Blog By : Khaoula BEN SMIDA AOUEDI

🌍 This article is also available in French: Écris-moi ça comme si mon cerveau n’était pas déjà saturé – Khaoula BEN SMIDA AOUEDI

Introduction

We often hear that AI is designed to make work easier, faster, and more efficient.
And in many cases, it does.

In this blog, we will explore how AI affects not just productivity, but mental effort. More specifically, we’ll look at how effort doesn’t disappear, it shifts, and what that means for our daily work, our attention, and roles like software testing where human judgment still matters.

1. AI saves time. But does it save our brains?

We hear the same promises everywhere: more speed, more productivity, more automation, more efficiency.

And to be fair, AI does deliver on many of them.

It writes emails, summarizes meetings, generates ideas, suggests test cases, and helps us move faster through tasks that used to take much longer. On the surface, it looks like a clear reduction in effort.

But I think something else is happening at the same time.

AI is not only changing how we work. It is changing how we think while we work.

And that is where I keep coming back to the same question: is AI really reducing effort, or is it simply moving it somewhere else?

2. The effort did not disappear. It shifted.

In practice, AI rarely removes work entirely.

What it often removes is the first layer: the blank page, the first draft, the initial structure, the repetitive starting point. That part is valuable, of course. Anyone who works with AI regularly knows how useful it can be to have a first version in seconds.

But the work does not stop there.

Instead, it becomes another kind of effort: prompting, reviewing, correcting, validating, comparing, deciding.

We ask.
It answers.
We check.
We adjust.
We ask again.

The task becomes faster, but not necessarily lighter.

This is the part that is still underestimated. We tend to measure AI by time saved, but much less by attention consumed.

3. From execution to permanent judgment

Before AI became part of our daily workflow, many of our tasks were repetitive but stable.

Writing emails. Preparing meetings. Documenting decisions. Following processes we already knew well. Producing content or analysis in forms we had practiced for years.

These tasks were not always exciting, but they were familiar. They did not require constant arbitration.

Now, AI handles part of that execution.

So what replaces it?

Not rest.

What replaces it is judgment.

Is the answer correct? Is it relevant? Did the model understand the context? Is the tone right? What should I keep? What should I rewrite? What am I still responsible for?

That kind of work is less visible than writing from scratch, but often more cognitively demanding. It asks for constant micro-decisions. And over time, that mental intensity accumulates.

4. Talking to AI is work too

There is a misunderstanding in the way we often speak about AI: as if using it were passive.

In reality, meaningful interaction with AI requires attention.

You have to know what you want, or at least get close enough to describe it. You need to identify vagueness, spot inconsistencies, catch false confidence, and refine the request until the result becomes usable.

That is not passive assistance. That is active cognitive work.

Sometimes, one hour with AI feels like three hours of mental activity compressed into one. Not because the tool is ineffective, but because it keeps the brain in a constant loop of interpretation, evaluation, and correction.

The output may come faster. The mental load does not necessarily get smaller.

5. The hidden fatigue behind productivity

This is where I think the conversation needs more honesty.

AI absolutely increases capability. It helps us produce more, explore more, and move faster. But increased capability does not automatically mean reduced fatigue.

Sometimes it means the opposite.

Because the nature of fatigue has changed. It is no longer always the fatigue of volume or repetition. It is increasingly the fatigue of continuous mental engagement.

Reading. Sorting. Evaluating. Correcting. Deciding.

Again and again.

The work feels lighter in execution, but heavier in attention.

And perhaps that is why so many people feel more mentally saturated, even when some tasks are objectively easier than before.

6. What this changes in testing

I see this especially clearly in software testing.

For years, the ISTQB process has offered a clear structure: planning, design, implementation, execution, and closure. It has served as a reference point for how to approach testing in a disciplined way.

That structure still matters. But AI is changing the environment in which it operates.

Today, AI can generate test ideas, assist with analysis, support risk prioritization, accelerate automation, and even help during execution. The testing process is no longer just a sequence of human-led activities. It is increasingly an interaction between human judgment and machine-generated proposals.

So the question is no longer simply whether the traditional process is still relevant.

The better question might be: how should it evolve?

7. The tester’s value is moving, not disappearing

Whenever AI enters a profession, people immediately ask whether the human role will disappear.

I do not think that is the most useful question here.

In testing, the real shift is not the disappearance of the tester. It is the redefinition of the tester’s value.

What matters more now is not only the ability to write and execute tests. It is the ability to think critically, understand business context, challenge outputs, detect what does not make sense, and explore what AI did not see.

In other words, the tester becomes even more important where human judgment is irreplaceable.

That is why I do not believe the future of testing is fully manual. But I do not believe it is fully automated either.

It is hybrid.
It is iterative.
And it depends on a human mind that remains capable of doubt.

8. AI is not removing intelligence. It is redistributing it

So is AI making us less intelligent? I do not think so.

But I do think it is redistributing where intelligence is required.

Less energy goes into certain repetitive forms of production. More energy goes into interpretation, supervision, evaluation, and decision-making.

That is not necessarily a loss. In many ways, it is progress.

But every shift has consequences.

If our work increasingly depends on being the final reviewer of machine-generated output, then we need to recognize that this role is mentally demanding. We are not simply doing less. We are doing a different kind of work, one that often requires sharper attention for longer periods of time.

And that can be exhausting.

9. Conclusion: the machine may be faster, but the brain still pays

I am not writing this to reject AI. On the contrary, I use it, I see its value, and I believe it is already transforming work in powerful ways.

But I also think we need to become more precise in the way we talk about that transformation.

AI does not simply remove effort. Often, it relocates it.

It removes part of the execution, but adds supervision. It shortens production time, but increases the density of thought inside that time. It reduces some forms of friction, while creating a new kind of cognitive load.

So perhaps the real question of this AI era is not whether machines are replacing human intelligence.

Perhaps the real question is whether we are paying enough attention to the new kind of mental effort they create.

Because yes, the machine is doing more and more.

But at the end of the day, it is still our brain that carries the final decision.