AI Era Transformation: Is AI the End of IT (as we know it)

[00:00:00] Speaker A: Foreign. [00:00:11] Speaker B: Welcome to this week's coffee with Digital Trailblazers. Great to have you here this week. I'm going to give my usual two or three minutes for everybody to join. We got a quite a bit of sign up for this one, so clearly people are interested in the future it and what AI is or will not do to it. I'm not surprised that we all want to hear how leadership is going to change, how the different functions in IT is going to change how you're going to change your career. So very excited to see this. Hello Steve. Hi Chris. Chris is my supporter of the Week. I want to just thank Chris for just being such an outstanding partner as I think I announced a few times. I was scheduled to do a a keynote out in Atlanta next week and on AI governance and he is helping me reschedule that because of things that I'm going through personally. So I just want to thank Chris for just being such a strong friend and supporter and you know, go check out netwoven and give a date here. Chris. I think we're doing it. September 10th is our rescheduled date. For those of you in the Atlanta area, we'll be doing an AI Governance summit around then and I'm really excited for it. Of course that means I'm going to have to update my deck again because by the time September rolls around, everything we're talking about AI today will be completely obsolete or at least different. And we'll have some things to talk about. We'll see Martin and Joe. We'll see if that continues on that way. Hello Jay, welcome for joining and our conversation this week. AI era transformation is the AI the end of it as we know it. There are some who might suggest it is the end of it. Every four to six years there's some maverick in Harvard Business Review who comes up with some kind of article suggesting that it is done. And then of course we are like, well, not so fast. We still have some COBOL lying around, by the way. Yeah, we have some no code and low code and self service it. But you know what? We still need governance, we still need process, we still need architects and experts and none of it actually goes away. A lot of the services that we do tends to get commoditized, automated. We move up stack. I don't know how many IT departments have storage engineers anymore. If you have a data center, you might have a storage engineer, but we have more cloud engineers probably than storage engineers and network engineers combined. Our software developers are doing increasingly more stuff with automation. They've accepted and embraced low code technologies. Our testers are largely doing automated testing, continuous testing. So we've certainly gone quite a bit of distance in terms of what IT is doing and how it's functioning and how it's organized, particularly over the last five years as things like Agile and DevOps and again, low code cloud has all given us basically capabilities and technologies to do more, maybe with fewer people, but certainly with more expertise. And so now along comes AI and been writing about AI's impact on it for quite a bit. Over the last six months I've talked about AI's impact on software, AI's impact on requirements, on testing, on data governance, on IT operations, just to name a few. Have a whole series of articles on InfoWorld that talk about what's happening in these different disciplines and how AI is really changing the world in these different areas. And the one you all know about is around code, right? So latest research, 30% or so of code suggested by AI is Bing accepted by IT departments. And it's not saying much necessarily about the quality or the steps it takes to get AI code into production, but clearly there's some value there because we're putting 30% of it into production. We don't know how robust it is, we don't know if it's introducing tech debt yet, but we are hearing our leaders, our AI leaders who get to see everything. I'm talking about the Google leaders and the OpenAI leaders and the anthropic leaders coming out and saying there will not be coding or software development somewhere in the next three to five years. And CIO Magazine Online has an article, I think it was out yesterday, that boards are now putting pressure on CIOs to reduce staff in the belief or the reality that we need fewer people in IT because of AI. And so that's what's happening right now. AI era transformation Is this the. Is the AI? Is AI the end of it as we know it? Yes. I'm playing off the song by rem. It's the end of the World as We Know it. Don't know if that will really be the case, but I'm going to give the floor over to Martin first. He suggested this topic and I've broken this down, Martin, into three categories. Let's stick on the delivery, development, agile, low code side and just talk about like, you know, maybe look at this on a one to three year horizon. Let's not try to go too far out, you know, how is AI changing these disciplines and is it the end in your opinion or Is it just changing? Hello, Mark. [00:06:19] Speaker C: You know the, the world of it is always ending. Yeah. Who needs it? Yeah. If you're a CEO and you've seen all this AI and you're seeing AI generating code and everything else. Yeah. You got to, got to be thinking to yourself, well, I'm a CEO, why do I need a CIO anymore? Why do I need an IT group? But there again, we've had that in the past and we've had it with outsourcing and things like that. I don't need an IT department. I'll hire company X, Y or Z to do it for me. And we've seen through all of those cycles, things start to become clearer and we find out that we do need it. But the role of IT and what it does does change and evolve. Same as it does. Yeah. Right across the. I saw a great quote recently that said, yeah, you will have two types of people in the future. You will have unemployed people who don't use AI and employed people that do use AI. And I just thought that was fairly true. And it's becoming truer and truer. Regarding your question in terms of Development and DevOps and STLC and agile, I think that's going to continue to evolve. AI is fundamentally reshaping the IT landscape. So repetitive tasks, tasks that can easily be done, will actually continue to evolve. And how we're doing them, how we're using AI to generate a lot of these things, it's going to change that whole delivery aspect. But you still need it involved because it's role, if you think about it, is not just to generate code, it's more and more strategic, it's more and more how does it work with the business to identify how the business can be improved, what could change? And a lot of those higher level functions. Yeah, the lower level functions. Yeah. As you said. Yeah. You don't have a storage engine anymore and some point you're not going to have coders either. Yeah. But the ability to actually understand and work with the business to define how things could be improved and then let AI generate the solution I think is where we're going to end up. [00:08:40] Speaker B: I think that's a good vantage point and I think that's a good tee off to say, look, the reality is every time we've built a layer of technical capability, it means the entire skill set moves up stack in some way. We're doing things more robustly, we're doing things more efficiently, we're building better integrated connected applications, more modular ones. Certainly there's Going to be an opportunity for folks working in the software delivery angle to move on to the business side. So asking questions, what should we focus on? We can't do everything. What's going to deliver business value. That's certainly going to be an increased opportunity. But let's, let's go back down in the middle. Maybe, John, maybe you'll jump in on here and think about this. If I'm a software developer today and I don't want to jump onto the business side, I love development. I know two of my daughter's friends are going to university starting next year to study computer science and engineering. And I'm like, gee, what's the world going to look like for them when they're out in four years? You got a perspective on that, John? [00:09:48] Speaker A: Yeah, I think if you're in that role, I think a lot of like what you can do has just got accelerated. And so I think it's still going to be really important to have the really strong developers because I think the developers are going to be people that glue the different components and Lego blocks together. And AI could be used to help write a lot of the code. But if you want it to work right, that's where you need the people with a strong development skills. If you need to troubleshoot something, that's where you need the people with the strong development skills. And so I think the people in those roles, they're going to be able to do their jobs a lot faster, make a lot larger impact, and it's still absolutely critical. The other area that I see AI really increasing is the amount of testing that goes on because a lot of times people are, you're using technology that's developed outside the organization and it's often not entirely controlled by the organization and can change at any time. And so like having the stuff behave the way you want is you're going to need those technical people just making sure the system responds the way you want when you launch and as you go on making sure the system responds the way you want. [00:10:58] Speaker B: I'm glad you brought up testing because you know, in those situations, John, most companies dramatically have under invested in testing over the years, even though the tools have gotten fairly robust in terms of automation, handling test data sets, synthetic data, automated performance testing, scaling up and down infrastructure to do the automated performance testing, taking live data, feeding it into your performance test to make sure you do some realistic testing. There's all kinds of capability there. And one of the things that's been a big gap is just enough people in the IT Organization to be able to do this either with the scale or just the amount of money the CIO has to spend on testing. And so if you're involved, I think, you know, testing is a great area to think about going into. To Joanne, I'm sure you have an opinion on this one. [00:11:55] Speaker D: Yes, I do. You know, I look at it from a couple of different perspectives. To me, AI in the agentic form of AI will have an impact and generative AI as well, but a slightly different one. But overall I see this as a catalyst to the IT organization to become what is needed for a long time, a true impetus and catalyst to become a business unit. To me, this is a way that it becomes, not only has a seat at the table, but becomes a strategic organization to the business. And this is also what will take the CIO to a CEO role. Because you're going to have new roles being defined within IT that are somewhere around things like data translator. How do I. How should this data be interpreted? You're going to have a lot more people doing things like metadata introspection. So the roles will change, the actual developers and you know, testers and the environment around them. I think that's going to become more around things like testing. For the ethics of AI, is this the right thing to do? This is a really good opportunity for people to upskill themselves in ways that they never imagined would be an IT role. Because the maintenance of storage and keeping the lights on and all of the things that are cost center driven in IT will be handled by agents as soon as they are trusted. So to the point about testing, yes, test more because that's the only way you're going to develop that trust is constant reuse and constant refinement. But that's the level of testing that I think will happen. I think a lot of folks that I speak to in it, particularly within the organization, who are, who were used to be called programmers and developers and operators, are now taking on significantly more valuable responsibility in determining what's what and letting the AI do the sort of grunt work, if you will. [00:14:16] Speaker B: I love this idea of IT becoming a business unit. Joanne. I think we're gonna have to have another topic on that is, which is why, why I wrote this down and, and the reason I think it's interesting in this scope is that when you look at where agents are being built by the vendors and in their platforms, they're largely, you know, workflow, departmental oriented problems, you know, either in marketing or finance, human resources and things like that. When you start getting into Industry workflows, I would put those as emerging but likely to come. And when you start putting them into customer facing and you know, not just end user employee, but customer facing capabilities, you know, moving from apps to agents and where you're going to deliver real business value to your customers, I still think that's an emerging area. I don't think companies have figured out their agents in that space. I mean, if they did, you know, we probably would have seen Amazon with a buying agent out there. It's not even there yet. So there's still a lot of Runway there. When we start talking customer facing. Do you have an opinion on that before we go to Joe? Yeah. [00:15:31] Speaker D: Oh, sorry. Yeah, just, just quickly, you know, there's a bunch of startups that are doing exactly what you're discussing. But I just want to take a step back for one reason and there's a lot of confusion about what an agent is and what an AI agent is. And I think we have to be very careful in our definitions because agents that are designed ultimately to run autonomously are not the same as AI agents. Meaning you're using AI and quote unquote identifying a task. You know, these are agentic agents, literally sense, detect, learn and act autonomously. They're designed for that capability that is still emerging. I 100 agree. I think what a lot of companies are doing now and trying to figure out is what part of the, I hate to use the word maturity curve, but what part of the maturity curve they want to aim for as opposed to where they are. And that's one of the, one of the issues around AI in particular. But yeah, the customer focused one, you know, little shout out to Mayank meta for be heard. They're in the process of doing customer facing stuff and it's very interesting in the way that they're using agentic AI, but also in the way their customers are reacting to it because they're driving true business value right at the get go. And I think a lot of companies could take a lesson in what are you really trying to accomplish with these agents, AI agents or agentic AI? Are you looking for efficiency? Are you looking for a better customer experience? And how are you really going to measure that? So there's a lot that's still in flux. One could call that nascent or one could call that emerging. [00:17:31] Speaker B: Interesting. I'm really interested to hear Joe's opinion on this. Before there, I want to give a shout out in the comments to Sandy McCarron, good friend, colleague, partner of Star CIO and who has Been on here before. She says her organization, Sapie partner is developing a workshop 3 day AI design sprint with a 24 hour MVP. Very interesting. And she also says ask this question. I think it's relevant to this. Joe, what does Human in the Loop look like? Does it increase when we talk about the end to end delivery life cycle and then what happens when you're high when your competitor hires that person. So Joe, welcome to the floor talking about AI. Is it the end of it as we know it? What are your thoughts around this today? [00:18:22] Speaker E: So I'm going to answer your question in a short and concise yes. And I want to introduce a new term into the conversation. Evolution. We are moving forward as the IT specialist from the days, you know, I think back to the days when you wrote an assembly and it took a lot of time. Once we introduced compilers, we were able to have higher level languages. Now we have interpreters that generate code. Now we have AI that can write code. But all along the way this was a natural progression of capabilities. It was not the end of programming. We're always going to have to build applications, build workflows. The caveat here, and it comes back to your comment about Human in the Loop. The caveat is that when we turn these engines loose on fixing up the company, making it run faster, better, smarter, more efficiently, it may sub optimize. And by that I mean leaving it to an individual to use tools to automate their process might be in the old adage, paving the cow path. Where is the vision that is a broader perspective across the organization that typically the CIO has today to understand how the different functions across the organization interrelate and interplay and how do we streamline that. And I think Joanne's point was very cogent. And you've heard me say more than once that in my role as CIO I often said we were BT business technology because the B comes before the T. I think it's more true today than ever with AI. We have to focus on how does it accelerate the business, how does it deliver more value to our customers, to our clients, how does it make us run smarter and faster? That's really the future role and the future role of the cio. [00:20:26] Speaker B: Thank you, Joe. You know, I put this comment sort of bridging up to your thought, how, you know, computing languages have evolved in their sophistication and simplicity of vernacular, available of libraries, APIs as services. We've gone from assembly code up through Java low code and now the new language might just be prompts the adage, you get what you pay for. Maybe the adage here is you get what you ask for. If I asked you to write some code, to do something, something, and I'm not specific about my requirements, my acceptance criteria, my non functional requirements, my security considerations, who the end user is, what their real objective is in trying to accomplish this. That same concept probably has dozens, if not hundreds of prompts, and probably only a handful of them are the right ones to be asking for what you're really looking for. Maybe we won't be coding, but maybe we'll, you know, maybe English and other languages is the new prompt. But, you know, I tried an experiment this week, Joe, and I gave ChatGPT a pretty high level request. I essentially told it, I'm trying to build this app, write out a CSV for me with all the features and user stories, group them into an MVP release and a release 1.1 and develop a dashboard that illustrates the features and when they're going to deploy. I kid you not, it gave me six very broad, boring features. I didn't give it enough detail to really fill this out and give me a full end to end application. So, you know, if I really want something that's potentially a prototype or a pilot, I'm gonna have to spend a lot of time going and investing in my prompt. And I probably could get it there, or I might have to get it there in bits and pieces and then assemble it myself. But I am still building an app. It's just, you know, the approach and the tools I'm using are different. [00:22:49] Speaker E: I think that's exactly right. And it's also, you were very focused on a specific app. Remember that the function of the technology leadership is to help take the entire company forward. And so my fear is, as we abdicate responsibility for building solutions to individuals throughout the organization, you lose that perspective of the overall functioning of the organization and the service to its customers. [00:23:20] Speaker B: Sweet. So we'll go, Joanne, and then we'll switch gears to our IT operations functions. Go ahead, Joanne. [00:23:27] Speaker D: Sure. I, I just want to comment on your experience. This is where the rubber hits the road and the difference between the tools that you use, the, the AI tools that you use to develop, and also the difference between generative AI and agentic AI. If you want an outcome, use agentic. If you want discovery like you were getting the broad feature function, generative will do the job. But there are very specific classes of tools that are emerging and I think this, this is germane to the notion of IT and IT organization overall There are going to be new roles emerging in the ITO that will look at the various tasks, subtasks, subtasks of subtasks and start opining about which tools should be used for which purposes. For example, knowledge graphs, which are now very ok, everybody is looking at them. They're a very different mindset, but it's a mindset shift that is going to hit it faster than anything else. I'm not used to using these kinds of tools. Which is the best one for me to use? Is it cursor, is it this or is it that? It's, it's not about the name brand of the tool, it's the function of the tool. We now have so many more choices. And so I would say to you, if you wanted to run the same experiment in an anthropic, you'd get a different set of results. If you chose to take that same prompt without tweaking it and run it in a different tool set you would like Client, for example, you'd get a completely different set of results. So it's all, it's not about the prompting so much as the asking the question of the AI, which is the best tool set for me to use to ask the prompt and how would, how is, what is the best structure of that prompt that I should use? And to start paring it down. Because although AGI, the, the basic, you know, general information, general intelligence is still off in the future, the roots of it come from the large language models and that's part of where people get very frustrated and where the hiccups start to happen, where you get, you know, large management consulting firms reporting 85% of the projects fail. This is the root cause of it. So, you know, that's, I think one of the areas where it is going to expand its purview in a much more user friendly way. [00:26:16] Speaker B: We shall see. Joanne, I don't know about the user friendly part. I mean we, we've had to put in, you know, design thinking and figure out where that belongs into our process. You know, how do we, you know, you discussed last week, you know, getting technologists to go out to the factory floor and see how things are actually done. You know, we have a, we don't have a good history of, of doing that effectively, which goes back to where, where, where Martin was, you know, move up, stack a little bit, really understand end users, really understand workflow, really understand good design principles. I mean all those are just great ideas for people to go to. And I want to jump, I want to give you the first crack at this. Joanne we're going to talk now about its M Cloud computing end user compute. Before I go there, I'll just say that I did leave a link in the chat a little bit. Obsrinivas had asked what are the new roles that AI is going to enable. We brainstorm our list of them. 25 of them I think came out of this group at a previous coffee hour and I did share them in a blog post and I left the link in your comments. Sandy is saying creativity is the hardest thing to replace. Maybe I should have put that on there. Maybe we'll have another topic just on that because you know, was it Google announced the ability to make motion picture quality AI video now through AIs and trying to attack the entire workflow and cost structure of Hollywood. So we got to be careful. AI is going into everything and everything. It doesn't mean it's going to completely eradicate people getting involved with things. It just means our roles are going to be very different. Joanne Let me just do my quick break here and we'll jump into this. Folks, we are in our 130th episode of the Coffee with Digital Trailblazers. If you are here for the first time. We meet every week on Friday at 11am Eastern Time to talk everything from AI to Z. Everything that digital transformation leaders are facing in their jobs, in their technologies, in process, in governance and leadership, and sometimes in Life. Our next two episodes on the 13th we did an excellent episode last year around Celebrating Moms. We're going to do this year's episode on Celebrating Dads in Tech and the focus this time will be around improving work life for everyone. Just thought that would be good timing to introduce that concept here and then on the 20th, dovetailing off of my daughter graduating and her friends graduating, preparing grads for AI errors, opportunities and disruptions. And I think we're going to talk about design thinking here, Joanne. I think we're going to talk about making it into a business unit. I think we got two great topics to go off of for my July upcoming ones, but let's just jump into some nuts and bolts, right? So it used to be somewhere around 60 to 80% of it spend was in the run operations and everything. Just keeping the lights on. We have all the different phrases around it, all the infrastructure, all the network operation centers, all the help desk functions and slowly we've been shifting those dollars and more importantly our attention into the value added areas. We've been doing more with automation. We've been using More service provider is we've used cloud technologies and now AI is starting to take into that world. Things that we're automating are now being AI oriented and identified and things like that. I'm finding advertisements for agents that will do root cause analysis, that will do dependency mapping, that will in some cases actually create your cloud infrastructure for you based on a prompt. Joanne, how will ITSM cloud infrastructure and end user computing evolve in the AI era? [00:30:34] Speaker D: Well, that's a lot to parse. Thanks for that one Isaac on a Friday after a very long week. No, I'm just teasing. I think my rule of thumb and I may get smacked for this one own your AI because if you don't, someone else will and the idea of owning your AI will will definitely impact itsm. I think we're seeing some repatriation happen. I think the trend is going in that direction not only as a result of AI, but because of cyber security and also the cost of cloud. What does that mean for the organization or the individuals? I think we're going to see a resurgence in on prem data centers. I think colos are going to come back in a way that they're not extensions of cloud, that we're going to get back to business in some more realistic format than the esoteric perspective people apply to cloud. The idea of lift and shift is over and I think AI is the the key driver for that. So I would say some folks are going to end up doing two or three times their role for a short period of time until the workforce figures out where these new jobs are being created. What jobs have gone away as a result of AI both today and over the next 18 to 24 months. [00:32:16] Speaker B: Joanne I was doing a getting ready for that netwoven AI governance and updating a slide and had something along those lines as well. What's the next two years of transformation look like? And I called it multicloud 2.0 for some of the reasons that you're suggesting. I was a bear against multi cloud two to three years ago because of the added complexity that's required to do it. Virtually all organizations are multi cloud now, but now there's actually some good reasons to think about multi cloud beyond just ownership and cost and just the flexibility of moving payloads around and things like that. Owning your AI is becoming a major theme. I want to get Martin's viewpoint around this. Martin, controversial questions I'm your board leader. I come to you as CIO and say I need a two year plan where we're not going to have IT operations. I want the cost savings, whatever else you need to run our IT operation functions. Find really AI oriented, low cost service providers. Is that a realistic demand? [00:33:32] Speaker C: Well, it depends on the company. You know, typical consulting answer. [00:33:36] Speaker B: If you're. No, no, no, no, no. You're pretending whatever company you want, I'm your board leader. You're not going to say, well, it depends. [00:33:48] Speaker C: So I would, I would put this in a couple of different frames. It depends on the type of company we're talking about here. So if the company is a fairly modern company and has minimal legacy it, you know, then it's possible. Yes. You're automating a lot of things. AI is going to drive a lot of the manual tasks and everything like that, the provisioning, whatever else and it, and I'm kind of generalizing here, but it doesn't matter whether it's on prem or it's private cloud or it's public cloud or multiple multi cloud, whatever, you're going to get AI to orchestrate a lot of that stuff. Yeah. So that is all possible. It's all feasible. It's in a timely manner. We're already there in lots of ways. [00:34:34] Speaker B: However. [00:34:36] Speaker C: Most companies have a mass of legacy and a mass of cobalt and other things and as four hundreds and whatever else kicking around and trying to actually get rid of all of that in a. Yeah, a one or two year span without massive investments and massive redevelopment is not going to happen. So there you go. I'll give you a definitive. [00:35:03] Speaker B: So let's take the other extreme around this, Martin. You know, remember when cloud came out and you know there was one sort of vernacular around DevOps that said we don't need ops anymore. You know, development's going to run the infrastructure. You know, we can dial up and dial down what we need and we'll automate everything. You know, we'll put Terraform in there, we'll put CIC and E in there and you know, we'll be there as a public cloud, start adding services. [00:35:35] Speaker C: And the CSO said, OMG DEV is going to run. [00:35:39] Speaker B: No. Even before the CISO got involved, the reality was you can do all those things in dev except then you become an ops department, right? [00:35:52] Speaker C: Yeah. All you're doing is just moving the labels around. It's not actually achieving anything. [00:35:57] Speaker B: It doesn't. That's right. So you just move the responsibility. Maybe you shrunk the dollar a little bit, but it didn't eliminate. And so I'm wondering even those who don't have legacy and that's not A factor. And you're very cloud native, you're cloud native in your applications, you're very SaaS oriented, you're very AI forward or becoming an AI organization. Does IT operations completely disappear even in that situation? We're going to give John a chance to answer that, that I think IT. [00:36:36] Speaker A: Operations are never going to disappear. And I think the other thing is that the bar used to be like people had a technology bar before they could be adding technology to business. And with AI, it's made it so easy for people to use technology, to build technology, to integrate technology that I'm starting to see a lot of places like people, people now can do stuff that you used to have to be a developer. And so I just see the technology bar so much lower now that it is really going to have to step up their game on what they're doing from a governance perspective and from a higher leadership perspective because now we have business people that can actually write code on things. I did want to make a comment back to the thing about DevOps, which is the one thing I absolutely loved about DevOps was it lowered the silos between those two different groups and it got the development team talking to the operations team, which in the past, a lot of times they was just throwing stuff over the fence. But that was what I thought was really, really neat about DevOps in that movement was more of a cultural ship and taking those barriers down between two different things. The very last comment I was going to say is that I think so much work in IT has kind of been taken over by SaaS over the years. But, and, and now what I'm starting to see in all the SaaS companies is they're adding it to it. And so even if you're not adding, I mean, AI, so even if you're not adding AI to your company, if you're using third party software SaaS, they're adding AI to all of that stuff. And so your company is going to be infiltrated with AI one way or another, either by the business people or by the SaaS companies. [00:38:21] Speaker B: So let's, let's put you in that situation, John, your CTO, 200 people in your department and you know, let's say you're at the 30% sort of ops side of DevOps or IT ops, and five people come into your office who are on the OP side and say, how do I navigate my career through the AI era? What are the first three things you're thinking of that will likely be things your organization's going to need in IT operations going into the future. [00:38:57] Speaker A: Well, I think the thing that people need more than anything is a list of what's going on in their company. And so if we're talking about what they need or the skills wise, starting with what they need, I think the most important thing for it is to always be aware what the business is using, what the technology is running, who's providing that technology and what it's doing. And that to me is always one of the absolute most important things to have in a company. On the user side, I think with the rate of technology evolving, I think it's important that we have a company of continuous learners, people that are always trying to understand like what's the most important problem to be working on, what are my options, what are people doing, what is the new thing that people are doing or what's a tried and true tested thing and what are my options to solve problems. [00:39:45] Speaker B: So I got two, I got one is around asset management and how things are operating, just being able to assess and I got two on problem triage and really understanding what the right priorities to focus on. Do you have a third one before I go to Joanne and Martin? [00:40:00] Speaker A: I mean there's, it's hard to choose. Well, so in the IT space I think it's really important to have some standards on what, like some rules, regulations, standards on kind of what, what is important. And this could go so many ways, but if people don't have any guidelines or any boundaries, we're going to have the Wild West. And so I think it's really important for us as its to really have standards that everything has to adhere to so that we can say when something's brought in that's not treating customer data safely, that's potentially putting things at risk. We can say, hey, we have these standards for a reason. Let's make sure that, let's figure out a way to meet your business value, your business needs in a way that is safe for the business and complies with our standards. [00:40:48] Speaker B: Thank you, John. I'm going to put my AI hat on and think Joanne is going to talk about value and you know, maybe around being closer to your end users. And I'm going to guess Martin's going to talk about change management. But let's, let's see if I'm right about this. Go ahead Joanne. [00:41:07] Speaker D: You hit the nail on the head. You do need to be closer to your customer. You do need, you know, I think that there's, and I'm already hearing about this from questions that I'm getting Asked, how do I use AI to optimize my SaaS portfolio? Where can I deduplicate? Where can I get rid of stuff? Excuse me, are there AI tools or kid, can I build a GRC tool for with AI to help me get over the hurdle of how much duplicate, duplication, waste, whatever the three word acronym or phrase is about not including corruption, of course, because nobody was is going to talk about that in IT ops. But generally speaking, how AI is going to drive that part of the market and what that means to it. I mean, think about the cto or the CIO who's got 2800 SaaS apps to manage and wants to start paring it down not only for budgetary reasons, but just because, you know, two people using something that you're paying for on a monthly basis, that OP spend can be better spent as capex. So I think we're going to start a bit of a pendulum swing away from the OPEX argument to the capex argument as well. And while to John's point, we'll never not have it ops, those OPS jobs will take on a different form, or rather they might still be called ops, but it could be ops in a different way because we'll be looking at optimization, we'll be looking at how do we run things not in a cloud or across the three clouds in some way that start setting up the notion of quantum because it's not that far out, you know, and AI is pushing that side of the IT organization just as much as it's having an impact on applications and what the business needs. Can we get farther, faster? Because the other part of this is that our cost for infrastructure is going to continue to go up every time we're using AI because of the way we're in need of faster boards, more chips, all of the infrastructure that goes along with it. I mean there's a lot of, there's anything from building a server to using a cloud is going to change radically in the next little while because the costs are extraordinary to run AI in the cloud and people are very quickly realizing that the way in which AI is being tokenized and costed is not the same as cloud. Cloud is the add on to the AI or the AI. AI is the add on to the cloud. [00:44:16] Speaker B: Joanne, you kind of gave me a theme here that's me worth just amplifying a little bit. First is this notion of consolidation. We actually covered that at last week's coffee hour. I wrote a blog post around it. The link is in the chat if you want to do a recap. But then this entire theme of just continuous improvement, right. If you're one of those companies, Martin had suggested that hey, you're not ready to be completely human free because of your tech debt or your architecture or any number of reasons that are just reality for most organizations. You're in a loop of continuous improvement, right? Of finding ways to do things more efficiently. And quite frankly it's hard to find really good service providers who do that. Well, if you want to take something and say I'm not touching tier one support, I'm going to do a playbook for the next 18 months, go find somebody to do tier one support for you, sounds great, but if you have an infrastructure mess, if you have an application sprawl out there, you're going to need some people to look at this and say, you know what? Where am I starting? Right? Why am I investing in this change? And ask you all the right questions that suggest how to go out and improve things. I like this idea. Continuous improvement is a good focus of IT operation. And then your third area, Joanne, I don't think we're done with infrastructure disruption. Whether it's quantum or two things before that, you know, we, you know, our data centers are going to continue to look and our cloud's going to continue to look the way it does today. I just don't see that as a step wise improvement. There's just too much power being consumed, there's just too much compute being requested that we're going to see some seismic steps and we're going to need people in IT who understand the trade offs, the timing to make changes in their infrastructure model. Let me bring Martin in next. Go ahead Joanne. [00:46:12] Speaker D: Sure. I, sorry, I just want to finish with one thing. You're going to see the emergence of the AISP who is going to account for and accommodate for the extra compute on a lower price platform. The connectivity issues, latency is rearing its ugly head already. You know if you, if you use like a GPT 4.4.5 it takes longer to think. So think it translate that into the amount of compute that's going to be used. You're going to look at new chips. Not, not everyone will be able to inform to afford, you know, high quality Nvidia boards at 30000 a pop or better. So there will be this new version of MSP that will take what they have, improve it enough, just enough to get you over the hurdles. And to your point, Isaac, there's going to be two or three levels of disruption on the infrastructure side before Quantum, but if we don't think about Quantum now, we're going to get caught off guard later because it's a different, a completely different way of looking at the world. [00:47:25] Speaker B: Thank you, Joanne. We're going to go to Martin and then Heather. We're going to hear from you around cloud and infrastructure, but I want to talk about Org and leadership when you come on board. So we'll shift gears after Martin too. Hey, Martin. [00:47:37] Speaker C: So firstly, you need to recalibrate your AI because I was not going to talk about change management. [00:47:42] Speaker B: Oh no. Okay. [00:47:45] Speaker C: I'm actually going to talk about the last part of this question, which is end user computing, because we haven't really talked about that at all. And I think we're going to see dramatic changes in end user computing because why are we actually going to be having people defining some of these applications when you can give a, an AI tool to a business person, get them having a conversation with it and the AI, the agentic AI tool is going to build the application for them. So I want to ask that question to you, Isaac, put you on the spot and ask you to answer that one. [00:48:26] Speaker B: I think the view of the world through a screen that has, that's application oriented is going to change dramatically over the next five years. I think it's probably a five year horizon when you look at how enterprises change, you know, cycle out their infrastructure and the costs around it. But you know, I think end user computing may have the equivalent of an iPhone moment because I think you're right. I don't think clicking into apps and connecting to browser windows is going to be how we're working in the future when the main window of what we're looking for is either working with agents or prompting or even using voice. I think it's going to change a lot. So I agree with you. And what does that mean if you're into these devices and this is what you do? I think the devices will change, but I don't think the job function, specking out, learning how to deploy it, figuring out how to manage it, figuring out who gets what, how to configure it securely, make it easier, but I don't think it's going to completely disappear. I hope that answered your question, Martin, because it's a good one. Heather, Love to hear talk about cloud, but I want to shift gears and also talk about the org and how the role of the CIO is changing. Welcome to the floor, Heather. [00:49:54] Speaker F: Thank you. I want to just touch point on something that John mentioned earlier and that was some of the three things that he thought were so important. And talk about the priorities and understanding what the IT departments already have. I think taking what the business unit's needs are and connecting that to IT as a business unit, that's where the priorities will come. They'll bubble up that you can't. Just because we have this, whatever this is, doesn't mean that it's going to work for the business unit, doesn't mean it's going to have the result and the impact that is necessary for the business unit that's going to be using it. So let's not lose sight of what the business needs are. Also, there was some discussion in the comments section about the whole new jobs. And I think what people are often afraid of is that, you know, my, my job is going away and it's, you know, I'm not going to have this. New jobs doesn't mean bad, it just means different. And I think if we keep that perspective, the panic will be less and the ability to adjust will be greater. [00:51:04] Speaker B: I'm writing that quote down. New jobs doesn't mean bad. It means different. Okay, so now you're advising leadership around their recruiting strategy and their hiring strategy. You know, they're sort of confiding with you, Heather, about how the org is changing. What are you seeing around this in terms of how CIOs are thinking about hiring and who they're hiring for, and more importantly, how the org is going to change over the next two years because of AI. [00:51:36] Speaker F: You know, one of the biggest issues, irrespective of what department or type of company or industry, is the consolidation, having one person wear many hats. So to the extent that someone can bring into an organization a lot of perspective from either other roles that they had, creativity, innovation. Just because you're not in an innovation role doesn't mean you shouldn't bring innovation and being able to tell those, share those experiences and make them relate. I was talking to someone yesterday about a role that I was thinking of that I have to fill. And, and he came as a referral. And looking at his background, I said, you know what? This person really is not employable in this particular role. But because he came as a referral, I wanted to have the conversation. And as I was talking to him, I said, look at your role. Look at yourself rather as the generic potato chip package, black and white product X. Think about what the company needs from a bare minimum, you know, not how it's going to be applied, but it needs to do this. It needs to do that and then you can figure out how you can translate what people can do to bring that on. I think all too often people are saying, oh, I need someone who's in SaaS and they only look for SaaS salespeople or only look for cloud administrators. You got to look for people who have an array of skills that can bring those different perspectives to the role. And yes, the department will consolidate not because it's it, but because everyone's consolidating. You know, there's expense reduction and you know the, the salaries is going to be the hugest, one of the largest expense lines. So if you don't have that mindset, then you're not going to be able to find the one person that does what you need them to do. You just need to be open minded and look for that range of people. And I think to that end be mindful that sometimes more senior people that are usually impacted or more often impacted by ageism are excluded, but they're bringing all those different perspectives that could impact an organization positively. [00:53:55] Speaker B: Thank you, Heather. I also put a different quote down here. Look for becoming multi skilled and look for the multi skilled. I think that's just general good advice and related to that is wearing many hats, but also if you wear many hats, being able to collaborate with others and don't become a silo of knowledge. When I hear from John and Joe, I'm pulling you back on stage. We're talking about leadership. You're getting a seat at the table to tell us how you're refitting the IT organization in the AI era. John went off. John, do you have anything to add? [00:54:29] Speaker A: One of my favorite things to do is to look at what is the top programming language through the years and every year different programming language emerges as the most important one. And then you start looking at programming books from five years ago, 10 years ago and they're almost worthless. And so what I've quickly come to realize is that programming and technology and, and those skills, they're very short lived because they're always being replaced with something else. But you look at leadership books and business books from 50 years ago, 100 years ago, they're still very applicable. And so I think it's really important for people in the company to always, you want to have strong technology people, but having the business background and thinking like a business person is so critical. Trying to understand like, you know, what is the most important thing for the company, like how is my role in this, like what can I do to move the company forward? What can I move do to move, you know, my portion of the company's goals forward. I think the mixture of those skills are, are what is really, really important for it. And it's going to be more important going forward when we have AI, which makes it easier to do things with technology. [00:55:47] Speaker B: Thank you, John, for participating today. Joe, I'm dragging you up here. What are you doing as a CIO differently to prepare your org and to continue to prepare your org as the technology changes so quickly. [00:56:01] Speaker E: I'm not changing my discipline, Isaac. I have always and will continue to value most enthusiasm, excitement, interest, thirst for knowledge, willingness to learn, adaptability, flexibility, all the ease. We always talk about empathy and. [00:56:24] Speaker B: There. [00:56:25] Speaker E: Are so many personal qualities that I look for because I think to John's point, you know, knowledge has become a commodity. If I don't know how to do something in Excel, my computer can actually talk me through it. At this point, if I don't know enough about the business or my competitors, there's so much information that I can get publicly available and digest it through an AI engine. These things can be done. What you need is the drive, the personal excitement to get into these things. So I've always looked for that. I will continue to look for that. I think that's how the department evolves. Bring in fresh new talent that's excited and willing to learn. [00:57:12] Speaker B: Joanne, I'm guessing you wrote Eskild and I bolded it and now John mentioned Joe mentioned it. I'm. Are you going there? [00:57:19] Speaker D: I was going there and I think those skills are even more important today than they were when I wrote about them. But the other part of this is I think we're going to see, you know, CIOs are becoming more and more strategic and I think we're going to see a blending of corporate strategy with technical skills being applied. And it's the application of the technology that will be the standout skill. If you can connect the dots between A, B and P or F or whatever, you know, enumerator you want to use, it's that ability to not see so far in the future that you're a futuristic, but rather to see the end goal that may not be clearly defined today, but rather nuanced and shoot for it and put your steps in place from a very pragmatic but strategic role. I see a lot of CIOs picking up more and more, not so much MBA type stuff, but leadership skills that are around particular areas of interest to their industry or their, their organization. And there's an elevation process happening Heather may disagree with me, but I see a lot of CIOs that are trying to gear themselves up to become CEOs. [00:58:44] Speaker B: As if the job is disappearing. I'm going to give Martin the last word here. This is a great topic. Martin, is it? I'll give you the final word. Is AI the end of it as we know it and if it's not going to be the end, is that even possible where there'll always be an IT department? [00:59:04] Speaker C: It is not. The end of is the end of the beginning and now is the beginning of the next phase. AI is changing a lot about how we are doing things, but so many things have over the years. I've always pushed that it should become more and more strategic. It should be more and more looking at the business, not looking at the bits and bytes. And I think AI is just driving that to become even more true. We have to actually look at how it's going to drive the business forward, how all of these things are going to be used to deliver business value. [00:59:44] Speaker B: That's a really strong ending point. I'm hearing kind of a resounding theme of moving app stack. Not just understanding the business but but a lot of what vendors again deliver today are horizontal capabilities and where businesses that have been lagging in technology capabilities. Part of IT is just complexity of their industry, part of it is lagging industries that have under invested in. But if you look at the places where AI is going to be the most disruptive and also has the most potential impact, these are opportunities for all of us who are working in it. I'm speaking about health care, I'm speaking about manufacturing, I'm speaking about government, I'm speaking about higher education, even areas of retail. Are we going to bring an immersive experience back to in store type of capabilities and retail through ar VR AI experiences. So I'm pretty excited about the future of technology. I think that every time we've gotten a disruptive technology land on our shoes, we've asked this question is this the end of it as we know it? And the answer is yes. Move on. Time to do the next thing. Time to be innovative. Time to understand your end users. Time to continuously improve what you're doing so you can make room for the next new thing that will drive impact in your business. Folks, thank you for joining this week's coffee with digital trailblazers. Really fun conversation. Thank you Martin for introducing the topic. Joe, John, Heather, Joanne for joining us. Some great comments this week and questions. We'll be back next week. Our conversation on celebrating dags in Tech Improve Work Life for everyone. And our conversation on June 20, preparing grads for AI eras, opportunities and disruptions. Everybody have a great weekend. I'll see you here next week.