Jim Spignardo Podcast Transcript
Jim Spignardo joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to the Coruzant Technologies, Home of the Digital Executive Podcast.
Welcome to The Digital Executive. Today’s guest is Jim Spignardo. Jim Spignardo is the director of cloud strategy and AI enablement at ProArch. A global IT services and consulting firm with over 25 years in it. Jim’s journey spans network engineering, cloud management, cybersecurity, and strategic consulting.
What drives him is helping organizations cut through the noise and deliver real measurable business outcomes. At ProArch, Jim leads initiatives that modernize infrastructure, empower teams, and maximize ROI On Microsoft Technologies. He’s worked with diverse range of clients from nonprofits to global enterprises, guiding them through complex cloud transformations.
Well, good afternoon, Jim. Welcome to the show.
Jim Spignardo: Thank you so much, Brian. Nice to be here.
Brian Thomas: Absolutely, my friend. I appreciate it and I know generally you’re out of the New York area taking some time in in, in Georgia today, so I appreciate you making the time. I’m in Kansas City and Jim, let’s just jump right into your first question, if you don’t mind.
Yeah, absolutely. With over 25 years in IT and work spanning network engineering, cloud security, and consulting. How did you ensure that a cloud modernization strategy doesn’t become just a technology upgrade, but one that is clearly aligned to business goals and deliverable and delivers measurable ROI?
What are the common pitfalls you’ve seen in this misalignment? Yeah, that’s a great
Jim Spignardo: question. One thing that we we’re consulting organization by nature. So we always start with business outcomes. We wanna really translate the goals of, of that organization into things that are measurable and can prove value.
And then typically the architecture follows after that. So, you know, we begin with making sure that we understand those outcomes and any constraints. So think about it from this perspective of, you know, why are you doing this? What’s the justification? And sometimes it’s organizations want to decrease their data center footprint.
They’re coming up on a renewal with their VMware and all the things have gone along a lot with that recently and, and having to pay extra money or that they have maybe have an application that’s outdated that would benefit from some, some modernization in the ability to be more dynamic in scale. You know, when we, once we look at that, we really want to understand.
How we design for that value and at the same time, make sure that there’s a, a resiliency built into those solutions. So we follow Microsoft’s cloud adoption framework, the well architected framework as well. And you know, we wanna make sure that. You know, just because you’re going to the cloud, a lot of organizations assume that, and there’s all this inherent built in resiliency.
We make sure that you understand that, you know, you could, if you put all your resources in a single region and in a single availability group, you know, you’re, you’re not that better off than you were, you know, with a very small data center. So all of those things have to be considered from the, the, the get go.
And then ultimately, it’s really about making sure that you have good governance and cost management in place. So that you’re actually to be able to track the ROI and the investment that you’re making, you know, and these are all things that Microsoft does a really great job with. You know, that’s really where we.
Do most of our business. So the AWS definitely has these tools as well, and you’re able to kind of, you know, see what you’re spending and, and what the, what the the value that you’re, you’re getting returned as far as some of the common fit pitfalls. A lot of times you see organizations that are in, just in a rush.
They want to get to the cloud as quickly as possible. They want to modernize and they just wanna lift and shift everything as it was. And really, there’s a great opportunity here to improve on many of the things that you’re already doing. So you’re moving that technical debt to whether it’s AWS or Azure.
You want to put in place what are called landing zones, and you can think of landing zones just as simply as blueprints of how the infrastructure should be laid out, and ensuring you have things like policies in place that can be placed at the very top level, the subscription level that float down to all the resources as they’re being.
Provisioned. That can also include tagging your assets and making sure you have a good identity strategy around how you control access to who can do what with those resources. And then also you wanna make sure you have a good roadmap. Making sure that you understand where you want to be in two, five years down the road.
Again, making sure that you have that framework in place to provide you a good foundation for how you scale and build out in the future. And then lastly, you know, you just don’t, well, not lastly, but secondarily to the last, again, is around resilience. Making sure you understand your recovery point, objectives, recovery time, objective objectives, how quickly you can get things back up and running.
In the case there is an outage and, you know, never, never, never overlook security and compliance. These platforms have some really incredible ways to build that in from day one. I mean, you, it’s, you save yourself so much time versus having to go back and retrofit later on. So.
Brian Thomas: Thank you, Jim. I appreciate that.
Yeah, absolutely. I really like how you started with just kind of outlining, you know, starting out with the business outcomes. You know, you need things that are measurable and you’re looking at things that can provide value, true value. And I know for your, your customers, you design for value and you build in that resiliency, as you mentioned.
Mm-hmm. But I’ll just highlight a couple other things. Good governance, track the ri and, and have a good roadmap. So I, I really appreciate that. And Jim. The next question I have for you, you developed an AI adoption playbook at Pro Arc, especially around Microsoft 365 copilot. Yeah. What are the key elements or steps in that playbook that enable organizations to turn AI hype into practical working workflows?
Maybe you could walk us through an example use case where this playbook delivered measurable business value. Sure. Absolutely.
Jim Spignardo: You know, like anything else, the use of generative ai or in our case, you know, more specifically co-pilot, we treat it like any other enterprise initiative. So you have to make sure that you start with a secure foundation and you look at and try and target some very high value use cases that can establish success early on.
It’s also very important to make sure that you identify the folks within your organization who are very excited about this technology. We call those our champions, and then we have to measure relent relentlessly to tove verify that you’re actually getting what you expect. We call this approach our smart start approach, and it really starts with looking at your data state.
So we’re talking about copilot specifically. You know, we run a, a Microsoft 365 data risk review. Go through the entire data, graph, data and, and also do a gap analysis. We’re looking at things like identity. We’re looking at how the M 365 environment is configured. We’re looking at how data labeling and sensitivity labeling and protection is done, something that most organizations aren’t doing enough of, and the, the purpose of that is.
We wanna make sure copilot only sees what it should or what you want it to see. As I mentioned before we define those first wins, we may pick two or three personas or roles in the organization. This may be sales or project management or finance. We build out a roadmap and we assist them by kind of aligning to Microsoft’s adoption guidance.
I dunno if you’re familiar with that, but the, the guidance is get ready, you on onboard, engage, and then you deliver the impact. One thing you can’t o overlook though, is standing up the human system. We think of AI as kind of taking away all these responsibilities, but there still are humans in the loop here.
And so we need a good AI usage policy that can establish the ground rules for those users. But we also very strongly believe in standing up. Knowledge hubs and I call those knowledge hubs, centers of excellence, where your users can interact with your champions to get very specific role-based training to their, their, their position and their work, as well as prompt toolkits that they can use to, to really give them some, an early confidence.
’cause there’s still a lot of skeptics out there. And they’ll lean on AI and then it’ll kinda. Tail, tail off, and then they’ll kind of come back to it when they’re, when they’re, uh, asked to. But it’s important that they constantly are being, this stuff is being reinforced and it’s very important that we measure and iterate.
So as the person who leads adoption and not my organization, we use things like my M 365 admin reports and co-pilot dashboards. To look at our adoption score, make sure that we can actually demonstrate the cost and value to the organization as far as assisted value. We can actually translate into dollars and cents, which you know, is very powerful as it relates to a specific use case that we’ve found a lot of traction in.
We built a lot of copilot agents, but one specific agent that has really resonated very well is we built one called a Microsoft Funding Finder agent. And that agent is used by our sales teams to help them unlock or find potential funding that we can apply to our customers to help them in their modernization journeys.
Uh, you pro, you know, if anyone has dealt with Microsoft over the years and we’re a very deep partner of theirs. Uh, you’ll know that it’s hard to wade through all the information. So we kind of brought all these resources together in one location where our account teams can ask a question, give the context of what type of project we’re working on with those customers, and see if there’s something that matches that customer to be able to apply those funds to that, that engagement and that has really dramatically reduced the amount of paperwork.
It’s helped us win more deals. On and on beyond the agents, we are able to, again, as I said before, demonstrate hundreds of hours a month of copilot assisted work across our users which typically can translate into tens. Well, right now I think we’re tracking around $15,000 of assisted value every month across the a hundred users or so that we have licensed.
So, you know, that’s, that’s kind of where, where we really, that’s our
Brian Thomas: approach to, to AI overall. Thank you. I appreciate you. Unpacking all that. I know starting out with a project like this, it’s, you start with that secure foundation. You establish success early on where you can see those early wins. You’re constantly measuring iterating of course, and then you build out that roadmap that you can actually follow along the way.
And then of course building out knowledge hubs, as you mentioned, to ensure rollout success. I liked your example of that agent. I think it’s Microsoft Money Finder, I believe you said. So,
Jim Spignardo: yeah. I mean ultimately, yes, it’s called Funding Finder, but we should have called Finder. I shoulda have called it Money Finder.
Brian Thomas: No, that’s great. I appreciate that. So that’s, that’s just awesome. So Jim, the next question, you stress that technology isn’t just about systems, it’s about people. Yeah. How do you help organize, how do you help organizations, CIOs, IT leaders build buy-in. Change culture and prepare teams for AI and cloud transformation, especially for those resistant to change or maybe you wary of automation.
Jim Spignardo: Yeah, it’s not easy. You know, there’s a lot of, a lot of organizations understand that they’re being expected to do something. They’re, they’re seeing a lot of their peers and other organizations, but they’re just not unsure. So really you want to start with safety first. And at Pro A, and we encourage this in our clients as well as we, we actually have an AR GO AI Governance council, and we also make sure that we have an AI usage usage policy that’s defined very early on.
So this kind of reduces the anxiety for those users about. You know what’s permitted, what are the norms and also signals to them, and it’s actually part of our, our mission statement as the governance council, that AI is not here to replace them, right? It’s here to make them better at what they do. It’s here to augment.
Their capabilities. So this ultimately anchors the enablement and, and the risk tolerance and compliance. If you think about the, like, the industry of robotics for a long time they were all about the three Ds. I dunno if you’re familiar with the three D’s, but it was, you know, get rid of the dull, dangerous and dirty work.
There’s similar in the AI world where, you know, getting rid of the dull, disruptive, and draining work. For our users, and by doing that you can actually show them immediate, immediate relief and they kind of understand, wait a minute, this tool is here to help me. Right? It’s here to take meeting notes, which I find onerous take.
It’s helped, it’s helps me get through those long email threads that I have to summarize after I’ve been on vacation for a long time. It gets you started on then those initial drafts of documents and it’s amazing how fast. The skeptics can fade away when someone realizes they can get a B hour back in their day to do things that are more creative and more productive.
And we, we run this play openly within pro A. We also, like I said before, we build a Champions network and we train in the flow of work, and that’s very important. We don’t make this kind of an option. We say, this is the new way you’re gonna do work and this, these are the tools you’re gonna use and this is the process you’re gonna use.
So it’s important you identify the early adopters. We have a user group that we run every month where we’re constantly training folks on what’s the latest and the greatest things within AI and copilot, and we share what’s working and what’s not working. As I said before, we, we really adhere to that adoption framework from Microsoft.
We, we can make this repeatable as we continue to expand it across the organization or when we’re working with our customers as well. And, you know, it’s, it’s, it’s really about, you know, what’s gonna stick with those users and. And being able to prove, you know, return on investment to the, to the exec teams.
Thank you. That’s
Brian Thomas: awesome. You know, I, I really like how you take this approach. You know, obviously there’s a lot of anxiety ambiguity in this, right? How do you reduce that? Well, you have to have some structure in place. Like you very familiar with the AI governance councils AI usage policy. And again, taking by that messaging of taking away the fear.
That these tools are here to help and augment what they’re trying to do. I like how you highlighted reduce that dual disruptive and draining work. I think that’s important. Get that message out there, but really identify those early adopters. Capitalize on that success. Appreciate that message and Jim.
Sure. The last question of the day. What developments in cloud AI or adjacent areas, maybe edge computing, large language models, ML ops, do you believe will be the most disruptive over the next three to five years? How should organizations begin preparing now so they aren’t cut off guard?
Jim Spignardo: And I think there’s a lot of things that are obvious that are gonna happen, and then there’s a lot of things that we just don’t know yet.
Right. And so, you know, on the obvious front, uh, a Gen AgTech AI is definitely here to stay and it’s gonna be built into the, the enterprise stack. You look at what Walmart’s doing right now, you know, they, they started out with all these various agents and now they kind of have this one monolithic agent that runs all of their business.
So we’re gonna be really seeing a shift from copilot as a personal assistant to actually. Processing work that spans teams and systems, not just for individuals. So think of it as, you know, forecasting what’s gonna happen in the business, helping on the customer support front, being able to provide better security coverage.
So the, the other thing too, I think you’re gonna really, what we already are seeing is around SecOps security operations. Microsoft has their platform for copa, for security. You’re gonna see a lot more of that built into to systems. Thir first party, third party, where AI is gonna be used to triage threats or vulnerabilities or incidents.
And respond in minutes and not hours, instead of have to have humans looking at this stuff constantly, it’s gonna alert them the fact, alert them to the fact that, okay, we found a threat, we took care of the threat. This is what we did. But even with those more sophisticated things, being a partner in that troubleshooting or hunting to kind of try and pin down where the, where the the vulnerability or threat is coming from.
And then, you know, if we look at. Data governance. This is something that a lot of organizations have struggled with tremendously, but it’s not really gonna be an option as we look at the, the age of AI where data is, you know, and not that it’s not important now, but it’s, you know, it’s really, really important to have good data governance and also treat your data as though everything has a purpose.
Everything should carry a label. Everything should be protected based on what that content is. And making sure all of that’s in place and, and many organizations are very much behind in, in all of that. And so, you know, we’re definitely here to help our customers, but it’s something that’s new and it’s gonna take some time.
And then, you know, if you look at what are the things to, for organizations to be aware of so they don’t get caught off guard when all these changes are happening. As we mentioned at the beginning of this top, this discussion, make sure you’re standing up those landing zones, establishing good governance for your cloud environments, ensuring that there’s the right rollbacks, role-based access controls in place from the very beginning.
Not discounting resiliency. It’s great to use the cloud for a lot of different things because again, you can scale very well. It’s very dynamic. You can scale in, scale out, and you can build things very quick, but you have to make sure that it, that they’re resilient. And, you know, around ai, one of the things that I, I think that a lot of organizations overlook is this concept of a governance council because they really are just getting started and, and they don’t even have kind of a sense of.
Well, what that, what would that look like? But once you get people in the room and you start having conversations, you realize that now more than ever, you can’t really get away from not having eyes on how this technology is being used and all the right players in the room. So, for instance, our governance council includes our ciso, it includes our representative from legal.
People from our di uh, digital engineering teams, people from our HR teams, because they all need to have input into how this, these technology is gonna be used and how they’re gonna be used safely and ethically. And lastly, really it’s about, you know, making sure you, if you’re tinkering with ai, you know, start thinking about where the business pain points are.
Don’t, don’t come up with use cases first, but think of what the pain points are, what you’re trying to solve for. And pilot two, agent two use cases. And tie them to explicit KPIs that you know are gonna be able to demonstrate value quickly, and then scale that as you find things that work.
Brian Thomas: Thank you.Really appreciate that. There’s so much there. And you know, as you look ahead, you’d mentioned there’s some things that are obvious, some things that are not, but Right. You know what Agen AI is being built into the enterprise stack today, but as you mentioned. Probably see a gradual move from the copilot personal assistant to those enterprise agents, which I, I see organizations doing that today.
You mentioned SecOps. I think realtime monitoring, alerting and actual tasks to remove threats are important. Again, with so much data and so much, so many endpoints to protect, I think it’s important to leverage AI there and establishing good governance and role-based controls and access. I think it’s very important as well to help keep things kind of buttoned down and then building that resiliency.
I really think. What you talked with our audience today is very helpful and it’s gonna help a lot of folks start to navigate down their roadmap. So I really appreciate that and Jim, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Jim Spignardo: All right. Thanks Brian. Appreciate it.
Brian Thomas: Bye for now.
Jim Spignardo Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
