuff and I'm helping me to do this and, and others go, yeah, I'm aware of it, I'm familiar with it. And it's, it's becoming, and we've mentioned that too to our talent acquisition team. It's become a core competency or core skill that has to be on the resume now. Yeah, right. It's, it's no longer. I mean, can we overlook it? I guess it depends on the role, but you better be willing to be an exception. Learning it pretty quickly when you get here.
Chris Daigle
Yeah. Yet the data that we're seeing is that companies are much more interested in hiring you if you have like AI experience that may not even be relative to the role that you're. But if you know, they understand, if you know how to use the models, you'll figure out the role or however to apply it, you know, are you seeing this experience? So we, we partnered with a group called Scaling Up. They're professional coaches and consultants. They help companies with hyper growth. And their, their kind of like head of thought is guy named Vern Harnish. And Vern was recently talking to. It was a software development firm in the UK and the experiment that they did was they gave all of their developers cursor licenses. Right. Okay. So. And for those of you that don't know cursor, it's a, it's supports encoding by using natural language, it does all the code writing. Right. So at the end of, I don't know what the measurement was. It was maybe 12 weeks, they had 50 developers and what they found was that the top five were producing as much code as the other 45.
Podcast Narrator
Wow.
Chris Daigle
And what they did was they got rid of those 45, but they paid the hell out of those other five.
Podcast Narrator
Right.
Chris Daigle
They paid them like 5.5x what they would make so that they could keep that talent. Right. Are you see and I hear this term and Twitter and all this stuff about the 100x developer because they're using. Are you seeing that type of impact yet in your organization with those who are coming in with saying I've been using it for two years versus those that say I'm not using it, but I've been a developer for 15, 20 years.
Jim Spignardo
Yeah. I don't have nearly as much visibility into that side of the business. But what I will say is we absolutely have been able to hold the line on additional headcount based on the efficiency gains that we've seen. Right? Yeah. So it's not necessarily, hey, we're going to, you know, excise a unit or a group. It's more of. We're able to accomplish a lot more and actually slow the pace of hiring.
Chris Daigle
So, yeah, that's a couple of places I've seen recently. The trend looks like it's keep hiring flat and let natural attrition kind of, you know, trim out the people that don't belong. But AI is allowing them to grow the businesses as long as the people are have gone through a process like what you're talking about, where there's ongoing training and there's helping identifying use cases and there's measurement of enablement and adoption and all those types of things. So you're saying that for you guys, most of this tracking is being done in Copilot or the Microsoft platforms?
Jim Spignardo
Yep, yep.
Chris Daigle
Okay. So for anybody. And, you know, I don't know what the percentage is, but I would imagine most of the clients that you're looking for and that we're looking for by default, they're on Microsoft. They're a little bit older, they're a little bit typically.
Jim Spignardo
Yeah, typically. We've, we've definitely seen other situations, though, where, you know, we've been brought in to say, okay, give us a presentation on what's the difference between ChatGPT Enterprise and King Copilot, you know, and try to be as, as objective about it as possible. And, you know, we've been able to cut. And I wouldn't say, I don't like to use the word displace because I use ChatGPT myself as well. Right. But we've been able to illuminate for that customer that, you know, if you're looking to try and control the risk and be able to make sure that you can have more governance and also keep your data inside your organization. You, you know, the Microsoft platform is hard to beat. I mean, especially when you look at how the security tools integrate. A lot of organizations are going like, well, I don't like Microsoft's LLM. I'm like, well, they don't have an LLM. They use OpenAI.
Chris Daigle
OpenAI. Yeah.
Jim Spignardo
ChatGPT 5.4 dropped today. I refreshed my Copilot chat window and sure enough, there's, oh, there's chat GPT5 4, same exact day. That's how, that's how tight their ability to launch these models is. But also too, you can use other models. Microsoft's now opening it up for Claude. And if you get to the point where you're using something like Azure, OpenAI foundry, you can swap in any models you want. So really, at the end of the day, you're really having a conversation about the interface more than the back end technologies. And, you know, and, and there's definitely some legitimate complaints about some of it. But I will tell you if, if you don't like something, wait 10 minutes. And typically it's being addressed, you know, that the product as it's, as it stood two years ago and what we're, what you're using today, it's unrecognizable. It's absolutely recognizable from what it was.
Chris Daigle
Even, man, if you think about it like before Thanksgiving, it was still Gemini 2.5. It was, you know, Chad GPT5. It was claw, like, and just since then, and now people are asking about, I was at that event yesterday and people who don't even have, you know, a plan were asking about Open Claw. It's like, man, y' all need to just relax a little bit, right?
Jim Spignardo
Yeah.
Chris Daigle
Yeah, let's get a GPT license first, huh?
Jim Spignardo
Yeah.
Chris Daigle
So when you have clients that say, I understand there's risk associated with being maybe more on the cutting edge of testing out things like especially autonomous agents and that sort of thing, because it's, I mean, I've been in the space, you're in the space. Like, we know things move fast, but I am blown away by how quickly people have shifted from like, understanding how to use the, the large language models and in their day to day to immediately like, agents, agents, agents, agents. Like, that's like, I'm hearing that all over the place. And this morning, with all the chief AI officers in our community, we had a conversation and that was, how do we address the, the, the. The shiny object chasing with an appropriate security posture for these agents, particularly something like open claw. Claude, Bot. Molt. Bot. Whatever you want to call it. So how are you guys not saying, you know, pouring cold water on them, but still managing the cause if you don't test it? Man, I think there's a big gap there. Big miss for a company if they don't leverage agents, but there's that big safety. And yeah, you know, so, so we,
Jim Spignardo
we, you know, we want our users to experiment. We. But we want to do, we want to do that safely and in a Controlled manner. So, you know, we again leverage the Microsoft security tool stack pretty heavily. So we have the ability, using Microsoft Defender for cloud apps to have visibility into what people are using as it relates to cloud based applications. And Microsoft actually can rank those sites and those services based on the various set of metrics, privacy controls, SOC compliance, and give it a rating score. And so what our CISO has done is if a particular AI application does not achieve an 8 out of 10 or better, we automatically block it. Right. If you want to make a case to the CISO about why you think you need access. But even with that, even when we're allowing anything that's an 8 or a higher, we're still keeping tabs on what it's being used for and making sure that it has a business purpose. Right. So if we see something that's, you know, unrelated to our business, we might block it even if it is an 8, or give someone a chance to explain why they feel they need to have access to it. We're also making sure we understand what's going into those systems. So looking at the prompts, looking at the documents, being able to see what's being shared, how are you seeing that
Chris Daigle
on the back end? On Microsoft you're able to do like prop samples.
Jim Spignardo
It's an extension to the browser. And because it's an extension of the browser, that's all being captured when you go to those sites, you can see what's being uploaded, what types of prompts are being put into those systems. And then finally Microsoft came out with Agent365 during night. And that is an incredible control plane which can really give you visibility into all the agents that exist in your environment, who created them, how many people are using them, what they're attached to, what data is going into them. And there's a kill switch. If you think there's a agent that's not is going outside the bounds of your government, your usage policy, just kill it. You can then layer on top of that too is the data loss prevention stack and make sure that, you know, sensitive data is restricted from being put into these tools as well. So how does that work?
Chris Daigle
So if, if somebody wants to, you know, maybe there's no malice, but they're copying and pasting IP or something and they want to use that in a web based access to copilot or whatever. How does that work? How does the model say, wait a
Jim Spignardo
minute, if we have automatic labeling turned on, right, that that document will be detected, okay, having a certain sensitive information type in it, label gets placed on it. That label then comes along with an information protection policy which determines where and how it can be used. So we have one label that we use, it's a restricted label. That restricted label literally means you can only share it with internal individuals that you've given explicit access to, no matter what. Right. If I move that document to another document library where the permissions are different doesn't matter. You cannot access that. If we tell Copilot you can't use restricted data, if I try and prompt and ask to use, it's going to say don't have access to that. Sorry. So even though you may have permissions to it, it's not allowed to access or. And again, in the case of using a third party application, if I go to attempt to upload it, it's going to be restricted or that system won't even be able to read it because it'll be encrypted.
Chris Daigle
It makes a lot of sense and I declare ignorance when it comes to copilot. Just a lot of our clients, even if they're in the Microsoft environment, we still work with the other models with them. But I'm not seeing that level of like control on what's being uploaded into the tools in the other models. And right now I'm trying to think how would you even do that? But if that's baked in with Microsoft, that's very comforting for sure.
Jim Spignardo
Yeah, yeah, that's really, I think where the advantage lies.
Chris Daigle
I think you're right.
Jim Spignardo
It's just the security stack and the control tools that. And again, like I said, that extends to third party solutions too. It's not just controlling Microsoft stuff. It's able to actually take advantage of the security tools stack to, to put some controls around using these other third party services.
Chris Daigle
So let's switch gears a little bit. What are you looking forward to the most or what are you most excited about with what's happening with the tools right now?
Jim Spignardo
That's a great question. There's just so much I've really kind of leaned into a lot of these things. I'm a big fan of home automation. I've really automated the heck out of my house and so I'm really excited and a little nervous about seeing the convergence of robotics and AI and what will be possible there. I like to think of myself as a little bit of a futurist. As growing up as a kid, I really wanted to believe that someday I would have a robot that did all the things that I didn't want to do around the House. You know, I'm now in my 50s. I'm hoping that that reality comes to, comes to fruition before I, you know, take my last breath. And it's interesting because, you know, you cannot untangle these, these, these tech, these, these industries, right? They're, they're, they're really are, are advancing together and it's exciting to see that and it'll be exciting to see what that potentially could bring.
Chris Daigle
You know, we do a lot of work in the construction, commercial construction space with those clients. And yeah, my chief AI officer, he's a bit of a futurist as well. And that was, it was like the constraint for them is people, skilled labor. Let's go talk to Elon. Get 5000 Optimus robots and transform. Certainly like an industry. So I, I totally agree with you. And we priced a few robots. We. There's some Chinese models that you could get for 3,000, 5,000 out. What do they do? I don't know. But it's getting very accessible. Like that's what an electric bike, bicycle costs, right?
Jim Spignardo
Like, yeah, right.
Chris Daigle
An E bike or a robot. That's going to be a tough choice, I guess, right?
Jim Spignardo
Yeah. Can you give me a picture? Can it give me a piggyback ride?
Chris Daigle
Yeah, probably. Hey, so for, for those who have resonated with kind of the approach that you've shared and how you guys are looking at things and they want to find out more. They're in the Microsoft ecosystem there. What's the best way for them to find out more about working with Pro arc?
Jim Spignardo
Sure. Yeah. The best way is just to go to our website, ww.proark.com it's arc with a like arch, not arc. We have lots of resources on there, free resources, white papers, we have webinars, we've listed. We actually have an AI return or a copilot return on investment calculator. You can kind of plug in and say, well, if I get this many assisted hours with copilot, where's my break? Even if I pay my user, my workers this much, how much do they have to use it before it actually pays for itself? We do, we have a lot of different blog posts on there and we've just recently also with our security team, started some office hours where it's been very, very well received with our customers. And they come in and they just ask questions and to ours, to our SMEs. Yeah, but yeah, and if, if anyone's interested in following me, Jim Spignardo on, on LinkedIn. I'm the only Jim Spignardo on there and I write about three articles a week, AI and other business IT related topics. And I do also have, at least I hope I do, a ebook that I'm going to be releasing for free in March called the AI Turning Point, which is going to discuss kind of less of the technical aspects of how companies deal with the changes that AI are bringing to the workforce, but more of the business process and things are going to have to change within businesses in order to support this, this transformation.
Chris Daigle
I'd love to get a copy of that. And for all those links for the listeners that's going to be in the show notes and it just, you know, for, for as, as a listener, I want to share with you the way that Jim has approached. This is very prudent. Like there was nothing here that I heard where I was like, well, I disagree. This is all really solid stuff. So I would suggest that if what you heard that fits with what you're looking for, especially with the the depth of technical skill, that they have to be able to do more than just the AI side of things or think about AI at a lot of different levels, not just the human level, but also the technical capability level. Definitely plug in with, with what Jim's up to. Jim, thank you so much for taking time out on a Friday to have this conversation with us and share kind of the way that proarch is approaching this and that you got a fantastic role there. That's a lot of being that person and that company has got to be a lot of fun. So thanks again.
Jim Spignardo
My pleasure.
Chris Daigle
And for everybody, we'll be releasing another episode as we always do on Mondays, and be prepared. We've got the the hundredth episode is coming up in April, so we'll be doing something very special for that. And thank you so much for listening and if this helped you or if you thought that this kind of demystified some of the AI conversation for you, please feel free to share this with those on your team or anybody that you know think could benefit from this. So we'll see you on the next episode. Thanks everybody.
Podcast Narrator
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Episode 96: Using AI Adoption Strategies That Actually Deliver ROI for Your Business
Host: Chris Daigle
Guest: Jim Spignardo, Cloud Strategy and AI Enablement Leader at ProArk
Date: March 23, 2026
This episode dives into real-world strategies for driving effective AI adoption in businesses, focusing on approaches that yield tangible ROI without creating unnecessary risk. Chris and guest Jim Spignardo provide business leaders and executives with practical wisdom on AI tools, organizational change, executive education, and governance. Through stories from the field, best practice playbooks, and lessons learned, they offer a non-technical, actionable roadmap for putting AI to work safely and productively.
On organizational AI maturity:
"They're experimenting, they're ideating... but still not clear on the direction we should be taking." – Jim Spignardo (06:22)
On the shift in AI adoption:
"It went from like, I need a GPT license to let's talk about agents." – Chris Daigle (13:42)
On demonstrating ROI:
"This last reporting period... about $75,000 a month in assisted value, which is almost a million dollars a year." – Jim Spignardo (19:54)
On change management:
"We had to really bake these tools and these cases into the workflows. We couldn't make it an option." – Jim Spignardo (30:36)
On the Microsoft ecosystem advantage:
"If you're looking to try and control the risk and be able to make sure that you can have more governance and keep your data inside your organization... the Microsoft platform is hard to beat." – Jim Spignardo (37:18)
On the speed of AI advancements:
"If you don't like something, wait 10 minutes... the product as it stood two years ago and what you're using today is unrecognizable." – Jim Spignardo (38:09)
On responsible AI experimentation:
"We want our users to experiment. But we want to do that safely and in a controlled manner." – Jim Spignardo (40:13)
Looking to the future:
"I really wanted to believe that someday I would have a robot that did all the things that I didn't want to do around the house... I'm hoping that that reality comes to fruition." – Jim Spignardo (45:05)
This episode is a rich roadmap for responsible, practical, and ROI-driven AI adoption for business leaders—grounded in real transformation stories and actionable guidance, not hype.