Article
The Gap Between Professionals in the AI Era
A few days ago I interviewed a senior marketer. An experienced man, years of practice. I asked him about AI.
He said he barely uses it. Now and then he asks it how to set up something technical. Nothing more. He does not use it to simplify routine tasks. He had one bad experience with the output and decided he was too senior for it to add value when it is not perfect.
That caught my attention. This exact attitude can be observed across different fields, for example among some experienced programmers too.
I know the other side as well. Professionals who automate everything that can be automated. When they have something to do, the first thing that comes to mind is a question: can this be done through AI? And if it can, they build a tool for it. And they never click it by hand again, nor write that code by hand again.
Two senior people do the same work today, in the same field. But their working days look completely different. In ten years in e-commerce I have not seen such a difference.
That senior does the same task today, does it in a week, and does it in a year. Every time from the start. The other one solves it once, builds automation around it, and then comes back to it only when it needs tuning or fixing.
Both work equally hard. The difference is whether the result of the work becomes a foundation that the next day a layer is built upon, or whether a person does the same work from scratch every day.
I belong to the second group. I do nothing twice. What I solve once, I return to only as a built foundation on which I build something further.
And I enjoy it. For some it is hard to imagine how much. It is the same feeling I had when I learnt to program in primary school. Back then it absorbed me. Now, with AI and automation, I feel a similar flow.
I meet people, at interviews for instance, who do not have this at all. That senior rejected AI because the output was not perfect. But that is not how it works.
When it comes to a complex problem tied to the context of a company, the first version of the automation handles it at eighty, ninety per cent. That is not a failure. That is the start. It improves step by step.
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Summary
Common questions on this article's topic
Why do some experienced professionals reject AI?
Does AI automation have to be perfect to be worth it?
Is using AI a question of skill or of character?
How much can AI automation save a firm?
Why does the gap between firms in AI adoption widen?
Does AI automation need maintenance?
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