A Journey to Pathology 3.0: Gen(eration)AI

I grew up without a computer. When the ZX Spectrum finally landed in Yugoslavia sometime in the early eighties, I had a choice to make. And I got it completely wrong. I picked an electric guitar. Problem was, I had no talent.

For the next ten years, I lived without IT, convinced—just like with music—that if you didn’t start young, you’d never be any good. When I finally got my hands on a 286 in ’92—complete with DOS 5.0 and WordPerfect’s iconic blue screen—it felt like a second awakening. My late father was even more enthusiastic. By ’98, when I visited him, he proudly showed me that he could dismantle and reassemble a desktop PC blindfolded. I smiled at the time, never quite grasping the weight of that metaphor. I do now.

Over the last few months, I have been proselytising generative AI both in and out of work. I got hooked—ChatGPT is now part of my daily routine. I use it to test ideas, draft and refine content, and refine my thinking. But here’s the surprising part: while I expected my younger colleagues, friends, and even my kids to be prompt whisperers, I’ve noticed they tend to use it in a much more superficial way—quick queries, playful interactions, and surface-level prompts.

This got me thinking. Traditionally, new technologies have empowered the young—those who adapt quickly, learn new tools effortlessly, and grow up immersed in innovation, while many older professionals found themselves playing a constant game of catch-up. From early computing to the internet, smartphones, and social media, the digital revolution has often left the more experienced workforce struggling to keep pace, sometimes dismissed as “digital dinosaurs” by their younger counterparts. AI, however, flips the script. For the first time in history known to me, a breakthrough technology seems to give those with a few grey hairs an unexpected boost.

It is not just about learning how to use a new tool; it is about knowing what to ask and how to interpret the results. This is where the mileage brings the upper hand. Years of experience give an intuitive grasp of what “good” looks like, allowing to refine AI’s output with precision. Unlike their younger colleagues, who are still developing industry expertise, experienced professionals know how to frame problems, provide relevant context, iterate for relevance, and apply AI-generated information in a way that adds value—maximising AI’s potential rather than being overwhelmed by it.

Moreover, AI can act as an amplifier for accumulated knowledge. It allows experienced professionals to execute ideas faster, offload repetitive tasks, and focus on high-value strategic thinking. For those who spent decades sharpening their wizardry, AI is not a replacement—it is an enhancement, removing inefficiencies and helping them stay the MVP. I’ve seen colleagues in their 50s, 60s, and beyond who often embrace AI enthusiastically because they see it as a productivity booster. ?They are using AI to automate reports, develop consulting strategies, or even package their knowledge into digital products. They don’t expect AI to “think for them” but to gain more time to think. In that way, they can apply their expertise more effectively, mentor the next generation, and embark on new career ventures. AI, rather than rendering them obsolete, has given them a new competitive edge.

This reversal of the typical technological adoption curve may positively impact workplace dynamics and create a new kind of intergenerational collaboration.

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