Is AI the modern day Tamagotchi?
No doubt some of the younger readers of this article are already scrambling for the search bar to ask, “What is a Tamagotchi?”
I appreciate the reference is a little retro, but please indulge me.
Rewind to 1997. The Spice Girls were everywhere, dial-up internet was making that unforgettable noise and schools were dealing with a new digital craze that eventually resulted in blanket bans across classrooms.
The offending item was an export from Japan called a Tamagotchi.
For the uninitiated, it was an egg-shaped digital pet that lived on a tiny screen. Your job was simple: keep it alive. Feed it, play with it, clean up after it and generally give it enough attention to help it develop through different life stages.
Nearly 30 years ago, we became obsessed with looking after a tiny digital creature.
Today, we’re doing something surprisingly similar. Except this one writes emails, creates images, analyses data, automates workflows and occasionally makes things up with absolute confidence.
So, what’s a 90s pocket game got to do with AI?
Quite a lot, actually.
At the heart of both is the relationship between technology and its owner: humans.
Sound tenuous? Stick with me.
Bandai, the company behind Tamagotchi, describes how the care you give your digital pet influences how it develops. While AI doesn’t “grow up” in quite the same way, there is a surprisingly relevant business lesson here.
The value you get from the technology is heavily influenced by what you put into it.
And that’s where the similarities start.
You have to learn how to communicate with it
The whole purpose of a Tamagotchi was interaction.
It would tell you it needed something, usually through an irritating series of beeps, and you had to work out whether it needed feeding, cleaning, entertaining or something else entirely.
Over time, you got better at understanding it.
AI isn’t particularly different.
Prompts, context and instructions have become our modern-day Tamagotchi buttons. Ask a vague question and you’re likely to get a vague answer. Give it context, explain the audience, provide examples and define what good looks like, and the output usually improves considerably.
This matters for businesses investing in AI.
Buying access to the technology isn’t the same as knowing how to use it. The real advantage comes from people learning how to communicate with these tools effectively and understanding where they can genuinely add value.
It still needs human intervention
Leave your Tamagotchi unattended for long enough and the inevitable happened.
It died.
Thankfully, the consequences of ignoring ChatGPT for an afternoon aren’t quite so dramatic.
But the need for human intervention hasn’t disappeared just because the technology has become more sophisticated.
AI can analyse information, generate content, identify patterns and increasingly use agents to complete tasks autonomously. But useful business outcomes still require direction, judgement and oversight.
Someone needs to define the objective.
Someone needs to decide whether the output is actually any good.
And someone definitely needs to check that the incredibly convincing statistic it just produced actually exists.
The temptation with AI is to equate automation with autonomy. They’re not the same thing.
For business leaders, the opportunity isn’t necessarily removing people from processes. It’s deciding where technology can remove unnecessary work while keeping human judgement where it adds the most value.
What you put in affects what you get out
With Tamagotchi, the quality of care affected how your digital pet developed.
Neglect it and things generally didn’t end well.
AI has its own version of this relationship.
Give it a one-line instruction with no context and you’ll probably receive something that looks acceptable at first glance but falls apart pretty quickly.
Give it good source material, clear parameters, relevant examples and a defined objective and you’ve got a much better starting point.
There’s another side to this too.
The more you use AI, the better you become at using it.
You start understanding how much context to provide. You recognise the tasks it’s good at and the ones where it struggles. You learn what to trust, what to check and, perhaps most importantly, what to challenge.
That experience is becoming a skill in itself.
For small businesses in particular, that matters. AI can put capabilities that previously required significant time, resource or outside expertise within reach. But access to the tool doesn’t automatically create the capability.
Knowing how to use it does.
You still need to clean up the mess
Anyone who owned a Tamagotchi will remember this particular feature.
You literally had to clean up digital poo.
Fun, right?
Nothing says cutting-edge 90s entertainment quite like cleaning up after a pixelated creature on a keyring.
AI creates its own kind of mess.
Hallucinations. Generic copy. Questionable data. Unnecessary content. Strange images. Repetitive language. And, occasionally, complete nonsense delivered with the confidence of someone who has absolutely no doubt they’re right.
The speed of AI means businesses can now create more, faster.
But more isn’t automatically better.
If AI allows you to produce ten times as much content but someone still has to spend hours fixing it, have you genuinely become more productive?
The role of human quality control arguably becomes more important as AI adoption increases, not less.
Because when the cost of creating something approaches zero, knowing what’s actually worth creating becomes incredibly valuable.
It can become strangely addictive
There’s a reason Tamagotchis became the scourge of classrooms.
Students became obsessed.
The constant beeping and alerts told you that your digital pet needed attention. But after a while, you didn’t need the beep. You’d check anyway.
AI is beginning to create a similar behavioural shift.
A task lands on your desk and increasingly the first thought is:
“I wonder if ChatGPT could do this?”
Write an email? AI.
Summarise a document? AI.
Analyse a spreadsheet? AI.
Create an image? AI.
Brainstorm an idea? AI.
That experimentation is part of the attraction, and it’s also how businesses discover genuinely valuable use cases.
But there’s a potential downside.
Not every problem needs an AI solution.
Sometimes the quickest way to complete a five-minute task is still to spend five minutes doing it, rather than spending twenty minutes trying to automate it.
The businesses that benefit most from AI probably won’t be those that use it for absolutely everything. They’ll be the ones that understand where it genuinely saves time, improves decisions or creates something that wasn’t previously possible.
You need to know when to intervene
Perhaps this is the most important comparison.
A Tamagotchi didn’t remove responsibility from its owner. It created responsibility.
AI shouldn’t remove it either.
The technology can increasingly do more of the work, but that makes the decisions around when and how to use it more important.
What should be automated?
What requires human judgement?
Where does AI make something faster without making it better?
And where could getting it wrong damage a customer relationship, a reputation or a business decision?
Those aren’t technology questions.
They’re leadership questions.
So, is AI really the modern-day Tamagotchi?
Obviously, there are some fairly significant differences.
Nobody is expecting ChatGPT to sprout legs, beep from your pocket and demand feeding. At least, not yet.
But there is something familiar about our relationship with it.
We interact with it. We learn how to communicate with it. We give it information. We check what it produces. We clean up after it. And the more time we spend with it, the more it starts finding its way into our everyday routines.
That’s perhaps the most important lesson for businesses.
AI isn’t something you simply buy, switch on and suddenly become more productive.
Getting genuine value from it requires attention, experimentation and boundaries. It requires people who understand both the technology and the problem they’re trying to solve.
Above all, it still requires a human being who knows what good looks like.
Nearly 30 years ago, we were responsible for keeping the technology alive.
This time around, perhaps our responsibility is making sure the technology actually makes us better.
Frequently asked questions
Is AI like a Tamagotchi?
There are some surprising similarities. Both rely on regular human interaction to get the best from them. With AI, the quality of prompts, context and information provided can significantly influence the usefulness of the output.
Why does AI still need human intervention?
AI can automate tasks, analyse information and generate content quickly, but human judgement remains important. People still need to set objectives, check accuracy, provide context and decide whether an AI-generated output is appropriate for the business.
Does AI get better the more you use it?
Not necessarily in the way a Tamagotchi develops. What often improves is the person using it. Regular use helps people understand how to write better prompts, provide useful context and recognise where AI performs well and where human input is still needed.
What does human-in-the-loop mean in AI?
Human-in-the-loop refers to keeping people involved in an AI-enabled process. Rather than allowing AI to make every decision independently, humans can review outputs, provide feedback and intervene where judgement or additional context is required.
How can small businesses get more value from AI?
Start with clearly defined business problems rather than adopting AI for its own sake. Look for repetitive or time-consuming tasks where AI can improve efficiency, then provide clear instructions, relevant information and human oversight.
Should businesses use AI for every task?
No. AI is most valuable when it solves a genuine problem, saves meaningful time or enables something that would otherwise be difficult to achieve. Sometimes completing a simple task manually is still faster and more effective.
