The Odd Things AI Makes Me Think About, Curiosity No. 2

Curiosity No. 2: First It Ate the World, Now It’s Eating Our Brains

You know the old tech saying: “software is eating the world.”

We watched computers quietly consume the physical world – stores became apps, taxis became algorithms, maps became lines of code, offices became tabs in a browser. Everything solid slowly turned digital.

Now, something stranger is happening: AI isn’t eating the world. It’s nibbling on our minds instead. 

Not in a scifi, brainhijacking way. More in a “Wait, why did I just ask a machine for help drafting an email I already knew how to write?” way. AI has started to take over the subtle, everyday cognitive tasks we once considered unquestionably human: finding the right words, checking our logic, organising our thoughts, remembering what happened last quarter, explaining something we never fully understood in the first place. Bit by bit, the machine is not just processing our information – it’s coauthoring our thinking.

A quick business example to make this real

Think of the presales team responding to an RFP.

In the old world, the team gathered inputs from experts, reused elements from past proposals, aligned on technical details, and shaped everything into a coherent value story. It was coordinated, thoughtful work – timeconsuming mainly because so many pieces had to be assembled.

In the new world, AI generates a strong first draft – structure, value messages, use cases, risks, and industryspecific language included. The team focuses on refining, validating, and strengthening the response rather than building it from scratch.

The work hasn’t disappeared, but the starting point of thinking has shifted outside our heads. 

Why this matters

When technology ate the physical world, businesses reorganised operations. Now that AI is eating cognitive load, businesses will reorganise brains – or more precisely, the way people use them.

Three quiet shifts are already happening:

• We think less from scratch. We react to machinegenerated starting points instead.

• We remember less. Why bother? The machine remembers instantly and without complaint.
• We decide faster. Sometimes too fast, because the draft feels “good enough.”

This isn’t bad. It isn’t good. It’s simply… new. And with every convenience it offers, AI also asks a quiet question:

What parts of thinking should remain stubbornly, beautifully human? 

But shifting the cognitive starting point comes with real challenges

AI’s speed and confidence create a subtle shift: we risk reacting to its answers instead of thinking through our own. When a polished draft arrives instantly, it’s tempting to accept it as “good enough.” The antidote is simple but powerful – treat every AIgenerated output as a starting point and ask, “Why this answer and not another one?” That small question, even when AI itself provides the chain of thought or reasoning, keeps human reflection in the loop.

Nuance is another quiet casualty. AI tidies complexity because tidiness is easier to process, but business rarely works that way. Context, sensitivities, and corporate undercurrents matter. To preserve nuance, we must reintroduce it deliberately by asking questions like, “What’s missing here?” or “Who would see this differently?” AI won’t offer that nuance unless we ask for it.

Creativity can also narrow when everything starts with a prompt. AI is excellent at remixing what already exists, but the ideas that matter most – the unexpected ones – tend to come from human jumps, not machine patterns. Alternating between AI assisted work and pure human ideation helps keep that spark alive. Sometimes the most productive thing a team can do is think without the machine in the room.

And finally, there’s the risk of oversimplifying the messy problems – the ones shaped by priorities, incentives, politics, and emotion. AI sees patterns; enterprises run on contradictions. The most helpful stance here is to use AI for clarity rather than certainty. Let the model surface and structure the information, but keep humans in charge of interpreting the mess. 

Ultimately, responsible AI practices (as practiced within Fluido’s AI framework), discipline, and built‑in governance are key to keeping humans in the loop. More importantly, it is up to each of us to ensure that our collective human cognitive capacity is actively practiced and preserved.

So, let me ask you now: as AI starts nibbling at our cognitive world, how will YOU make sure you’re still the one choosing the red pill?

Did you like this post and are you interested in taming the AI Beast? Follow our Fluido AI expert – Greg Anderson, Didier Dessens, Oby Manyando and Boris Naumov. And if you’d like to continue the conversation, feel free to reach out to me. You can also read more about our AI initiatives here.

About the post Series:

“The Odd Things AI Makes Me Think About” is a collection of short, thoughtprovoking reflections on the stranger, overlooked, and sometimes uncomfortable edges of artificial intelligence. This series steps away from the usual AI “from doom to utopia” narratives, and instead explores the quirky, curious, and occasionally provocative questions that surface when humans and machines collide.

Expect posts that challenge assumptions, spotlight unusual angles, and invite a different kind of attention-because the most interesting ideas usually live just outside the mainstream.