Technology Tales

Not so fast: When tasks using AI may take more time and attention than you expect

Published on 29^th November 2025 Estimated Reading Time: 5 minutes

If you believed all the hype that surrounds AI, you might believe that all of us would out of work before we knew it. The truth is that the new technology is not that miraculous, especially when based on some experiences that I have been having. Firstly, there are deficiencies and then there will be new things that need doing as well as becoming possible for the first time.

PowerShell Scripting

One pertained to spinning up PowerShell scripts for doing code reviews of SAS programs submitted by a vendor to a client of mine. While all worked well for simple cases, I found that more complex tasks like finding the datasets using in code and comparing them against what is listed in the program headers became too complicated and probably needed a week of my time to get things in order, which was the amount of time that I did not have.

Picking out macro calls from code and comparing them against lists in the headers was more successful because the code situations were less variable. Other tasks were really handy, though, even if I would benefit from AI teaching me how to write PowerShell scripts by myself. That would give me more scope to critique the code that was being produced. Starting simple and progressing one step at a time would ensure sounder embedding of PowerShell commands in my memory.

Article Writing

It is all too tempting to get AI to write articles on subjects of your choosing for website content production. That which sounds like a labour-saving way to go can command a higher amount of attention than some realise. Sometimes, writing it all by yourself might be a better approach, one that I am using for this piece.

My workflow often involves these steps when AI is involved: assembly of the source material, conversion of source material into an article by one AI, fact checking of the same text by another AI and restructuring by that second AI with added links for those wanting to find out more. While human content production is reduced, the need for human oversight, along with fact and link checking, means that time is used in other ways.

In short, it is best not to rush this, as I found when assembling two articles on Canadian rail travel. You also need to watch how much content is being processed because that can both overwhelm human bandwidth and undermine human engagement. This is more than proofreading of what is produced; you need to know something about a given subject yourself too.

Image Production

While AI can do well with producing some images, there are ones where it will struggle because of lack of training. An example is when I asked for an image with cyclists placing bicycles on a bus before boarding it. None of the generated images worked, meaning that a trip to a stock library was in order.

While some can specify everything in a prompt at one sitting, I work more iteratively, which probably adds to any task, especially with image generation. It proves that still is a place for stock libraries and having your own personal library as well. We need to remain as orchestrators in all of this, and lack of personal talent can remain a limitation.

System Administration

While this may not be something that I do professionally, my keeping an eye on the worlds of DevOps and DevSecOps means that I am seeing that the presence of AI is adding work of its own. This has no sign of lessening, proving that work is changing dramatically instead of reducing, especially you bring Agentic AI into the equation.

It feels much like the advent of personal computing and that produced a similar seismic shift in the workplace in more innocent times. This time around, nefarious actors are misusing AI, a not unexpected if ominous trend, adding to the security woes that have beset computing for a few decades now.

A Human in the Loop?

At a recent conference, much was being made of keeping humanity in the loop when it came to using AI. There is a catch, though: how do we have engaged humans in the loop? After all, creating computer code allows one to get into flow and remain engaged, possibly overriding any feelings of fatigue. This is what needs replicating, hardly an experience reported with automation in other professions.

The use of AI is a developing field, bringing new challenges as well as solving old problems. That also means upskilling on a grand scale, something happened over time with personal and business computing. While it looks as if the process could be faster this time around, it is too early to know enough about where this revolution is going to take us. That may be enough to keep us engaged.