娇色导航

Keith Shaw Hi everybody.

Welcome to Global Tech Tales, where we talk with editors from around the world about the latest technology and leadership topics, and hear stories from IT leaders about what they are looking for. I'm Keith Shaw co hosting along with Matt Egan.

He is the global content and editorial director at Foundry, who is also representing the UK in this in this podcast this month, we are joined by Jens Dos. He is the editor in chief of 娇色导航Germany. Welcome everyone. Matt Egan Hello, Hello.

Glad to be here. Keith Shaw

All right, today we're going to be talking about how AI will be reshaping it, with groups already challenged to find resources and skills to support things like cloud automation and security. We now have generative AI as the next big game changer.

So this is requiring IT leaders to think about staffing processes and how much closer it works with the business and whatever else is thrown their way.

Add to this an increasing number of IT leaders that are getting burned out, and it's a recipe for a lot of stress for the IT group. So we're going to start, as always on this show, with some statistics.

I've got like six different stats here, so we're going to run through these as quickly as I can. A march. 2025, report by the American Management Association found that many employees, 57% said that they are not keeping up in AI. Less than half.

49% have received training in AI in avix. 2024, it Trends report, shortage of skilled workers is the number one challenge, and as a result, 24% more IT teams are planning automation, and 96% are already using AI or machine learning tools.

A data strike survey said that 54% of IT leaders say that resource shortages are a major issue in managing modern data architecture and ISC reports, almost 60% of cybersecurity professionals say that skill gaps are significantly impairing their ability to secure organizations. Couple more stats here.

A census wide Red Hat survey found that 80% of IT leaders report an AI skills gap shortage, even as AI and cloud investment grows and a 2025 Nash square digital leadership report global digital leaders say that they expect to stay at one company for an average of only 3.3 years, representing that burnout.

So with all of these stats in there, you know, how are IT departments that you talk with dealing with the lack of skills across the organization? Jens, let's start with you Jens Dos

Many companies already explored AI in some way, shape or form. So they are kind of banking on this when it comes to Gen AI and agentic AI, and they have a general skill and experience foundation they can build upon.

Others are just re skilling their staff, like career changes from the business side, for example, as a viable option.

Or another solution we see is incubators and subsidiaries dedicated to AI initiatives or tech initiatives that are somewhat disconnected from the rest of the company and therefore can present themselves more attractive for new talent and restuff in that way. Matt Egan Yeah.

So I'd build on everything says, like, completely. I think I might expand it slightly and say that the growth, the rapid growth of AI, is impacting organizations in two different ways. From a skills perspective, everything's spoken about, right, which is directly.

So, you know, even if agents can take on roles currently being done by humans, who's going to manage the agents, right?

And then there's the there's the idea of, kind of how we grow and build ideas, like Jen says some people, it's like training at every level of the organization with with a leader who's dedicated to it.

Other places, let's set up an AI group and like and like, kind of incubating things, all of that good stuff, right? Keith, in your own conversation with Mark Benioff, he hit on this sales force is retraining customer service staff to manage agents in the customer service space, right?

But then there's also the indirect impact, which we've talked about a lot, which is building the AI ready organization, which is having a knock on effect in terms of infrastructure, cybersecurity, data analysis. That means different approaches that require different skills from what organizations have today.

And with all of this, I see organizations handling these issues in wildly different ways. There is the from a pure AI perspective, there is this idea of some combination of training and enablement for all staff, plus hiring dedicated leaders to drive forward change.

But then in other roles, it's often it's kind of hire and train just as hard as you can, because no one has a perfect scenario, and there's a lot of on the job training that has to happen. Keith Shaw Yeah, yeah.

I'm wondering if there's a balance between, you know, companies that are just going into automation and agentic AI as a way to deal with the skills gap, but it feels like that, that that would then lead to a skills gap on its own for the people that maybe have to manage that AI, and they're not ready yet either.

So it does seem to strike this weird balance. Matt Egan

I think, I think that the the idea of automation solving the problems of the organization, is arguably more conceptual. Than real in most cases.

So I'm seeing increased acceptance that one of the biggest routes to return on investment with AI is in exactly that area we talked about this before, like making operations, including IT support significantly, if not exponentially, faster and more efficient by layering over AI with human oversight, let the software and the compute take the strain of the first pass for the vast volume of activity so that a human can be inserted when needed most at either the strategic level or when a mission critical problem needs to be solved, waiting, not fixing problems.

I think that's kind of conceptually, an idea that a lot of organizations are hooked on, but I think the reality of making it happen is challenging from a skills perspective. I don't know, Jens, if, if that's been your experience. Jens Dos Yeah, absolutely.

The same thing here. Nothing to add, frankly. Keith Shaw

All right, so, so, you know, another question I had was, was, does it need to rethink that their processes and more quickly adapt automation within their groups? So it's not just about staffing, but it's also about some of the processes.

For example, there was a story I think I read it on cio.com where there was a forester study that showed that productivity losses from IT related delays can cost between 1.5 million and 3 million per 1000 employees, and most of this is basically due to waiting for like IT support desk and ticket issues and things like that.

So if automatic agents, or, you know, AI agents can can speed up the IT help desk ticketing process, which has been around for probably what 1015, 20 years now, you know is that something that they can think of to improve the losses that that they might get from waiting for these things to be to solve what are you hearing about that?

Should that is that something that's a pipe dream or do it, organizations need to re look at their processes. Jens Dos

I think they are actually re looking at their processes already, because, like first and second level support in it is already mostly automated till you have till you speak to actual human and everything beyond that, I think agentic AI can tackle more like to solve more complex tasks and to offload The menial Standard Work from the IT team.

So automating, the classic automation of processes, they are doing that, and they are doing it quite well, because operational excellence is on the top of every it agenda in every company. So they kind of have to, I think the problem there is more cultural and less technical.

But Matt, what's your point of view? Matt Egan Very, very similar.

I think this is one area where we are starting to see a real impact, which is, I mean, you can compare it to medical triage, or even, like, heuristic security, which was a big, you know, big term, sort of 1015, years ago, where, like, instead of every case being treated in exactly the same way by a human being.

Start off with you take that first pass, and lots of problems can be solved using automation, before you get to the piece where you need a human to be involved.

I was talking to someone recently where which familiar to us actually from our professional lives, where they gone through a big migration project, which meant lots of end users had problems.

But like the problems ranged from a mission critical member of staff not being able to get online at all to some people who weren't able to, like do some sort of fairly trivial things.

But the ticketing system they had in place treated everything with the same level of complexity.

And actually it was really straightforward to overlay a level of algorithmic triage that meant all of a sudden you went to really important problems first with a human and other things could be fixed anymore.

Like that sort of thing is starting to happen, I think, and it does have a real kind of ROI. It might not be the most exciting use of the technology, but it is kind of having an impact. Jens Dos

I think it is learning from customer service in a way, because the the AI can run a sentiment analysis on the ticket itself and and point it to the right department or to the right person in the first place, so you don't have the mission critical person not being able to get online.

So I think that there, that's quite a movement there, even though it's not that exciting. Keith Shaw

Do you see a lot of companies that are that are doing this within their IT groups? Or are they still in that pilot phase, maybe? Or, you know, have they? Have they actually deployed these processes in their own companies? Yet, Jens Dos

my experience, they are in the piloting phase still, but are close to deployment because, I mean, it's basically classic automation with AI on top so they know how how to do it, and they have use cases, as I said, from customer services, which they can build upon.

Matt Egan Yeah, same.

It. Not, I think we're in that interesting point where there's been, there's the great big conceptual ideas of how we're going to rethink our whole organization using AI, and we're going to need to rebuild the infrastructure to do it. And then there's the more tactical.

Let's just do things more quickly. This is a real sweet spot thing. So it's funny, because, like, even two or three months ago, no one was talking about it, and now a lot of people are talking about and it's incremental as well, right?

You can start to introduce levels of this and quickly test and accelerate. So I do think, yeah, it's, it's, I would agree with Jens, in my experience, it's, it's, lots and lots of organizations are doing some version of this.

Not everybody's got the case study they want to take to market and shout about. But it's, it's happening, Keith Shaw

Right and that leads me to another question, where? And then we've talked about this on the show before. So as generative AI gets deployed across enterprises, it groups find themselves competing with other lines of businesses, especially when it comes to AI related projects.

So it's almost like, who gets the priority? I think we've referred to it sometimes as the cobbler stepchild, no, what is it? The cobbler step Oh, man, I'm gonna mess this up. Matt Egan

Yeah, yeah, Keith Shaw Right, right.

So it is always working with the other groups. So, you know, even Jens, you mentioned like that, you know, they're starting to do this with customer service. I would imagine that the customer service would get automated first and then, and then it would go it second.

But also customer service, though, is external facing, and what I'm hearing is that they're doing a lot of internal projects, first with AI, just in case a hallucination happens or something like that. So are you seeing it getting priority on some of these projects? Jens Dos

I so if we have to make this distinction, but between IT and business. That's a topic for for another time, but if we have to, I think the lines of business get always the priority, because in my experience, they are the ones who do the business.

They are the ones where the problems they know, where the problems in the business lie, that can be solved so they affect the bottom line, Keith Shaw

The businesses that can make money, yeah, I would say money probably takes, takes priority. Matt Egan

Well, something we, you know, we often say about our own organization, right? It, it's very rare an organization has a problem that can't be solved by more revenue.

But I think, but I think, you know, just, just adding to what Jens was saying, I do think this is all very organization dependent, and it speaks a dichotomy we've discussed a lot on this show, which is the idea of AI inside versus AI outside.

Ai inside being existing processes internal. Do it faster, do it cheaper. Use AI to make that happen. Ai outside, which is like rethinking products and services and really kind of building things from the ground up with AI.

And I think, like, what you're starting to see that is maybe a little bit of a change is, and I completely take Jen's point, right. I don't think every organization has this real, sort of hard distinction between IT and the business.

But I do think, like one of the things that's starting to change is certainly at the strategic level, it is seen as a business enabler and maybe a revenue driver, as much as it is a support function.

And that means it is both a cost center and a service center for the real business, but also a strategic partner and an enabler for the core business. That is not a new thing, right?

It's why we've got CIOs, it's why we've got CTOs, and it's why, on the other hand, we have IT directors. But I think AI is accelerating that, because it's kind of throwing in front, up in the air, and creating possibilities that only it can make happen.

So maybe even that line between line of business and it is, in some cases, getting blurred a little bit. Keith Shaw

And Jens, I think before the show, we talked about about how you were finding that IT leaders are now finding themselves with more one to one interactions correct, and so that requires some new skills that maybe they weren't using before. Jens Dos

Yeah, it's a constant change, like an AI, or the influx of Gen AI in every corner of the daily life, made it tangible like for everyone.

So it's not in the basement, it's on every screen of everyone in the company, which puts CIOs in the position where they either can use like the momentum and align and weave it into the business even more, make it a business partner and a valued partner.

But the caveats are restrictions like regulatory security or the good old German angst that prevents the the employees to to to use it to its fullest, because it's sensitive data, right?

So they have to be quick and and provide a solution that's that's similar to, like the the open source, open Internet one and not be a killjoy, so to speak, not to take the fun of it.

And secondly, when it is more approachable, it's also more vulnerable, and it has to do things quick. So. They have to get from 100% approach to maybe, let's deploy quickly and just 80% to solve a problem and not build for eternity.

So maybe the solution we built today is obsolete in a month or a year.

So this connection of it to solutions being like Everlast has to change, and the business also has to recognize that if they have a question regarding this new, new tech technology, it might not have satisfactory answer yet, but they will get to you.

And this expectation management and this management of how it approaches problems for the business and talks to the business is basically constant change management for the 娇色导航in the coming years. In my opinion, Matt Egan Yeah, definitely.

I think expectation management is a brilliant phrase. Jens, I applaud you for doing that in your second language, because, because you're exactly right. Like, conceptually, business leaders can see potential and opportunity around AI, but there's not that many use cases where this is happening successfully.

So they the it. People have to somehow make it reality. And then we talked about this at the beginning, right? Keith, like the knock on effect.

So yeah, sure, we want to run a process that's going to change the way we do things, and it's going to, you know, save us all this time, maybe money, okay, but the infrastructure needs to be right to do it. We might need, we talked about this previously.

We might need to repatriate from from public cloud in order to do this, which means we've got to find data center staff. We don't have them like we we're going to increase our security risks, or, like Jens was talking about privacy issues exponentially.

So we need staff to who can help us mitigate those risks, kind of thing. And I think one of the skills IT leaders are, CIOs, pretty much have this, but they're having to develop even more, is the ability to kind of give that news, that bad news, right?

Yeah, gosh, we can do what you're talking about. Can't do it today. You got to figure it out.

It's going to take a little while, and it's going to cost you in these areas that you haven't even thought about, that's that's quite a challenging skill set to develop and maintain, I think, Keith Shaw

Right And the acceleration of this technology, you've never seen anything as fast as AI and generative AI take off, right?

I mean, we've, we've all been through different technology shifts and but it never seemed to be that, you know, moving at the speed that it's, that it's moving now, right? Matt Egan

Yeah, I think so, yeah. Go on. Jens Dos

It's, it's, so I heard it called, be called exponential growth. And this is the first in the industry, because if you deploy a new ERP like SAP or something, you can take your few years, right?

If you don't act now in AI, and if you don't grow exponentially like AI does because it's feeding itself all the time, you just get thrown out of the curve. That's just the reality. Yeah. Keith Shaw

I mean, there's also the hype expectations too. And so does it have to take that role of maybe tempering the hype, or at least bringing in a dose of reality? Matt Egan

But it's both, you know, to be an enabler, you have to like in the most positive sense. You've got to facilitate the ability to do the conceptual ideas, whilst at the same time, you know, I talk about this all the time, right?

Like nobody's talking about sustainability, like everybody's talking about throwing all of these new computational projects out there, like, and then maybe quantum will solve it, maybe like, but in the in the intervening time, hey, we'll just keep burning all this energy, like, to do what like.

And from an, from a 娇色导航perspective, that means, like, money, like, you've got to run this, this, these projects, and it also means skills, as we're talking about today.

So I think it's, it's on the one, it's kind of, it's, it's learning the skills of being a yes, but person, yeah, we can do that. But this is, these are the things you've got to consider.

You know, data optimization alone is a big barrier to some of, some of these concepts. I think. Keith Shaw

You know, because of all of this, because of the acceleration, does this?

Do you think that this contributes to some of the reasons that we're now hearing about 娇色导航burnout at the leadership level, and that, you know, these these leaders, are only lasting about three and a half years.

I mean, this is now, I think, shorter than ever, and 娇色导航tenure is actually lower than CEO tenure. I was looking that up, and as of 2023 the average CEO lasts about seven years, somewhere between five and seven.

It just feels like is the added pressure of doing all of the AI projects, and then facing the skills gap and looking at your processes, looking at your infrastructure.

Do you think that's just adding up to, you know, this, this burnout, or is there some other reasons for this? Jens Dos

My opinion, this can be attributed to the general velocity technology is evolving. Yeah, today and the digital transformation and a lot of strategies changes based on new technology, right? Because three years back, no one was including Gen AI in any kind of strategy, and now they do.

And so the strategies change, and the CIOs, like hearts, are kind of connected to their strategy that they worked out. So I'm not surprised that we have so quick changes.

But there are also other examples for for example, the 娇色导航of the logistics company Kun and Nagel has been there for approximately 20 years and just catered and let the change the fundamental modernization in their it for 20 years and but this was because the leadership team and himself were committed to that.

They said, we want to do this, and we commit to that, and all the sides are on the same page. And I think this level of commitment is hard to do in these days because everything is changing so quickly. Matt Egan

Yeah, I think that's what I would say. It's I think there are two separate issues here.

One is, yeah, the level of kind of scrutiny and stress on the 娇色导航is probably at the highest level it's ever been, which isn't entirely a bad thing, by the way, but like, like. So it is. It is a very stressful role.

It reminds me of, like, the CMO role of over, you know, a few years ago, like, in the expectations are very high. You're working in a very changeable market. Like, there's going to be stress and pressure, but you can't divorce that from the external environment, right?

So it's also a time of economic instability. It's a time of geopolitical instability, and we're living through an acceleration in an industrial revolution. So like, you know, if the 10 years, 3.3 years, what's changed in that time? Probably everything right for a lot of organizations.

So it's unsurprising that the person at the beginning of it might not be the person that survived it, just for the fact that they were there at the beginning of it, right, like they'd been inside it, so they can't see what needs to happen externally.

But I think what's really interesting is, I do think we're at a very specific point in time, and it's one of those, you know, was, you know, that idea of, like, you know, people always underestimate how much is going to change in five years, but overestimate what's going to change in a year, like, I do wonder what tenure will look like for senior executives in it in maybe three or four years, when maybe, like, there's a bit more of a well trodden path around these things.

And it's not just everything gets thrown up in the air and see where it lands. Keith Shaw Yeah.

I mean, that's, well, if it's, if it's continues to be exponential growth, you never know if there's going to be a plateauing or at least a slowing down. Jens Dos

I think the longer tenure will be tied to how tightly business and IT are intertwined then, because they are merging together now, because they have to. And if they are indistinguishable, if business is it and vice versa?

The job of a 娇色导航or the new equivalent we might have, then of this role might be more entwined with the business itself and doesn't have to make like this much change management, this much integration, this much talking to the business, if business and IT are one and the same.

Keith Shaw

Well, I'm also wondering if that's it's if it's a case where, you know, it was in the, you know, in, to use your phrase, Jens, like they were in the basement for a while.

They were, they were hidden off, they were, they were just kind of maintaining the computers and all that. That was maybe, like, you know, 1020, years ago.

But as we pushed, you know, I think, you know, 娇色导航and computer world, for example, always pushed this idea that IT and business should work together. And yes, get a higher spotlight.

But with that spotlight comes more pressure, and maybe that reduces the tenure, you know, but that could just be, you know, me assuming these things. Matt Egan

I think there's definitely a level of that, like I say we, we've won for the CIOs to be a high profile strategic leader. High profile strategic leaders tend to have shorter tenure. Keith Shaw

All right, so you were at the point of the show now where we do our vote, and this, this question comes from Matt, this week or this month, and so you want to read it? Or do you want me to read it? Matt. Matt Egan You read it.

Let's, let's stick to the knowledge. Keith Shaw All right.

All right. So is finding the right skills to support an AI ready organization the biggest challenge that is facing IT leaders today, and as always, yes, no, or I guess you could say it depends. So Matt, since this is your question, I'll let you go first. Matt Egan

I always say it depends, and I will probably say that today, but I certainly think it is one of the biggest challenges.

And I think it's an underestimated challenge, honestly, because, again, I think people think about the AI skills challenge specifically related to jobs that are specifically around AI, when in fact, it is everybody in the organization.

And it is also the knock on effect on the wider it provision and infrastructure. So. So do you know what? I've changed my mind. Yes, it is the biggest challenge, Keith Shaw Okay, all right.

Jens, yes or no. Jens Dos

For the sake of argument, I gotta say no, because I think data is the more pressing challenge, because without data, you cannot have any kind of AI, and many companies still struggle with visibility, connecting all the data points.

They need to get AI running smoothly, still figuring out if they are using a data lake or data mesh or something else. So they need to get this base covered, and then they can worry about, Keith Shaw

You know, I was leaning towards Matt, but then Jens, you made an excellent point. So I'm going to lean towards Jens on this.

I think that there's a lot of companies that are still struggling with just that whole digital transformation process, and they're getting all of their data in a row and their ducks in a row.

So I think it's a little too early to make the skills the top priority, but it's probably in the top three, I would say.

So it's a little wishy washy on my end, but yeah, I still think that there's some some higher priorities, and you can never forget about security. Security is one of those, those top areas that they always have to be thinking about as well.

So all right, thanks everybody for this conversation again. Jens from from Germany, and Matt from the UK. Thank you. Matt Egan

Thanks for having us. Jens Dos Thanks, Keith.

Keith Shaw

All right, and we're going to be back next month to talk about how artificial intelligence is accept is affecting the pursuit of it careers.

So if you like this episode, be sure to add some comments below and check out our other Tech Talk shows, such as Today in Tech. 娇色导航Leadership Live, First Person and DEMO, if you are looking for product demonstrations, I'm Keith Shaw, thanks for watching.