AI Leadership with Kieran Gilmurray: Navigating the Tech-Driven Future

AI leadership today demands more than just familiarity with emerging technologies—it requires bold decisions, strategic agility, and clear-eyed execution. And few speak more candidly about this transformation than Kieran Gilmurray, one of the UK’s most respected voices in digital transformation and AI strategy. 

Kieran Gilmurray doesn’t mince words. In a world where the pace of technological change is exponential, his message to leaders is clear: adapt fast, or fall behind. 

“You could end up, as I call it, a headless organisation,” Gilmurray says, describing a future where digital labour not only supports but runs the operational backbone of many enterprises. “Like Uber,” he adds, “where people are controlled by technology driving them, pointing in particular directions, allocating their next body of work.” 

The implications are both exhilarating and unnerving. 

When you talk to Gilmurray, you don’t get buzzwords. You get blunt force honesty. With decades of experience advising Fortune 500 companies, he’s become a go-to authority on how organizations can not only survive but lead in a world ruled by AI and automation.

He shares practical insights into how technology speakers like himself are helping companies gain a competitive edge through data analytics, agile thinking, and strategic foresight. This is a must-read roadmap for change for any business looking to thrive in the digital age. 

Let’s get straight to it: Are most executives genuinely ready for what AI demands of them, or are they bluffing? 

Gilmurray: Yeah, well they’re still learning. There are lots of businesses. I think there’s a great deal of FOMO out there where everybody believes everybody else has, you know, raced ahead—and some have and some haven’t. 

But it is a race, to a degree, to catch up and learn now. I think businesses are going to have to start looking at AI as a core part of the strategy. Now, we’re talking about narrow AI in general, retention models, analytic models, and the next best action. 

They will have to look at generative AI and see what part that plays in, you know, the construction of content, media, and business analysis. But they’ll also have to look at agentic AI, which is digital labour built on top of large language models that can take over many of the roles that particular staff members are doing.” 

Wait, you’re saying digital workers are already here? Is this “log in and watch it do the job” real? 

Gilmurray: So once you start looking at all of this, you’re going to be in a stage where we’re very soon going to have, you know, not just human labour, but a lot of digital labour built into a business. Now, nothing unusual there—Amazon factories are full of it. 

Lots of people have put agentic labour into, you know, workplaces already. But it leads to a different set of skills you need as a manager. How I manage a person is very different than how I manage a robot. 

How I manage, you know, a person plus a digital worker—and the performance metrics and the KPIs and the goals that I set, and the strategies that I put in place—they’re all new skills that people need to learn, including AI.” 

So, let’s say you’ve got bots doing the work. How does that change leadership? Who’s actually in control in that kind of setup? If tech’s running the show, who’s accountable when it screws up? Who’s left holding the bag when the bot breaks something? 

Gilmurray: Now if AI is going to take on, you know, a vast proportion of work, then you could end up—as I call it—a headless organisation, like Uber, which means, you know, people are controlled by, you know, technology that’s driving them, pointing in particular directions, allocating their next body of work. 

What does that mean as you transition, you know, to your workplace? What does it mean for your customers? 

If you look at Uber and some of the things that have come up against it over the last number of years, you know, have I decided policies that compensate for some of technology’s fragilities or when it goes wrong? 

If I’m DPD, you know, someone has went in, filled in a chatbot that I’ve used, you know, to try and reduce traffic or improve service, and if someone tells it to swear and it does, you know, how am I going to cope with all of these things and learn all of this tech and manage my staff?” 

This isn’t just a tech upgrade. This is a whole new playbook for leadership, right? 

Gilmurray: You know, there are so many questions that we are learning answers to. And not only that—if AI is going to do a lot of what we’re doing, then how do we develop, you know, the skills that AI can’t? The curiosity, the agility, the adaptability, the coaching, and the mentorship. 

You know, how do I learn the data, the AI skills themselves? How do I learn critical and analytical thinking? Where do I know to use technology decision insight? How do I cooperate or co-compete with my, you know, previous competitors, in cooperation or coopetition? 

If I want to open drawbridges and cooperate in an increasingly intelligent and digital world, you know? How do I plan for, you know, my new career or the new careers inside of businesses, like agentic AI architects, data strategists, you know, generative AI content engineers, agentic labour leaders?” 

And what about the C-suite? Are roles like CHRO and CTO starting to merge? 

Gilmurray: You know, how do I—maybe like a modern in the world—actually start to restructure my leadership team, so my Chief HR Officer is now, you know, taking on the role of a Chief Technology Officer as well? 

How do I get people excited about new roles like AI network optimisation engineer and everything that will come soon? 

So it shouldn’t scare people too much. They need change—enough motivation to move with the world and be very agile. But how do I let everybody know what I know? How do I get everybody excited? 

How do I build a change management program, a people strategy programme, while running myself to keep up to learn all these things? 

So, many businesses and business leaders have to adjust their learning, leadership model, and organization structure—who does the work, be it digital or human labour. 

And my biggest thing is to get excited about it and start now. So it’s not one thing, it’s a whole host of things—but that’s what makes life and business fun.” 

Are most companies still tracking what’s already happened, rather than predicting what’s coming next? 

Gilmurray: Yeah, well, you go back to what you can get from data analytics—and I say data analytics combined with, you know, AI and other automation tooling. So, I can get the what and the why at the most basic level. In other words, I can get descriptive and diagnostic analytics. You know, why are customers coming to us? How many customers do we have? Why are customers leaving? 

And that’s what I describe as the insight piece. And even knowing those numbers, I can make better decisions as to how many products I need to order, how many people I need to staff in my contact centre, or a whole host of things that, believe it or not, in this day and age—even the basics—some companies don’t have. 

Okay, so how do we get real foresight once we’ve got insight? How do we use data to shape the future? 

Gilmurray: But the real skill is: how do I get foresight? In other words, how do I get predictive analytics in place, which uses AI and machine learning and all sorts of different things like NL or neural networks to forecast what might happen in the future? 

In other words, if everything stays the way it is, what does the foresight look like in percentage over time? 

So now I’m making the decision fully aware of all of the impacts it will have going forward over the next period of time to a high degree of certainty. 

And then I can go, ‘Well, I’ve now got insight and predictive foresight, but how do I get prescriptive foresight?’ In other words, using AI models to determine, ‘Look, I want to end up over here. What do I need to do today to make those decisions?” 

So it’s not about chasing perfection. It’s about improving your odds, massively. 

Gilmurray: So, data analytics allows you insight and foresight. And if you make better decisions—and this is involved—you know, you need to be curious to look at these decisions. That’s a very human trait, not an AI trait. 

Then what we’re taught is that, you know, there’s a 95% correlation between better decision-making and better outcomes. 

So who wouldn’t want to make better business decisions every day that lead to a 95% success chance? The other 5% left over is for just uncertainty—that is always available. 

But rather than a 50/50 guesswork, I want insight and foresight, with brilliant people making great decisions every day that will result in a far higher likelihood of success. 

So why wouldn’t you want it? So how can businesses use analytics to get a competitive advantage? Get the foresight and the insight you need. Train people how to make better decisions. And better decisions lead to better business outcomes every time compared to anyone else.

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