View Recording: What Works and What Doesn’t in AI Enablement

Welcome everyone. We’re going to talk about a pretty bold topic, which is what works and what doesn’t in AI adoption. This is a sort of tell me how you really feel conversation today and I think you’ll find it useful. I’m going to spend some time going through what we’ve learned from doing about 16 visioning sessions with various companies on AI, the various successes that we’ve had in building AI solutions and enabling technologies like 365, copilot, and also where we’ve seen things that could be done differently based upon learnings from executive engagement or lack thereof and other kinds of steps or missteps that we’ve seen companies do well or not so well. So I’m going to use this an opportunity to make sure we convey that knowledge to you and then hopefully we can find ways to work with each other in the future, introduce myself a little bit. My name is Nathan Lasnoski. I’m concurrency chief technology officer. I’ve been working with AI for the last about 10 years, though with concurrency for about 22 so quite a ride. Certainly experienced. What AI has been we had been able to deliver in the context of our customers mission when we first got into doing AI, it was before the chat, GPT craze and the generative AI opportunities and it really represented a space where companies were making bets. But those bets really took a lot of activity in order to pay off. But one of the things we found is that even at that stage, going back ten years, many opportunities for AI to provide real impact within organizations and ways that substantially change the way their businesses operate. So interesting enough, like a lot of the learnings from back then still resonate now and some of the new learnings as the sort of GPT AI creates as a curd has been causing a sense by its accessibility, the lowered bar to get into leveraging AI and that lower bar sometimes causes companies to take approaches which are less than optimal. So we’re gonna talk a little bit about what those negative approaches are that you should avoid and also a little bit about what we’ve seen from how companies have seen success in the past, a couple things that I’m going to ask is if you have questions, I would love for you to put those questions in the chat. Love to answer them as we go as we go throughout this conversation today. Happy to dig into areas where you want to dig in and certainly happy to if it becomes something that requires a deeper conversation. We could see it to the end, or even take it offline later. So please please please ask those questions as you have them. I’d love to dig in. OK, So what? What exactly are we doing in the session? I have three different things that we’re going to do. I’ll talk about what successful AI adoption looks like, and I think that’s really gonna hopefully help set the tone for a little few of things. We’re gonna talk about today. We’ll go into some sort of a B scenarios like what works and what doesn’t work, and maybe that’s a little strong language, but I wanna help you to sort of avoid the traps that exist in adopting AI where people just kind of get stuck in spinning their wheels and then see here is to how to take action like where do I go from here? How do I move the ball forward to be a successful in my AI journey? So if you take one thing from this conversation today, uh, I think for me, this is it. Successful AI adoption is about actualizing the mission of your business. Companies sometimes get into use case validation. Zones where they get lost and they aren’t focused on what does the business need to be successful and how can I enable that business success as a result of AI sometimes say that like the AI opportunities are too rich to focus on ones that aren’t going to add value and sometimes we we we mix ourselves up in the context of the idea of quick wins. You know things that are low risk or low impact or scenarios, but we want to get some experience with it and that can be OK if it’s in the context of experimentation. But it also is a trap because it prevents us from thinking big enough in the context of where our organization could go. So I really urge organizations to think about what is the mission of your business. Why does it exist in the world? How can I leverage my strategy that I’ve worked on as an organization to leverage AI to be able to help me actualize that strategy? And AI certainly provides an incredible change that we’re able to take advantage of. It is as significant as the industrial revolution, and some people don’t take that to heart. In a sense, when they do, their evaluation of where we’re going, but the starting point that the mission of my business is really what counts and and if I’m not impacting that in a positive way. And I spend four months going down the road and it never really got there. It it puts us in a position where you really are looking at the opportunity cost of where we could have spent energy on making AI more effective for us to really help us with the mission of the business. So. So take that. Take that like basic mantra to heart. Because that’s really what I want you to be able to pull from everything else that we talked about today. So, uh, I’ll I’ll kind of build on that. It’s been a year and a half. What have you achieved? We bought a year and a half ago, maybe even a little bit more change on that. We saw generative AI hit the market and hit the market and it really substantial way. And what I’ve each of these blocks I’m gonna bring up on the screen here are going to represent impacts that we’ve seen in customers that I would ask you to sort of self evaluate. Have we seen that same success in our organization and what can we do differently that will enable us to apply AI to make that true? And if you haven’t seen that success, good opportunity to pivot. If you have good opportunity to double down on, but it’s a great point to say like OK, where you’re have in what have we done, have we taken advantage of the capabilities available to us? Have we forced multiplied our business? Does every employee have this capability or are we still kind of just figuring out what we want to go from here and so maybe you’re somewhere in between, so let me walk through a couple of different scenarios that have that same kind of idea. So how they increased revenue for the business by winning more deals? An example. We see all the time of organizations leveraging AI to decrease the time necessary to get the right deal in front of their customer to increase the ability for their accuracy to be spot on to optimize the gross margin of that deal when it is sent to the customer and reduce the time they’re staffed spends building the engineering document or quantifying something or putting together the the actual statement of work that gets sent to the quote that gets sent. How can I reduce the time to quote from a day to to hours or minutes? This is a an area that we’ve seen quite a bit. So have you seen in this year, have you or a year and a half have you been able to achieve increased revenue and if not, what’s stopping you from doing that? That is a huge question, a huge opportunity in front of us. The second is have I improved or have I improved your customer experience by easing frustration now that you create scenario that we’ve seen companies leverage AI assets either for their customer service team or the direct customer themselves by easing frustration easing how long they are sitting in a negative state. It’s ironic that this is the point where we’re talking about this, like, right after we’ve had travel disaster caused by massive outages and all these sort of problems, right? Like customer experience is king and when we are frustrated by ineffective customer experience, we get dissatisfied with the company we’re working with very quickly and if we can improve that customer experience, we put ourselves in a position where we’re able to have a customer for life because they know they treated us well. So many organizations you work with their customer experience this terrible like you call up and you get in seven different phone trees. You move from people to people who don’t know how to talk to you or don’t know what you want, or you explain the same problem 7 times. How can I make that experience a better experience and use their frustration? So I’ve seen companies that have used AI to achieve that same thing. Have you as a question another? It would be have I reduced my inventory carrying costs or have I optimized my my personnel or my material in my supply chain based upon estimating demand? Do I have I gained ground at that many companies have many companies, have not. Companies were talking to that had basically are still doing it by like I’ve got an Excel spreadsheet. I put my finger in the wind. I kind of use my intuition and I make decisions. Someone using tools that might start to gain a little bit of ground there, but this is something that’s always unique to the organization. How do I gain ground in reducing my inventory carrying costs in many cases gain other benefits by optimizing my ability to be responsive for my customer? Have you achieved that or haven’t you know there might be? Am I setting clear expectations with customers that are measurably more accurate than before, and this really correctly attached to the supply chain conversation which is, am I driving a relationship with my customer where I’m able to communicate clearly what is going to happen, and if not, how do I improve that? How do I set expectations even if I know that it’s gonna be 10 weeks? For example, if I know that I can plan around it if I might be frustrated about the time frame, but at least I know if I if it’s accurately depicted. If I don’t know that I’m going to have a negative customer experience because I’m going to be always asking, and I’m gonna be creating a lot of term for you by asking a lot of those questions. Now there might be Employees indicate that availability of AI agents creates definitive efficiencies for them. Have your employees gain that benefit or not have your employees gain the ability to leverage an AI agent to create a definitive efficiency in the way that they perform their work? Or are they just kind of like messing around with copilot a little bit like? I’m not really quite there. I don’t really use in my day-to-day work like how far have your Employees gotten in that real AI Enablement. So on if we really believe that AI is going to change the world, how effective have been making that happen? Have I created a new revenue stream? Certainly we’ve seen this from companies that they have information about an organization or a customer. They’re able to create a new revenue stream as a result of that. So like, maybe I sell a product to wide diversity of customers. I know about what best practices look like with that product. I can inform them with information that is a new revenue stream for me as a premium, that deficit to them, but also enables their business to be more successful. Have I been able to leverage that in this last year and a half? Do I have unintuitive insights into my production process that I’ve discovered? I I know a company that that applied AI experimentation to their production process discovered an ability to normalize it to a degree that they were able to eliminate a huge percentage inefficiency in their production process by leveraging unintuitive insights from AI. It’s it’s really about, like, applying experimentation and research to like research I think is sometimes like undervalued in this space, but it’s so valuable. Like how much can I learn about what makes us us to be able to be more successful in applying AI? So if you take those into, you know where you are. I would suggest that you just think about where you are on this cycle and I would love for you to even drop that in the chat. Like, are you? I’ll talk through each of these and I love for each. Just kind of drop that in the chat so people can get a little bit of perspective. So envisioning and strategy like I I’m just discovering where to go, I’m not sure where to go yet. Then I’m prioritizing that alignment now. One thing no included strategy here, right? It’s not just about coming up with a list of use cases, it’s about matching those to your business strategy. So just think about that. If you’re way you’ve done, this was just to create use cases and you didn’t map it to the strategy. Then you’re kind of missing that piece there. So am I in the visioning strategy piece? Am I prioritizing that alignment? Am I in that point where, like I know what I want to do, I need to prioritize? I’m going to do first. I’m translating that into taking action on those, so I’m and doing projects I’m I’m building it in the context of my other work streams. I’m translating that action improving results, so I’m seeing those results already there. The results are being translated and experienced in our organization. Clint pivoting based on that. So I’m seeing the result good or bad, and I’m pivoting on it. In the last meeting like now, I know kind of what results to expect and I’m scaling it. I’m looking in a way to apply that across my organization in a way that helps me to see broad value in the way that the results are being experienced. So on this, I would love for for you to put if you have have a perspective of where you are on that journey. I love for you to drop that in the chat to others can kind of understand where you where other people are coming from in this context. Let’s see here again. Only strategy, build, vision and strategy now. Thank you. Fourie. And then prioritize alignment. And I thank you evaluating opportunities. Thanks, Barry. Cool. Awesome. Keep dropping them in there. I would love to continue to get that perspective. OK, so you may or may not have ever heard this term before. For me, this is something that really hits home because it’s both a personal thing and a company thing, which is this, this perspective that the hardest company disrupt is your own. The hardest person is disruptive to disrupt, is yourself too. So if you just even think it from a personal perspective, the hardest person to. Change oftentimes is you because we have a hard time as people reflecting on things that we do differently and actually enacting that change because we get stuck in the rut, we get stuck in the things that we do our job to be done is always the same. We go into the office and do ex. Umm. So realize that not only is AI disruption a company thing, it’s also a personal thing, because we all sit in our companies performing a job that we’ve come to learn to know how to do. So what AI takes is it takes imagination, but it also takes growth mindset and it takes us thinking about what we are going to do in a different way than we may have envisioned in the past. And that can be hard for people. It can be hard for myself, I’m sure it’s hard for all of you to change something you did in the past. Your New Year’s resolutions don’t always work or you know things that we try to adapt to do exercising more or whatever. You know, book every night you know is is difficult for us to adopt unless we build a new habits and building the new habit is really what we’re talking about here. So I want to give you 3 terms that you should carry with you as we have not only this conversation but as like where you take from this the first part of the conversation is this idea of what needs to be true. There’s a a gentleman that I I’m gonna include in my newsletter later this week. Speaking of which, I felt the weekly newsletter on AI leadership, so I would really encourage you to follow that. I’ve got about 30 some articles I’ve already done in this topic or other topics related to it that I think you probably get benefit from. So hit me on LinkedIn. Go ahead and follow that and love to get you that content. So there’s gentleman that I’ve worked with variety of times. Brian Evergreen has a great book called Tanous Transformation and he likes to speak about this too. He calls it future solving, but I’ve always thought about as what needs to be true. He’s used the same term and the way to think about it is just like, don’t get stuck in what the possibilities are. Problems of today are think about what the future is that you’re trying to paint and what needs to be true to be able to achieve it. So if this is where I’m trying to go, what do I need to do in order to achieve that future? What needs to be true in order for me to achieve that future? In a sense, like will it into existence, will it into existence by knowing that there are blockers knowing there are things you have to climb over or adjust or blow up or do? But it’s about outlining for ourselves. Sort of. In the future, what needs to happen in order for us to achieve it? So if my goal is we go back to that one list like, my goal is to like, improve my customer experience, to make them less upset with me or in reduce my carrying costs. Like what needs to be true, nor for me to achieve that goal, think about that. Anytime you go down one of these paths, because there’s gonna be a lot of people in your organization that will be like, yeah, but yeah, but yeah. But yeah, but you gotta clear those out of the way and put yourself in a position where you can truly help them to be able to see the future that you’re painting and work toward that future. Uh. Second idea that is going to fit into this is this idea of jobs to be done. If you’ve ever run uh Red Clayton Christensen, he was a sort of famous Harvard professor. Just recently passed away that talks a lot about jobs, theory and disruptive innovation theory and modularity theory and so on. But jobs to be done is just sort of this idea that, like I’m sure you heard that nobody wants a three quarter inch hole, they or they don’t even to screw, they just want the boards fastened together. They’re trying to create a structure so the job to be done is create the structure. It’s not make the whole and put the screw in it and attach the two things like. That’s just a way you’re accomplishing that job to be done. So when we think about all the activities, the opportunities we have, I would encourage you to think about jobs to be done as a way to understand that the task being performed by your team internally and externally are just ways to accomplish an end. What is the end we’re trying to do and why and how do we enable a new future job? One is to be true in order for us to make that happen, and in this last idea I also have Clayton Christensen. Topic could go into a whole talk on this, but it’s disruptive innovation. This is just really the idea that like. Sometimes when you have these conversations, the things that people will tell you that they want are just incremental change on something they’re already doing, when in reality a disruption is much more significant than that. That’s has the opportunity to come to the process or the market. So everybody’s, it’s funny, I used to say everybody’s aware, like my kids don’t know what blockbuster is, they don’t know what the original DVD’s of Netflix were, right? But you know, many of us probably still remember Blockbuster was right. Like you asked, a person who went to blockbuster what they would like to see better in blockbuster, they might tell you like movie organization. I want one on my block or I want to be able to drop off at different times. They’ll tell you, like, different incremental ideas surrounding the blockbuster business model, but what they won’t tell you is, you know what? I want you to have a screen in your in your family room that can stream movies and never go to a blockbuster right? Like that, they will never. They won’t tell you that, right? They won’t. They might not go down. That sort of logical sinkhole, right? So disruptive innovation is about this idea that things that might enter the market might be perceived, perceived initially to be less feature complex or capable, but eventually sort of disrupts the established established capability or player. So AI has a facility to be able to make that make that a possibility for all of us. OK, so in this context, this is where we’re kind of getting to some of the best practices or things that we do differently. I wanna kind of draw a tension that exists in innovation. So imagine yourself as a company that has your own revenue opportunity, OK? Like you have market share, you’re a lumber company or blockbuster or whatever, OK? You know your revenue and then you have a competitor, let’s say it’s a blockbuster example, right? Like I’m blockbuster and I have family video. OK. Don’t you love it? Actually, you drive down the road and you see family videos that are now turned it on like completely obscure other stores you’re like, currently there’s no more family videos. Maybe there are, but like most of them are like something completely different now. So like, yeah, there’s a tug of war between these two companies. They’re competitive force that exists in that space between those two companies. Like what if my prices were different? Or what if I marketed different or what? But you know you’re you’re you’re ringling between like features of what you offer to your company and you’re trying to be more competitive. There is a space for AI in that spot. OK, so like there’s a space where AI in the competitive forces that exist in that type of war between you and your competitor 100% find faster responding to my sales to my customer, if I am better at my demand inventory, I will save operational savings, so be optimized in my revenue like those are things that just make you more competitive all up with your competitor and enable you to gather market share from them. So they’re circle strengths and your circle gets bigger. This is what we usually look for in like a lot of initial AI scenarios. And so those efficiencies move this direction, right? We want those efficiencies. This is good, right? But not but but like and. What we should also be looking for is what is the unharnessed opportunity that neither of us are achieving and it’s so sometimes it was talking with a person in a couple days ago and they’re like, well, this economy like no one is buying things that don’t have pain right. And and that 2 certain degree is true, right? Like if you don’t have pain, no pain, no gain like my wife’s a PT, and she will say that that’s not entirely true either. Like, you shouldn’t have pain working out like yes, but there’s still tension, right? Like I’m doing a longer run and I still have that pain in a sense. Uh, just no pain. You’re not. You’re probably not going to take action on. That’s just because we were respond to threats, right? I respond to a threat or respond to something that’s prevented me from achieving my like tactical near term goal, but realize that unharnessed future opportunities also a threat in a sense because it’s just a threat that sitting out there a little longer off in your journey but is also one that if you don’t respond to it is much more. Umm. Existential to your business. You. Asked the blockbuster guys like, you know, like, did you lose your business because you couldn’t set your pricing right with family video? Or did you lose your business because the market to completely shifted on you like to completely different distribution model, the things you were doing well that would be it, right, like they didn’t shift their market. So as you were thinking about the future pulling back to that like idea of what needs to be true, what needs to be true for us to execute on the mission of our business for the next 10 years. And that might mean just be more competitive with your competitor, or it might mean we’re seeing this business shift. This business is going to be very different in the next two or three years or five years because of this thing that’s happening within the market. How can we be the one that makes that happen to our market? How can we be the one that implements that change and creates the disruption versus response? The disruption, because I can tell you that responding to disruption has become something that is substantially more difficult now just because of how quickly technology influences our change. So all of that said, I’m gonna cover some ideas around what works and what doesn’t in some of those pieces of the conversation. So the first of these is business alignment. This may be like totally obvious to you on, but it hasn’t been obvious to everyone I’ve talked to. And this is to say that the companies that start with IT by itself trying to attack some isolated use cases are ones that can really struggle because they don’t have the relationship with the business to get real impact. So it just kind of goes unnoticed or feels like an interesting science experiment for a while, but doesn’t really show the real outcomes that the business is looking for. So those companies that really focused over here on it just kind of owning things, I’d say like a really good example of that is like like companies that have adopted M365 copilot and just kind of SAT night for the last five months. Umm trying to figure out if it’s beneficial or not to them. Umm, like those companies have really struggled, or ones that like their first IT use case was like I’m gonna go tack IT help desk you know not that IT help desk isn’t a great place to go apply AI it is especially if you have tools like a service now something that’s they’re already investing in that space you can start taking advantage of it tomorrow. Umm, but as you’re looking towards your overall journey, you need to figure out what impacts truly the mission of the business and the best companies, the ones that start with getting executive alignment as well as bottom up. And you’re applying those two things together to be able to say, what are my priorities look like? How does upskilling look like across my entire employee populace and how do I start a a journey of experimentation like against those priorities? Now how do I start down a road that enables me to be able to get that kind of outcome in a way that isn’t tied to just it doing it, but it’s tied to the business aligned attacking those opportunities. So business strategy alignment with AI, some of you may already have that today, kudos to you some you may not have really achieved that yet and this represents an opportunity. I’ve never seen an opportunity so significant where the business wants to have that conversation like in the past. You’re like, well, let’s have a digital transformation strategy or a digital being Enablement for your supply chain or whatever it is. It’s always been a little bit of an afterthought, like a difficult conversation, but AI, for whatever reason, is enabled that anable that spark sometimes what I’ve seen is that what comes out of those strategy sessions isn’t AI at all. It’s something completely like something else, right? It’s caused them to be able to optimize the part of the business they’re working in. I was talking to a company that was like they were doing like they were doing centralized scheduling of these people are going out to these pretty service calls and ended up being like moved to move to self scheduling. Like, let’s just get away from this idea of centralized scheduling and move to self scheduling and it’s just kind of wasn’t even really an AI problem on, but it was an opportunity for them to make a substantial change in the way that this is operated to become more efficient and then use AI to put some walls in efficiency around that to make them more effective than that process. So you may have seen this before. You know, this is actually idea of like understand those priorities in the context of categories that business and priorities, names of those values, descriptions, value categories, difficulties, ranking them. I would encourage you go after use cases that really do make that impact on business. Umm, try to avoid ones like as a first priority or ones that you put like executive focus behind that are just kind of pocket use cases that only a few people will see impact from. Like, look at ones that are actually gonna drive the impact, which is funny to say like you think that be obvious to everyone and maybe it is. But it’s also like a risk tolerance thing. Some companies that are like risk averse will not target where the big wins are, and they’ll just sort of not get anything. And well, then there’s just sort of sitting where they were in the beginning. So next piece of this is uh Co innovation, so coordination is really about seeing value in experimentation like enabling and experimentation culture within your organization. That isn’t about one effort failing or succeeding. Not that you shouldn’t have significant efforts that you apply energy to, and you’re evaluating whether or not they are successful or not. But what I have seen in organizations is like OK, we have picked this one use case and if this use case is successful, our entire AI efforts are like not worthwhile. Like, it’s like, that’s just not how it works. You know, like this is a tool in the toolbox, and if that tool works for certain use case, great. If it doesn’t, shift shift to another one. Focus on long game of establishing and capability, establishing a capability within your organization and building momentum versus the one and done versus this idea of like ohh just because this one hit a roadblock. We’re gonna, like, pause and wait six months and it is like it. It’s just, it’s just really, how do we describe this it it really sits in this idea of there’s not enough real understanding of the kind of momentum meaning to gain in innovation space. And that’s really what this is like. Don’t put all your eggs under one basket and expects that success to be the plus or minus associated with whether it’s successful or not. It should be your starting point. It should. It may be a big pursuit, but a join that to other things that so. For example, if you have a big demand inventory, supply chain forecasting opportunity that you’re working through, great hit it. That’s a huge area to get benefit from in conjunction with that, go figure out how people can get benefit from the user. Easier use case or M365 copilot or something else that’s going to provide a benefit to them that also sort of shows the different prongs of where people are getting benefit. I’ve seen some companies do really cool hackathons and such that are like enabling a broader team. OK, so uh, I’ll ask this question. Can this be a moment where we enable every person to be the best version of themselves? I am a person that believes, and I think the market in a high degree, believes that AI has the potential to enable and transform every job. There’s a gentleman that I really respect, Todd McLees. He has a skills framework where he talks quite a bit about the transformation of skills that are necessary in the AI company and those skills range from growth mindset to understanding how to delegate to an AI agent to thinking about creativity and different way and reigniting certain skills. This is a moment where we and every person in your business should be thinking about how do I think about the job transition that’s going to occur over the next 5 to 10 years and how I help people to perform 10 years, probably long. How do I help them to move that job in that direction that’s going to enable every person to be the best version of themselves if we actually care about people. This is this moment for us to be able to do that. So this is really this idea of scale engagement. It’s this this idea of how do I make the tent of people who are interested in excited about this broad enough and not make it a one time event where you get a bunch of excitement, but then people just sort of like you pick use case and everybody else just show left out to try, right? Like, how do I scale excitement and engagement across my organization and not just have a small AI team that everyone else just keeps going on about their everyday work right. Like yes, there are priority teams. Yes, there are priority of pursuits and they should be prioritized. The things that provide value usually have targets. You know, teams that are assigned to them, but also realize that this is a change that every person’s opportunity to perform work. And how do we enable all of them to be able to get that kind of opportunity? So that starts with executive buy in. Sometimes I think that people say it’s going to impact every job, but then they don’t act like it’s going to impact every job. If you really believe that this is going to impact every job, we have a responsibility to enable every person to be able to be educated and capable. As a results of leveraging AI, this is what’s going to transform much of our businesses as part of the new opportunities that exist. So how do we drive that scaled engagement? That’s challenges. Hackathons. Force multiplication, enabling everyone to start delegating to an AI agent so that will happen over time. I agree some things that copilot doesn’t do just aren’t good enough, right? Some things that does do are excellent. We need to help people to leverage and understand how to use tooling that’s coming out of the market. We need to be able to be skeptical about just because it so many tacked AI on a product doesn’t mean it’s actually an AI product like this is happening all the time now. It’s like, oh, my new AI features like, did you actually build an AI feature? You just call it AI, so there’s certain scenarios where like you need to be skeptical. You need to be discerning and enable them to have the skills to be able to do that and cage that broad group and scale and scale engagement. And this is really combined with the idea of follow through. So umm, what works and what doesn’t work in follow through is this idea of like ooh, I didn’t see immediate success. Umm I it’s just like ohh I am not sure that you have to follow through the most successful companies. I was just talk about a company I worked with. We were working with with a company that does travel management and first couple first project was like it was super like Super useful, Super successful they they got benefit from the ability for their travel agents to leverage like generative AI to help answer questions from their customers. He knew that wasn’t the end game, right? That was just sort of start in the sense like he created something that that like became a commodity later, like became a by situation and later on down the road. But then so. Well, it’s gonna take that to the next level. So like we know that like we’ve gone through this innovation cycle, we’ve seen the market reduce some new things. We’re gonna keep following through. We saw this with a scenario with demand forecasting like first one. Yeah, like we got somewhat there kept iterating and in the iterations got to the success that they really wanted to see. Don’t have cool feet that like or like have false expectations that like everything’s gonna be perfect all at once. It won’t like you have to have file through. You have to follow through on the swing. You have to have executive buy in that goes through this example of file. Through that we worked on was this autoquoting scenario 600 sales are up. Using it, we needed a lot of foul from for that sales team, especially the sales management to get them to use it, to build the new habit, to make sure that they like we’re actually using it. We tracked how many quotes are created through the auto quoting tool. Was a new skill. Some people liked it, some people didn’t like follow through file through file through, just like every new habit that you’re creating, you have to have the commitment. And if you don’t, you’re not going to see the success just because you’re gonna stop it too early. You’re gonna be like, oh, it didn’t quite get what I wanted. Like no, if you see the light at the end of the tunnel. If you see the what needs to be true, work toward that goal instead of like ohh shoot, we didn’t quite get there. Just gonna focus on something else like you have to be able to have file here. OK. I I mentioned this earlier, I think this is something that really again double down on which is this idea that we are under hyping AI upskilling like realize that like every employee is going to have to go through AI upscaling process or they’ll retire or whatever, right, like we want them to be able to be effective in the new economy, people coming out of school, they gonna have the easiest time because they already using it like ask my daughters. I didn’t look. People say, hey, you’re a technology personal cursory, your daughter’s using AI. Nope, I didn’t tell and all they just discovered it on their own, like they’re already using AI for various things. I had to, you know, dial it back and certain areas as a father and dial it up and other areas be like, whoa, cool. You did that. Our kids are already doing these things. The hardest part of the generation that change is going to be the existing workers who perform the existing jobs hardest person disrupt is yourself. That’s because you’re already doing something that’s successful. How do we shift and understand that that success that I’m doing now is not going to be successful in the future? We need to make it through that journey. So goes to that upscaling conversation. I was talking about earlier. No, not acting like AI is transformative. You either believe it or you don’t, man. And then when you, if you believe it better act on it. If you don’t believe it, fine. I’ll see you in five years and we’ll have a conversation about who is right. But if you believe AI is going to have an impact on upscaling, take action on AI upscaling growth mindset, meaning people have to have the understanding that what I do now is not what I’m going to do in the future, and that’s OK and that’s good. This sometimes easy for me because I’m in consulting. I know that my technology landscape changes every couple of years, but even for myself, sometimes that’s hard. Like I have habits of how I do things. Umm, this idea of AI Enablement skills. This isn’t just a technical skill. Don’t he? Tricked in this idea that like I’m gonna send everybody off to a boot camp or they gonna take this online class and all of sudden going to be AI experts like, no, this is a transition of diversity of skills. People who haven’t used creativity skills in a while, they haven’t learned how to delegate because they never been a manager. Now everybody’s manager because have AI agents, they delegate to like this idea of the skill shift the the understanding that I need a dedicated and substantial AI upscaling process is a critical thing for us to be thinking about. So building something complex? Realize so going into a new section that kind of just gives you some orientation when you are choosing to build something. OK, when you’re choosing to build something, most people think that this is what a ML system is. It’s a data scientist building an AI system or it’s a low code system building the AI system. Realize that that contains a lot of things, right? You’re AI systems are essentially apps, right? They are. They’re applications you’re building that contain data science capability, but also our diversity of other capabilities that fit in that picture. Realized that as you’re building this capability, your organization, you’re gonna move from experimentation to POC to pilot to production and in conjunction with that, you’re going to go through various maturities of that production environment and safety that needs to exist for different types of pursuits, which is why I always say, pick a heart problem like pick something that we’re going to get real benefit behind because we want to use this as a vehicle, not only to get that benefit, but also to show patterns that you will use in high capability environments. So in order to do that, you sort of derisk it, right? You move into a ideas of a proof of concept that moves into a minimum viable product and adds a few more capabilities and then moves into this idea of machine learning operations, which is essentially this idea that like once this system is actually operating a part of my business, I need a way to maintain, monitor updated, update the knowledge base, know how I manage it over time, automate deployment so you keep moving up a maturity curve. So like I’ve got a customer building an external chat experience for their end customers like 10s of thousands of end customers that we need to protect it from people trying to hack into it, trying to ask it an appropriate questions. Safety and security on the questions. It does answer that they’re actually right. The ability to fix it if we break it, like if I screw something up and I I like crowd striker, if I if I need to redeploy like how quickly can I do that? How quickly can recover myself? So this idea of building those right patterns into my environment, so there’s different phases that you think about there and it’s kind of A1 pager of that. You know when you think like, well, it first, I’m gonna do risk. I’m just gonna do a bullet POC right? Don’t read, but realize that that POC needs more work to be a pilot in an MVP. It needs more work to be a full MLOPS implementation. And it’s funny because we knew this and know it from the pre GPT world. You know the things that we did when people said, oh, yeah, OK, it’s $1,000,000. I’m going to build this Anand forecasting system like OK, I get it. It’s a big Pearl, big thing, you know, and this sometimes in this case, because you can do things so quickly, people forget about doing the rigorous stuff to bring it into production, and you need to make sure that you do that well, otherwise you’re gonna get jammed up later. When you think that there’s a you run at that problem. OK. Nothing to kind of think about Azure. You’re orienting yourself around what works and what doesn’t work, or like how it where success can be gained is understanding the kind of tool you’re building. Like what am I? What am I exactly kind of create here? Most of us aren’t building atomus AI systems. I’m not building a self driving car yet. Umm, you know, certainly people are. But think about the amount of engineering that goes into building an autonomous AI system. And it still has mistakes, right? Like it is a somewhere down the road kind of scenario for us where we’re starting with people is this idea of start with AI as a tool, this human controls and tasks that AI uses to automate simple subtasks. Right? It does something for me. I delegate to it. It performs the task, gives me information, then moving this idea that human controls and task will substantially help when invoked by the human, like they provide more of a consultative action in the context of that. Moving into this idea of collaborator, if you ever watch this thinking about Star Trek the other day, you’re thinking about some of the holodeck conversations or things of that sense. They are working with data like where you’re truly collaborating with a system that is providing as much to the process as you are, and you’re executing tasks in parallel. Those exist today. These are systems that people are already using to perform certain activities. Preparing a brief I’m preparing a financial package for meeting with a customer. This is a little bit more than a tool on. It may even be a little bit more than a consultant and maybe collaborating with you, provide providing recommendations back, but then also getting this idea of AI is expert. That is, even doing things that I can’t do that might be informing me. So know where your goal is. Work toward it. Know that you’re not gonna get to like, say 4 in your first project. You might just be starting here, which is totally OK, or maybe you’re starting here at one. Also totally OK, right? It’s leading you toward a journey which enables you to be able to provide more value for the organization, but nowhere your end game is so you can work backward from that to be able to make that possible. Cool admission. OK, so where we go from here? I asked this in the beginning the presentation and I’ll ask it again now what might drive these think about? And there’s other ones that I didn’t put up here because I didn’t wanna make the list. Was already a little long. I wanted it to be consumable. Realize these are examples, but what might drive these kinds of impacts in your organization really? Take that to heart. Apply the perspective of starting with why? Knowing what you’re trying to work backward to achieve, and understanding that your goal is to work prescriptively toward those in an incremental way, but then also to know how do I apply my team, my staff, my employees, my entire organization to be able to upscale and go toward these goals? How does my AI journey enable these goals? Field made true and I might say we’re a year and a half in. I’ll say I have the same conversation. In fact, I think probably do that. Like if we have the same conversation in one year’s time, how many of you will be a look at this list and say I have made, I’ve gained ground in XY and Z on this list because I’ve applied different change to the way that I think about AI in my organization. Have applied the eye to the mission of my business and in this line and this line and this lane, I’ve seen the success that it’s possible because I’ve done the hard work I’ve done the investment, I’ve performed the right exercise to be able to make me get there. So like why? Why do we think about this? What are we building like? You know, it’s interesting to think about this like as an organization that is been in AI for a long time. But what are we trying to create? I would think even think about this in yourselves. Like when I think about building AI competency and maintaining AI competency and doing so over time in the most exciting market, our goal at concurrency is to be the number one AI partner in applying any kind of opportunity and organization. We intend to be the number one AI partner and most trusted and most capable delivering the most value. That means different things and it means to us a diverse talent. It means we’re conversation partners with our customers. It means providing robust ROI calculations in conjunction with doing projects. It means investing internally to be better every day. And what’s happening within the market? It means being able to rapidly prototype and prove something early on to make sure we’re targeting the right things. It means picking the right use cases and building repeatability. This isn’t just about concurrency, this is something you can do as well in different lanes, right? So you also might say I want Mike talent inside or my organization that for every employee to be diverse AI talent and we wanna Co innovate with the business on driving outcomes and we want to know that when we do a project we have robust ROI calculations and we want to do, we don’t wanna think about from our D perspective where a business and our markets going. So we picked the right thing. So we want to rapidly prototype and fail fast or succeed fast, and we want to know where opportunities in our industry are the right things to focus on. Our goals are your goals in a sense, umm, and it’s an opportunity for us to to work together really well. So how would we help? And I I I hope that each of you take this to heart. If you don’t know what you want to do, we will help with envisioning and strategy. We will help you either. Go through some sessions to be able to identify the right use cases or even help you on the long term from a strategy perspective, we will have a solid use case. Together we will pick something to build and then we will help you scale it. We want to engage organizations that want to make a difference with AI and are going to commit to doing something otherwise thought, wasted charge time. Right. Because really the whole point is to gain an outcome. It’s to gain revenue, it’s to gain revenue or operational savings for organization. When you think about it, think about the same way like there’s this term. Let’s get real. Let’s not play like it’s the idea. Like, let’s make a difference in the world as a result of leveraging AI to be able to make it happen. And this is really where we think we can help and we would love to provide a lot of the same benefit benefit to you nice by the way, I love the data, the data thing. Thank you, Matthew Sutton. OK. So that that represents like a my my talk for today. But B, what I would love for you to do is first, this is something I love some feedback on. I think this is hopefully representing where I have seen the last year and a half go succeed or fail. I’d love to get your feedback, so fill out that form. I just want to know how much did you enjoy today? Was this something providing benefit to you? Should I have the same talk done? And just like I’m gonna just same type probably 15 other times, I’d love to know. Like what can I do better in this and what did you love about it? And also love to understand. Umm are any of these these types of ways we can help resonate with you? Because for me, there are ways we will love to engage in organization to help them see real value. So when you fill out that form, please select a way that we can help. You would love to catch on the flip side, don’t forget to kind of catch me on LinkedIn. Feel free to chat or also hit follow that newsletter because I think you’ll find some benefit from them. OK, cool. Lots of fun. Lots of fun stuff. I do have a little few moments for questions, so if you do have any questions, I’ll stick here for a few minutes. Otherwise, it was nice talking to everybody and really appreciate your time today, but if you have some questions, go ahead and drop in the chat. I’d be happy to hit him. No. OK, great. Alright, well really great talking to everybody today. Thank you for taking the time to spend with us and we’re looking forward to having some followed conversations about how we make this real for you to have a great afternoon. And thank you for spending time.