Introduction

I’m in my mid-fifties, with three decades of business consulting behind me — work that has taken me around the world — I´ve worked across process management, change management, end user training, knowledge management, and digital transformation; often associated with ERP programmes. I’ve always been drawn to what technology makes possible, and lately that curiosity has turned, with real intent, towards AI. Not because of the hype. Because of something more personal: a growing conviction that these tools don’t diminish professional experience — they can amplify it. Knowing what to do with a tool, and why, and when to/ when not to — that still takes learned experience. This blog is where I think that through out loud and share what I´m discovering, learning and creating along the way.

There's a photograph on my wall that captivates me. I took it at dawn, in difficult light, after getting up earlier than I wanted to. I know exactly what I did to get it — the decisions, the patience, the small adjustments that made the difference between a decent shot and one worth printing. It feels like mine.

I've been a photographer for most of my life – it sounds cliched, but ever since I was old enough to hold a camera – in later years exploring it professionally. It's the discipline that sits alongside my work, the thing I do that has nothing to do with clients or deliverables or project outcomes. Photography, for me, has always been about learning to see — really see — and then having the skill and the patience to capture what you've seen. The craft matters to me. It always has.

So when AI arrived in my editing software — quietly at first, then rather dominantly — I wasn't prepared for how it made me feel. I'd expected to be impressed. I was. I hadn't expected to feel unsettled. I was that too.

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It started with Luminar, an editing application — one of several serious alternatives to Adobe's Lightroom — and it has embraced AI more aggressively than most. Sky replacement. Automatic subject isolation. Tools that can relight a face, remove distracting elements, enhance textures, and add atmospheric effects that would have taken hours to achieve manually, if they were achievable at all.

The results, in the right hands, are remarkable. And that's exactly where the trouble started for me.

The first time I used one of these tools properly — replaced a flat, overcast sky with something more dramatic, relit a subject that was slightly underexposed — the output was better than what I'd captured. Noticeably better. And I sat there looking at it, genuinely uncertain how I felt. Because on one level, of course I liked what I saw. On another level, something troubled me.

The line had blurred, faster than I'd realised. There's a long and respectable tradition of post-processing in photography — from the darkroom techniques of Ansel Adams to the careful adjustments that any serious photographer makes in editing software today. Nobody serious argues that cropping or exposure correction compromises the integrity of a photograph. The question of where editing ends and fabrication begins is not new. But AI moved that line in ways that felt tangiably different. It wasn't adjusting what was there. It was, in some cases, replacing it.

And then the second thing happened, which troubled me more.

I started noticing people — non-photographers, people who had never particularly engaged with the craft — producing images with these tools that were, by any conventional measure, stunning. Images that would have required years of skill and experience to produce, generated in minutes. The tools had democratised something. Which is, in principle, a good thing. But it raised a question I found myself sitting with uncomfortably: if anyone can produce a technically accomplished, visually striking image with the right software, what exactly is the value of having spent years developing the eye, the technique, the patience?

I haven't resolved this. I want to be honest about that. There are photographers I respect who have drawn firm lines — who will use AI for noise reduction and sharpening but not for sky replacement or subject alteration, because the former enhances what was captured and the latter changes what was there. That distinction makes sense to me. I've found myself gravitating towards something similar, though I'm not sure I've settled on my own rules clearly enough yet.

What I've come to believe, though, is that the question of what AI can do is less interesting than the question of what you bring to it. Because here's what I've noticed: two people using the same AI editing tools on the same raw image will produce very different results. The person who has spent years learning to see — who understands light, composition, mood, the specific quality of a moment — will make different choices at every step. They'll know which enhancement serves the image and which one tips it into artifice. They'll know when to stop. They'll have a point of view that runs all the way through the work, even when some of that work is being done by an algorithm.

The person who hasn't developed that eye will have the same tools, but not the same judgement. And judgement, real human judgement, is not something you can install.

There's something here that connects directly to the broader argument I'm exploring through this blog — about experience, and what it's actually worth in a world where AI can replicate so much of what we thought required skill. In consulting, as in photography, the surface outputs are becoming easier to produce. A competent-looking deliverable, a polished-sounding recommendation, a visually striking image. The tools handle more of the execution than they used to.

But the deeper work — understanding what the problem really is, knowing what a good solution looks like, having the taste and the judgement to know the difference between something that merely looks right and something that actually is — that work doesn't get easier just because the tools get better. If anything, it becomes more important. Because when everyone has access to the same capabilities, what differentiates the work is the human talent behind it. The experience that shapes every decision, even the ones the algorithm is making.

Photography taught me that before consulting did, if I'm honest. The camera was always the easy part. Learning to see took years. AI hasn't changed that. It's just made it more obvious.

The tension I feel when I look at that edited image on my screen — the one with the better sky that I didn't actually photograph — I think that tension is worth keeping. It's a reminder that the tool serves the vision, not the other way around. And that having a vision worth serving still takes something that no software update is going to provide.