View Recording: Top 10 IT Trends for 2025

Everybody, this is gonna be a great session today. I am really proud to have the opportunity to spend some time with you. My name is Naples, nosci. I’m a concurrency chief technology officer and we’re going to spend some time talking about the top trends for 2025 and how technology is changing around us and innovating things that we’re doing and a lot of content covered today, but also a lot of ways for you. To take advantage of your your upcoming your new year that we’re already in. Wow, this is awesome. So a little bit about me. I’m a concurrency ctoi have spent the last 22 years in tech consulting and spent a lot of my time helping organizations executive teams to direct where they place their tech investment. That includes AI includes. Their infrastructure includes the road map around how they think about their organization. And today, I would love to convey a lot of those themes to you that we’re seeing from many of our shared customers. What you can see on the screen is my QR code for LinkedIn. I would love to. Be in your social network. I’d love for you to take advantage of a lot of the content that I produce every week. I produce AAI leadership newsletter and there will be another one coming out today around 5 habits that you can apply in your organization to help employees gain AI competency. I think you’d get a lot of value from that. There’s also another, probably 25 historical newsletters associated with that same. Sort of content. So connect me LinkedIn, follow me on LinkedIn. I would love to be an asset to you in that way as we start today. I’d love for you to drop your questions in the chat. I can’t promise I’m gonna get to every single one of them, but I certainly will do my best to be answering those questions as we come along. So what are we doing today? We’re gonna review each trend and as we review each trend, I’m going to talk about why it matters. A little bit about the context of it and then some content around. How to take action from those trends? Think you’ll get a lot of? Uh, a lot of next steps out of this. I think you get a lot of actions that are possible and hopefully it’s an opportunity for you to make this real in your organization, whether you’re helping to educate the next generation of student. You’re enabling in your business, or you’re somewhere in between. You’re enabling your employees to be the best version of themselves. Now is the time for us truly to be talking about these subjects. So the first trend that we’ll be talking about today. Is employee AI adoption at scale? This is really something that we’re seeing hit as we hit the 3rd wave of AI adoption. Think about maybe the Wave 0 being everything that happened before. Generative AI we then had these sort of two instances where companies were first trying to figure out what was going to happen, understand where AI was, was moving their organization. They had to discover they had to talk about it. They had to envision and then they entered into sort of APOC phase of starting to play around, enabled employees to poke and prod and understand where it might. From here, what we’re seeing truly as we’re entering into this year is every organization is seeking to take advantage of AI in their employees at scale across their organization because they know that AI is enabling employees to be able to produce more than they could without it. So. Let’s talk a little bit about that subject. So I want to use a little bit of a historical reference. If you remember these these examples from the past. Think about when Steve Jobs, Steve Ballmer said. There’s no chance that the iPhone is going to get any significant market share. No chance. Not going to happen, right? Remember that. Remember when he said that? He then said, man, it doesn’t appeal to business customers because it doesn’t have a keyboard. Now I remember seeing my colleague who had gotten the first iPhone and I was blown away, and I recognized at the time there were millions of business consumers that were using their blackberries and were using these like little keyboards that existed on your your phones to be able. To do productive work, and Steve Ballmer at the time wasn’t wrong. In a sense, because I remember trying to pull the BlackBerry from the cold dead hands. Of the the business consumers that were using it was like, wow, this is they really believe that this is going to drive their productivity. It did. It did. It’s in a significant way, specially because they didn’t have the capability before, but to look at that statement now, we really realize how was missing what the future was going to be in the context of producing true outcomes from AI, we realized that a change was coming to. The way people were productive. Now you may have noticed. This decent conversation between Benny Hoff and Satya Nadella around copilot. This idea of Bennyhoff calling it the second coming of Clippy, I think it kind of fits in that same picture you’re seeing an organization that is maybe a little bit on the outside of where some of that general productivity exists. It’s not to say that Benny Hoff is wrong around the idea of creating very direct AI agents. We’ll talk about that more later. That’s where sales forces put a lot of its focus. Listen for a good reason, but this conversation here is about how do we enable every person in their general productivity to achieve more. So when you think about the role transition is happening with artificial intelligence on a every employee basis, we have to realize that your current job. Is moving to a future job. What you are doing in five years will look very little like what you’re doing now. Doesn’t mean the outcome won’t be the same you’re trying to achieve an outcome like a financial plan for a customer. Or an inventory that you’re selling to a customer based on a product you’re building, but how you get there is going to change because you’re going to be able to lean on artificial intelligence for every employee’s productivity more than you ever could before. And the momentum that is arriving this year and has been arriving around every employee being able to take advantage of these capabilities has really started to roll down the hill in a positive way. So this is an opportunity for us to really take a step back, look. The kind of work that we do, look at the kind of work that our colleagues the left of us to the right of us is doing and how we can help them to be able to really gain positive momentum from using artificial intelligence in their daily work so. Some examples of those activities that are being learned are are the ones that you see in front of you. So let’s hit each of these one one that we’re probably already using today is the idea of having an AI agent, research and prepare information for us. We are preparing for a meeting. I want to understand. The performance of that organization stock over the last five years, so I know walking into that meeting, how they’re doing, right. Like in the last year, we’ve had companies that are doing really well. We’ve had companies that aren’t doing so well. I want to know how is this company performing right now. How much free capital do they have? Are they willing to invest? Are they looking to do transformative work? And maybe that’s based to a certain extent, with their predisposition is based on how their business is doing. I can get that information just by asking copilot for it. I might also be delegating management of post meeting. Actions I might be asking copilot to perform some activities for me or or having it assign an action to an AI agent that’s going to go and take secondary action based upon the meaning we’re delegating something. We’re essentially learning a new set of skills which is delegating to an AI agent. This is not something that we simply learn on our own. We need to have training and capabilities to be able to perform them. We also might be having an AI agent take regular action based on a reoccurring. Situation something that’s occurring on on every day. Maybe I every single time I have a post meeting action item that creates the. List of things that need to happen that AI agent assigns the to Do’s to all the individuals that are assigned those tasks. Maybe every time an invoice comes in, I have it automate the process of reviewing it for certain data points, and if it doesn’t, those data points don’t exist. I’m going to kick it back to the person that had produced it. I might then move into running processes autonomously. Maybe I’m performing a long running activity every single day. I’m I’m working my way through invoices. I’m working my way through the accounts receivable. These things need to be reviewed, but there’s there’s seven things I look for every single time and I if I had an AI agent that simply check those seven things, are there, maybe I wouldn’t have to do them anymore. Or perhaps I need to evaluate? A customer’s financial portfolio. Before I have the meeting with them, what if all the things I need for that meeting could be prepared for me by AI agent that I delegate to it, and that’s where things like delegate a set of complex tasks, even in the context of development activities, is this. Really exciting. So think about these kinds of activities in the context of how you’re enabling this within your business. Then ask yourself this question. Can this be a moment where every we enable every person to be the best version of themselves? Why is that so powerful? Well, it’s powerful because we have to realize that leveraging AI at this point is and has to be about enabling every person to be able to be the best version of themselves. And that may mean that. Some of the activities that they previously did are activities they perform anymore and we have to look to how we enable that person A to do the delegation, but B to be able to discover what their future job is. And this is a major point of transition within. Most of our organizations, whether it’s small or large, it still exists in virtually every job. So if you think about this, even double clicking in another level, OK, so think about every employee in your organization, every information worker. Minimum is is part of meetings. As they enter into that meeting, there’s at least six activities that they could be using AI for in the context of that meeting, and I do each of these literally every day. Well, hopefully I don’t do the 1st 1:00 every single day, but it happens to me pretty frequently is I’ll join late, right? I’ll join the meeting late and one of the first things I’ll do is I’ll ask copilot to ask what happened already in the meeting, and sometimes it’s important, and sometimes it’s not. But it gives me the opportunity to not have someone else give me the summary. Sometimes I may not be able to attend a meeting. I may even follow the meeting and ask what happened from the AI agent. I may even ask what? What did somebody say? Sometimes I might not totally understand what someone said. Maybe it’s a thick accent. Maybe it’s something I just didn’t hear and I need to ask the AI agent to provide me that information back. Or maybe I need to know what questions haven’t been asked. So a common thing is saying, you know, this is what’s happened so far. What are the things I might need to know that I haven’t already asked this customer? That copilot can usually provide me a helpful list of questions. The idea of summarizing the meeting, taking those action items, asking for tone, who disagreed. Who didn’t? Having the ability to then assign the action items into follow-ups and then in this case I just discovered this one recently, I had had a series of meetings with a with a customer and each of these had been recorded and I was working on a. Road map and I was like, oh man, I forget what the this this data point. I forget if they have this. Particular thing and I was able to ask the combined summary of all those meetings, the transcript of all those meetings, to answer that question for me, instead of having to go back to the customer to ask that question again. And I was like, wow, that was like killer cuz it really enabled me to be more productive. These are the kinds of skills that your employees are either either have. They’re using every day or they don’t have and they simply do it the way they did before, which is less productive and less capable. You might also be enabling your employees to ask for information. So like in this case, then we’re asking for information about sales performance. It is producing the report for us historically. Maybe I had to go like a specific report or a specific power BI view that I had to go create or ask someone to create. What if I can ask questions of data and have it provide me the answers and then be able to leverage that information from. A trusted lineage to be able to get work done. These are the ways we’re talking about enabling every employee to be able to get more work done. As a component of leveraging AI agents. Then moving into automating repetitive tasks with things like copilot actions or other kind of similar tools. Enabling summarization of communications or taking care of a task or creating a new document based upon a summary, enabling these activities that happen regularly and delegating them to an AI agent, and what you’ll probably learn is some things were great. Some things might not work great yet, and that’s OK. This is a part of us are evolving along with this. The Washington, one of the ways I’ve been thinking about this is we. We all have that person of our life who still struggles to use their mobile device, right? Like they they just don’t get it right, and you’re just like, why is this is so simple like my my 10 year old can work on a mobile device. How come you can’t? But a lot of that’s just because they haven’t learned it along the road, and it has been become part of their regular task. We have to enable every person to be able to have these capabilities, especially in the workforce. Where this then ultimately goes is the ability to record activities and describe them. Like imagine that I have us. I brought in an intern and that intern is going to perform a task that I know how to do and I do in my sleep, but I’m going to describe that task for them. Old school, RPA. You might record it, but it has to be done. Exactly how the RPA did it. Right. Where is the sort of new school RPA going? AI enabled RPA what copilot and other tools are capable of? Is the ability of not only recording it, but I’m describing the intent and I’m describing the activities along the way. And as I described those, the AI agent gets my intent and understands what I’m doing to be able to support. Performing those tasks at scale, so I create a smarter delegation to an AI agent that’s able to perform actions that I couldn’t before. See where I’m going here? Every employee needs the ability to learn these kinds of skills. What we then can do is we can measure how many employees the outcome of these activities are occurring, who’s using what, how often are they using them. And then once we have this data, this is from copilot analytics. So like. How many summarize meetings are we doing? How much intelligent recap are we using? Etcetera. And then it once I have this information, I can start to correlate that against business results. So I might see that my low usage employees are having less deals, 1 less outcome then my high usage employees that are creating more outcomes for my organization. I can use this information. To cross validate. Their performance, the things that are that really matter against business performance in their role and as we get better at both measuring their business performance and measuring their usage of AI tools, we can correlate those things to help us to be able to enable more people to get. Productivity. I’m working with an organization that has automated sales quoting for every employee, right? So they they have hundreds of sales reps and as they perform that sales quoting the employees that are using. To automate their sales, quoting are dramatically decreasing the amount of time it takes them to get deals out the door in comparison to those that have yet adopted that tool. So you’re able to really be very prescriptive about the usage of these AI tools. So what you’re doing is you’re training every employee to building delegated AI agents, and you’re enabling them not just to do general productivity functions, but you’re enabling them to delegate complex tasks. To AI agents that that AI agent then performs on their behalf. So that’s making AI agents with things like copilot studio. As an example of how easy this is. I have frequent workshops that I run with. Organizations like high schools or IC stars or other kind of other kind of internal enter organizations where they don’t have a lot of tech background yet, but they’re starting to get. That tech background and they can very quickly build AI agents regardless of how much background or experience they’re coming to the table with now. Some move faster than others, but everyone’s able to create an AI agent just based on the ability to follow prompts and describe the things that they want it to do. So a lot of opportunity that exists in organizations to be able to gain ground by delegation and creating AI agents that everyone can get real value from. So what you then see are agents that perform tasks like next best action or lead qualifying or expense approving that perform activities for us. So our goal is enable every person to achieve more with these kinds of activities now. As we build these, you’ll see the capability of the AI agents that we’re training our employee. To move up in the stack. So we’re moving from no AI, which is where many of our employees sit today to AI as a tool, which is where we start to leverage it just generally in our productivity. Maybe we’re using it as? Like copilot but without grounding to employee data. But then you start to move into things like employee as a consultant or as a collaborator where it’s providing information I couldn’t have found before based upon agent I’d created. Or even as a collaborator, where it’s sitting equally with my ability to produce goods to a point where I’m able to truly use it as a delegated agent that’s performing something that I trust it to do. And then maybe even as leveling up me. And that’s where as we keep moving down the road, it continues to move up that stack. So as you think about this, the last area I want you to think about and just kind of imagine this for a second. What if? Then think about in the context of development, OK, what if offshore development was replaced by delegated AI agents? What if offshore development was replaced by delegated AI agents? I don’t mean that to say like getting away from people who exist in a global economy. Me. What I mean to say is sometimes when we delegate activities we’re looking for like the cheapest way to perform something. We’re looking for a way to like drive down costs, associated building software or creating capabilities. What this is essentially doing is creating maybe some of those, those high scale, lower lower skill tasks and enabling AI agent to perform those. Or maybe if I had like. 5000 stored procedures I need to refactor. What if I could create an AI agent that actually helped in refactoring those 5000 stored procedures? Did it at scale, enabled it to be done the same way? How could I gain ground performing that kind of scaled activity? This is where it’s also coming to the development ecosystem and you’re seeing so much movement from what copilot get up. Copilot is possible to do yesterday now able to do today. Continuing to enhance into the future from code refactoring to security analysis. To making the first draft of a set of code based upon a set of business requirements to building AI agents that don’t even have a high dependency. So this is sort of activity #1 enable every employee within your organization to be able to be more of AI. The next activity is where we take this truly into product engineering and that’s that’s really starting with that skill of enabling AI to be part of that. Picture, but it’s also about building products that engage. To our customers and sometimes that is low code, sometimes that is AI agents were performing just as an everyday task. But it might mean that we’re building something as a product that our customers are engaging from us. So when you think about that, think about successful AI adoption as actualizing the mission of your business. Your business has a mission. It has a a goal that it means in the world and AI adoption is not about changing that mission. It’s about actualizing the mission and. Context of your employee adoption. It truly is about that. How does every employee be better at actualizing that mission in the context of product development? It’s the same thing, but it extends it further into the ability to serve our end customers with products that they’re using from us. So the way that you do that is by creating innovation hubs that exist within your organization. So organizations are finding like, hey, I put a couple lines in the water. I tried something out. I’m not sure how that you know I’ve I’ve got some value from it, but. Haven’t built the muscle memory to do this. Well, Sachin Adela has said that every company is a software company. Every company is building capabilities for their customers and I’ve seen that every day. Companies have never thought about themselves as software companies before, are now becoming software companies. Every company is also becoming an AI company in the context of which they deliver that innovation to their end customers. So this is truly about building a cycle, a muscle memory, an ability to harness ideas. Drive them into experiments and pilots, and then choosing the ones that continue forward into solutions for my end customers. Building that muscle memory inside of an organization, the companies that do this really well are going to get wins. They’re going to discover scenarios that work, scenarios that don’t, products that work, products that don’t. But the ones that put the energy in are going to be able to gain the ground, the ones that don’t put the energy in are going to be right where they are today. So the way to do that is to think about what are the possible futures that. Your organization can be in. Where is that possible future? What does it look like for your organization and how do we work toward that possible future? Very intentionally, by attacking with a scientific method, the goals that sit before it. From possible to plausible to preferred, enabling us to develop a long term and short term goal oriented forecast. That sits in two tracks. The first track is supporting and enabling the current business with products that. Enable my customer sustained innovation enabling my customers, but in conjunction with that, there’s this idea of tracking toward disruptive innovation. Future business that can exist now in the short term that enables our organization to sustain, to live into future generations and this is truly where many businesses struggle because they struggle to think about anything other than how they make money today. Anything other than how they serve their customers today? And maybe short pivots on that from the right or to the left? But what we truly need to think about in the context today, I innovation and innovation in general is how do I position the mission of my organization for when the technology changes, when the needs of the customer change because someone else came into the market and disrupted it? How do I become the disruptor? And that’s the opportunity that exists for us now. And if you don’t do it now. You’re it’s. It’s sort of like one of those moments that kicks us in the ****. Right, like. Oh my gosh. Like we all have these moments in time when the Internet became a thing where the mobile devices became a thing, where it’s like we kind of get jogged out of our out of our sleep. Right. Like we have to be shook to wake up like. Wake up. Ah, this is that moment in a sense of AI sort of waking us up again, like things change the the business, climate changes, the ecosystem changes, and our product cannot continue to stay the same. As innovation occurs, this is the moment for us to shake ourselves awake. And look at that moment as an opportunity for us. So as you’re building that product engineering muscle. Which you’re also going to find is that you have stages that things go through, and you can screenshot this, or you can get the deck from us later. One of the things that you’ll see here is you move from POC to MVP pilot to ML OPS. As you gain confidence in the solution you’re building, but organizations that are building that muscle, they understand, these are the things that are necessary to run it right. Microsoft just. Released a really excellent red teaming AI Systems report and it’s like all about how to build external products that are Red team really well now you’re probably not going to do that as you’re validating something even works in. 1st place your POC ING it. You’re like is this even a good idea? And you start to go through that process, but then as you move from that process into what’s really possible and then from what’s really possible into what’s practical and into operationalizing it, you realize all these things need to be done, right. You need to build all these components for it to be part of your true product engineering function. So you start to gain this ground. In enabling it within your organization. But that’s not all. Satya Nadella had this really killer statement recently, and he said SAS is dead. SAS is dead, he said. All software applications that we know today are just fancy interfaces sitting on databases. And there’s a link in there for the hour and a half long podcast. Man, it was really worth it to listen to around this content. Around this idea of what is he really talking about? But he also covered all sorts of other things, like how he got to become CEO. Oh, and like his leadership style and I’ll managed it was like a master class in understanding who he is and how he leads one of the most powerful organizations in the world. But what he’s getting at here is that we’re so used to interacting with everything via this like CRUD interface, right? I add things, I remove things, I adjust things. He’s talking about how. Our means of interacting with software is transforming overnight. The ability for us to converse. And interact with our applications to have it return information to. Maybe they’re being diverse ways that I even solve a problem or interact or have a response to an application is changing dramatically. AI being the vehicle to engage with data, to engage with automation, to engage with workflow in a way that you can think about. This is a agent hierarchical structure, right? I’m sitting here. I’m interacting with a supervisor agent. That’s performing activities on my behalf. I may be asking for data I might be return data I might be. Asking it to perform a task for me or to automate a task for me, but all of that is sitting on top of this sort of collection of agents that perform activities on my behalf as part of building and enabling a software product. Every software product is now becoming the AI software product. It’s not like you have AI projects and you have development projects. No, they go together. You have AI enabled software projects. And each of those bring all those packets together to be able to accomplish a good. AI enables every single part of your application to enable your customers better. And it’s just simply part of the muscle of delivering on common applications today. So building this muscle from innovation to doing it right are as part of enabling your organization today. And it’s a major trend that’s happening right as we speak. OK. So as we continue. Deep breath, right? That’s a lot of content. We just hit two big topics and we could probably just do a conversation just on those topics by themselves. But now let’s move into this idea of what does it mean to optimize it operations that supports all this cause above the line we have all this innovation that’s happening, but in conjunction with that we have this continued need that the business always expects for us to opt. The way we operate the IT organization. In this, in and of itself requires focus and engagement and energy, because we can’t forget, just because something is creating this disruption within the market. We can’t forget that, like, only a few months ago. Like half the airlines in the world and huge groups of of of organizations were completely shut down during that crowd strike disaster. That was like a basic IT operations problem and we realized and I think I I sometimes forget this myself like. I remember sitting in sitting in the airport, getting off the plane, seeing the United. Consoles being blue screen and being like wow, like I sometimes forget how important it operations in and of itself is to us being successful at delivering our core capabilities as a like as a country, as a business, as an individual. How critical that truly is? So what is optimized IT operations? It’s every organization needs. A simplified, efficient and secure it. That protects and powers the business. It has to exist. Its function continues to change. Its responsibilities continue to change as the cloud cuts off things that you have to care about. I may not care as much about a person that’s able to build the storage solution or implement the core networking because I’m not responsible for that, but I do need the cloud networking. I do need the connectivity. I do need to think about patching. I do need to think about the. Fin OPS associated with it from a financial perspective, all that still is important. Because it’s real to how we deliver our capabilities to our customers. So guiding principles for it operation. I’m gonna hit each of these and I think these are really important. Take homes as you think about where you place some energy and I’m not going to go into every single one after this, but I think it’s important just to kind of put these out there as you think about this in the context of your organization. So the first is this idea of commoditized end user computing. It means that every. End user computing device should be no different. Then going to your ATT store, picking up a new phone and connecting it to your Office 365 tenant. I lose it. It’s gone. I get a new one. It becomes the secure commodity that enables every employee to be more productive. That is the end game of end user computing. Many organizations are not there yet. The number of companies that have truly gotten to like Autopilot deployed. I ship a brand new PC to you from the vendor you log in, they start using it on day one. It’s securely connected to my organization. You far between. This is a core goal of every organization. In order to enable efficiency, yes, but also the ability to enable productivity across those devices. That then relates to the second principle, which is identity as a representation of user roles and rights. Many identity environments for customers are a mess, just a complete mess. They’re meant. They’re a bunch of organizations, got eaten up over time. Time there are roles here, roles there, legacy users there. It’s a mess. How do I make this better? I make it better by saying when an employee joins my organization, they have a role. They exist in the HR system. They then move to having roles and rights assigned by the identity solution that give them access to the computing device, their collaboration, their applications, their commodity, everything that is driven from who they are and that. Function of identity being a representation of that is truly a critical aspect of how we make. Work happen within the business and secure it, which relates then to the simplified and strengthened security stack. If you get those two first things right, you’re well on your road to getting a simplified strength and security stack. So many companies have, like, got a problem. Add a tool. Got a problem. Add a tool and their environments are made-up of this huge collection of tools that make them very inefficient at executing on these functions. They have teams that don’t know how to work them together. They don’t talk. And you end up with a big collection of things. That’s not saying that like you have to move to one stack. What I’m saying is, this is an opportunity to think about simplifying your stack and putting you in a position where things work together and they work. Simply moving that into this idea of consistent collaboration and communication. Have I simplified the way people interchange with each other? And the rights associated with that relate. So like a question that comes up with AI adoption is whoa, like I enable AI. And like, what if they can see, like, the salaries of people and some spreadsheet that they shouldn’t have access to? Well, this is the wake up call, right? We’ve known this is a problem for 10 years now. It’s an opportunity for us to do the over sharing report to make sure they have access to a single panel for us to apply rights through Microsoft information protection to give us truly a good picture of how we take this down. So consistent collaboration, communication, truly a goal of a principle of IT optimization, then leading into. An operationalized cloud data center estate with fin OPS as part of it. Sometimes now and you’ll see this in a second when people start pursuing AI applications. When they start pursuing the optimization of applications into SAS and Paas. When they start pursuing data states, they realize ah, I. Have not built the foundational operationalize skills. That need to exist in my cloud data Center for my IT team to support those goals I don’t have. Those I don’t have that muscle memory yet. They don’t know. Infrastructures code. They don’t know how to execute on any of these tasks, so it puts them in a really weak position to be able to pursue their overall goals. So in, in what’s part of this, too, is this idea of enabling fin OPS in the context of that it opt. And the last one here is then building on that. Modernizing the application of state moving toward pass moving toward SaaS applications. I was working with an organization the other day by mid year 50% of their data center should be shut down because of modernization to SaaS as a component of their applications and then the rest of. That were either moving to a path solution or migrating as is into the cloud. Getting them out of the data center business, but doing it smartly, right? Doing it in a way that’s tied to fin OPS. Optimization along the road. So these goals, these are principles that enable us to get our it supporting function into a better position, evaluate which of these are really working for you, which are not. Which have I achieved? Which have I not achieved yet. So how do you measure it? This is a list of those I can go in every single one, but this is a list of ways that you might evaluate that you’re getting there, right? Like so like am I saving money month over month? Vmi cloud fin OPS capability. Probably not. Most of the companies we engage like they have not built that muscle memory. They’ve got spend all over the place in the cloud. Estimate that like 30% or more of your cloud spend is waste. How do I get that back by applying a thin OPS capability? Or what are the percentage of systems covered by single identity solution? Many organizations pretty low, like we’ve got a big distributed identity solution. We haven’t consolidated them together to be able to manage this better. So think about these kinds of measures as you’re evaluating how I work with my your IT operations goals. So that moves us into the theme or which is to position data for the mission of your business. Again, deep breath. Wow. Like like this is. I like my you could say like your mind may be exploding right now. Too much stuff, right? Stick with me, OK? So next topic here, positioning data for the mission of your business. This is a critical goal for every organization in this common year. Now, what does it mean to position it for the mission of your business? It means create value for your customers. Create value for your customers with the data and the rest will fall behind it. Create value for your customers with your data and the rest will fall behind it. Focus on value creation. Focus on outcome. You drive for your customers or your customers, customers and the result of that will be better operations, better revenue, better delivery of capabilities. It’s not just about creating reports for your. Well, it’s about creating value for the customer that’s buying the product from you. So what are ways that you might think about that picture? Ways you might think about that picture are to align product and availability and pricing for their needs. You might be thinking about like I sell a product. I have product availability. I have pricing for my product. I’m not sure what my customer needs. How do I align those two things so I have my product available when they need it? And my pricing aligned to what they may want to buy it at. And that allows me to be able to be their best partner, their best partner. But then I might take that and provide insights into their business, because in order for me to understand product availability and pricing, I need to know them. I need to know what they’re going to need this year. So once I know that I get insights into their business, I start to base my product delivery patterns based upon their business needs and I can then leverage those insights to provide. I’d prescriptive best practices back and I can leverage that not just against MY1 customer I’m working with, but I start to understand my collection of customers and what makes a successful customer. What makes a successful business I’m serving? Imagine I’m serving restaurants and I deliver food. What do I know about restaurants? I know you want to stay in business. I know. Which ones don’t? I know how they order. I know what they order. I know the kinds of products they order and how they stock them. What if I was able to create knowledge that enables me to be able to provide perscriptive activities and choices, top quartile best practices to all my customers that I then charge them more for? Now you’re pivoting your business model. You’re pivoting your business model, not just in delivering products. But delivering insights based upon data that they will get value from and you’re driving your company forward and their company forward to have them create real value. This is where the data estates possibilities exist in your organization. So driving an example of this is Fox World Travel. They created a self-service AI enabled reporting engine that enabled their customers that they deliver manage travel experiences for. To understand more about the travel. Happening for their company. Compare their spend. Produce it in an interesting way. Give them the ability to start to explore it in different formats, then ask more questions around best practices associated with that spend. Where can I get efficiency? How can I drive my cost down? Where am I? What are my pairs that I use? Like what do I fly between and how might I optimize that? Can truly enable real insights for customers? So when you think about your data, I wanna. They like that all sounds great, right? Like, OK, cool. Let me want this. But then you have to think about like, how do I get there? And you can see on this slide when you think about your data, you need to start first with value driven use cases and you can see in each of these like executive financial visibility. Where’s my truck? Personnel optimization, demand, inventory. The quality optimization channel associated with OT data and you start to get like these. Visit these lines, these verticalized lines of capabilities that you’re trying to drive. These are called data domains, right? So each of these data domains are, well, each of these goals, these use cases are supported by data domains, financial domain, the employee domain, the domain inventory domain, the production data domain, the OT data domain. All of these fit in the context of data domains that crossover into each other as needed, and your goal is to make these available to each other. You have to prepare data. That supports these outcomes. They have owners. Each of the domains has an owner in the business and then they have ways of preparing that data. To achieve real outcome, you have business consumers. You have data scientists. They need to look at data in different ways. A business consumer might say I need models to build my reports off of a data scientist might say I want direct access to the raw data so I can do my experiments. All of that supports Elaine. All that supports Elaine and then these cross together to create customer 3, sixtys or other. Visualizations that enable us to gain real outcome for our customers. So we can’t get to that end game until we understand the data that we need to make that happen and what functional domains they need to exist in to be able to attack it. And so our end in mind may be what we talked about previously, but to. Get there. We need to do the hard work, so that means climbing the data maturity curve. It means that every organization’s in this process, if you’re still sitting down here in Excel and Manual or sitting in an on premise data warehouse. You have to do some hard work to get yourself in a position where you can start to. Create that real that real value, building toward a modern jade framework that I just showed, sort of verticalized view of enabling that for my organization and then gaining insight, wisdom, and impact associated with that meaning. I’m predicting something. I’m prescribing something and I’m storytelling something. I predicting something about my customer. I’m prescribing what they should do with it, and then I’m story telling around best practices and guidance and best ideas that happen as a result of that data. Truly helping them to be able to be more. So as we wrap up into the 5th theme again, deep breath. This all supports this. The 5th theme is that architecture is making a rebound. So architecture is really about making intelligent, proactive decisions about how I build out my environment, being very intentional about what the environment needs to look like because it scale things start to look very different architecture. On an environment determines how many holes you need to plug. Think about the dam and I have * ***** in the dam and I’m trying to plug those holes. Well, the way I architected that dam is going to define how many holes I need to plug. How effective have I been at building an environment that I spend less time tactically plugging holes and more time architecting my way out of real problems and one one network that I would suggest you follow. Is the chief architect network. It’s a group of about 350 almost 400, I think, by the time you start looking at it. Chief architects around the world that are talking about these kinds of themes and you’ll notice that they’re from mega organizations, people who are thinking about it, collaborating about it outside the context of anyone company or anyone’s like software vendors like sort of hat off situation, right like. I’m not working for anyone. I’m working for you. We’re talking about the context of what makes that happen. Follow them on LinkedIn, this great organization to gather some insights from. So I want you to think about what are the kinds of gaps that cause downstream effects as a result of missing architecture. Like when we don’t do this right? An example that we run into all the time is this idea of disintegrated mergers and acquisitions companies that like they bought a bunch of companies, they’re in their fold. They all have separate identities. They’ve never merged them. They’ve never moved them into one Office 365 tenant. They’ve never optimized the end user computing. It’s just like a big morass of lots of different stuff, and they haven’t brought them together. They haven’t built a pattern to how they intake those organizations. That is like architecture 101 opportunity and there’s a lot of reasons why that may not have been done and. It’s not the the blame has always fall on it, right? But it’s that opportunity to catch back that issue, to get us to a state. Or we can truly be efficient and apply our energies to scaling as an organization. It’s an example of an architecture gap. Another example might be a lack of internal and external identity standardization. I’ve got a bunch of different identities. I haven’t really standardized on any one of them. A missing data taxonomy. I don’t label my data appropriately. I don’t track it. I don’t have command size end user computing. It’s an example of what we talked about earlier in terms of, like how efficiently. Can I roll out an end user device? Have I built an architecture that scales from 1000 devices to 50,000 devices and really isn’t all that different? And that opportunity to truly have sort of architected out a problem is really a big step forward for almost any organization. So make this kind of really tangible. I want to show you an example of this, so ask yourself the question which of these networks is more secure? It’s not a trick question. It’s sort of obvious, right? Like it’s moving a direction. We start with a where manufacturing and server and user network are all on the same network. They can all talk to each other. They’re all sort of commingled. I’m on one network. I can talk to anywhere else on the network. Danger zone. Will Robinson really problematic, right, we know. Kind of obviously that this is an issue, right? We then move into B, which is like where money of organizations sit, which is this idea of server and user network on the same network, but the manufacturing network is on its own thing. Man, that manufacturing network. It’s got Windows XP. It’s got Windows 8. It’s got like unpatched Linux systems it’s got everything there. It’s like a total like disaster area of security and I got to keep that completely segregated from everything on this user network because the 2nd that something’s enters into my environment, that manufacturing network is toast. So a lot of companies at least have that right. They kind of separate those two things. But then C starts to get us to this position of the user network and the server network and the manufacturing network become separate from each other. Start to have these sort of firewall rules that exist here. So C starts to get us to that position. But the problem is that we don’t really do much actually on those firewall rules. We sort of let it just progress and move between those two environments. So D starts to get us this position where. OK, cool. I’ve got my user network. I’ve got my infrastructure, server network and my manufacturing network, but each application is its own network. Each application is its own microsegmentation. There’s a variety of technologies and tools that make this happen. Doesn’t just mean it’s a network network, but just kind of follow the concept that each app is in and of itself, segmented from each other app. To do that, I need to know how does it work. What does it talk to? What? And I kind of have to break it to fix it where this is very uniquely aligned is when people move to the cloud, when they move to the cloud, they have to figure out what things talk to, what they have to figure out what apps communicate and how. They communicate. This idea of building a app network for each application is really tangible and meaningful, and it’s a point in time where they can do it. So you start to see how like that segmentation is really meaningful, then getting to E which is the idea of you’ve already segmented the apps, you have the infrastructure. Now think like your domain controllers, your management stuff. But then there’s a couple other themes in here. User zero trust this idea that each device that’s rolled out may not even truly be on like a corpnet. It may be on more of like a guest network. It’s maybe not even VPN DNS off the network. Why? Because the user device is your biggest threat. Like, keep those things away from everything else. Can I treat these applications almost like SaaS applications in the context of my environment? Then having identity and conditional access truly being the. The factor of how I gate access to my applications and then even in the manufacturing environment truly going to zero trust design each piece of the manufacturing environment being separated from each other. You can see this is an architecture problem, right? This is this is about building an architecture that we work toward, and many organizations they haven’t really gotten gained ground here. They haven’t gained ground, so understanding what we’re working toward is truly the critical goal. And that’s as we talk with companies about like mergers and acquisitions. The first question I usually ask is have you built your destination environment? Do you know where you want things to go yet? Or is that still part of the picture? And many companies, they haven’t. They don’t know what that like destination really is going to look like. So architecture is all about defining that. Another example of an architecture concept is like lineage in the data space. So like if you think about what makes data trustworthy. And what makes people depend on it? It’s where it came from that they know where it came from back to that like maturity curve. Why do people export data to excel? Will they export data out to excel because they need to trust where it came from so they go back to the source system. The expert to excel and they do their financial report and then they do that every month because they want to trust where it came from. What if I have trusted lineage as to how it got to higher up on the stack to the power BI report? They look that power Bi report. They don’t say well. Oh, I don’t trust that it doesn’t look like my data. It looks like wrong because it doesn’t have these things. They need to trust the data that got there. Architecture concept is having lineage from point A to point B to Point C to point D in the context of my data flows being able to represent that if I can’t represent the lineage of my data, I don’t have trusted data. And then the last piece of this, this idea of fitting my AI elements together. Maybe I’m starting to use M365 copies. Cloud chat. But how does that relate to an agent that I’m building that might have a different chat? It might relate to a teams app or web app I’ve built, and then maybe I built a custom agent that has the analytics view and all these have to talk to each other. Now multiply this times 100 or even 1000 and you realize how complex our environments are about to become. This is where the resurgence of architecture is happening within organizations. How do I solve for this problem now? You might be like wow I. It started. I’m not even close to this problem. That may be true. Let’s go back to step one right. But you also might be a global enterprise. That’s saying, my gosh, I’m putting this into the wild. I don’t know how to ensure I govern this right. The balance between governance and enablement always needs to exist in the context of enabling AI elements within our organizations and architecture is the critical goal around it, and that’s why it’s making resurgence right now as companies are having to wrestle with these problems. So what are we doing next? How do we gain ground? All these five things have to exist within your organization this year. These are the major themes, not just for you, but themes for most organizations worldwide. They’re trying to gain ground in these elements. How are we helping you to do that? Our goal is to enable you to gain ground in these areas, starting with strategy, helping you to be able to move from point A to point B. Now what I would love to do is to have a follow up with each of you that are here on this call. In the way that we’re tying this into follow-ups is these next steps. So the first thing is we would love to bring the event to your company. I would love to take this content and brief your team members on in a in a company specific way on these kinds of themes and talk about them and workshop them and dive into them. So bring the event to your company. I truly mean it. I would love to spend time with your company going through the same content, focusing on areas that you think are meaningful and diving into it truly. And then let’s deep dive on any one of those core topics, which are the topics that are meaningful to you. Let’s focus on any one of them, you say. Like, hey, I really want to focus on, like AI enablement for every employee. Let’s deep dive into it. Let’s talk about how we make that true. And then finally, every one of these have Microsoft funding opportunities. You truly just want to understand. Like, hey, how’s, how’s Microsoft going to help me deploy copilot with some funding? Like now is a good time to be talking about that topic that exists. It may not pay for the whole thing, but it certainly is going to pay for part of it. It’s a good opportunity for us to have that conversation around how to make this real in your organization. So before you leave this call today, I would love for you to be able to fill out each of those different, pick the ones that makes sense for you pick. The ones that are going to drive real impact for your organization and I love to talk about them more with how you can gain ground within your business. So I’m super thankful that you joined joined us today. We’re going to have all these assets available as a follow up. So you can take advantage of the deck. You can take advantage of the recording. Bring it to your. Other colleagues within your organization, and let’s talk about how we can make this real. It’s really been a blessing to spend some time with you and I hope to spend some more, so thank you. Have a great day and thanks for spending time with me and listening to these different topics.