Are We in an AI Bubble?
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“The patterns are clear.”
That was my first thought recently as I scrolled through yet another thread announcing a new AI SaaS platform. GPT wrappers everywhere. Startups racing to integrate AI into anything that breathes. It feels like the dot-com boom again, only this time it’s happening at lightspeed.
So, the question arises: do we declare this decade an AI bubble? I think yes. But the story is much deeper than just hype.
1. The Technological Cycle: From Magic to Commodity
Every major technological revolution follows a familiar cycle:
Breakthrough Phase – The tech feels magical. Few pioneers push boundaries (think LLMs around 2019–2021).
Hype Expansion – APIs become public, wrappers emerge, media amplifies everything. Everyone wants in.
Commoditisation & Plateau – The technology becomes a utility. Margins shrink. Innovation slows.
Post-Bubble Consolidation – Most players vanish. A few infrastructure builders and innovators remain.
AI is currently somewhere between late hype and early commoditisation. The same base technology is being wrapped in hundreds of ways. And ironically, that abundance of tools might be inhibiting innovation instead of fuelling it.
2. When Convenience Starts to Kill Creativity
One thing I’ve been thinking about a lot: AI is saving us typing time, yes. But what if typing itself is where some of the best ideas are born?
Typing isn’t just mechanical. It’s part of the cognitive process:
When we write, we shape vague ideas into structured thoughts.
We discover new connections mid-sentence.
We stumble upon originality through friction.
If AI fills in all the blanks for us, we risk outsourcing not just labour, but also the thought paths that lead to breakthroughs. Innovation often emerges in the messiness of creation, not the polished outputs.
This is one of the subtle dangers of the AI bubble: over-automation can standardise thinking.
3. The SaaS Flood: A Race With No Moats
It’s honestly wild how many nearly identical AI SaaS products are popping up. Meeting note-takers, copywriting tools, email assistants... most of them are just GPT with a UI and a niche label.
But here’s the economic reality:
Low barrier to entry = too many clones.
Zero switching cost = users can leave at any time.
Upstream dependency = one pricing change from OpenAI can wipe out half the startups.
Race to the bottom = price wars, thin margins, no defensibility.
Unless a company has a data moat, deep workflow integration, strong vertical focus, or proprietary fine-tuning, it’s going to struggle to stand out. Most of these “AI startups” are really features, not businesses. And just like during the dot-com boom, many will vanish or get absorbed once the bubble settles.
4. Layoffs and Pivots: Knowledge Isn’t Dying, Relevance Is Shifting
Another clear signal of this bubble: companies are laying people off or pivoting aggressively. But this doesn’t mean the affected people have “wasted knowledge.”
The truth is:
“Their skills have depreciated in market relevance, not in intrinsic value.”
When industries pivot fast, static skills lose value quickly. People who mastered a single workflow without adapting find themselves displaced. Those who keep remapping their knowledge thrive.
The coming generation will face this constantly. Career volatility will become normal, not shocking. Skills will have shorter shelf lives, and adaptability will be the ultimate career armour.
Lifelong learning won’t be a cliché anymore; it’ll be the survival strategy.
5. Not All Jobs Are Equal in the Age of AI
Interestingly, while AI is rapidly disrupting cognitive, digital tasks, many human-efforted jobs remain harder to replace. For example:
Painting a house, designing and manufacturing a cupboard, plumbing, electrical work, welding — these require motor skills, spatial awareness, and adaptability in unpredictable environments.
Even in tech, some roles are “safer” than others. Traditional software engineering might face pressure from AI-assisted coding, but AI engineering, MLOps, cloud infrastructure, and cybersecurity are harder to automate because they involve building and securing the systems themselves.
This creates a fascinating divide:
Digital work is disrupted faster because AI can easily process structured information.
Physical/manual work has natural resistance due to real-world complexity.
Hybrid roles (humans + AI tools) might emerge as some of the most powerful niches.
For example, imagine a carpenter using AI to generate precise designs and estimates, then crafting with enhanced precision. Or a painter using AR + AI to plan colour schemes. In such cases, AI amplifies the human, not replaces them.
6. Strategically Positioning for the Future
For people like me, whose initial dream was to become a software engineer, this landscape means thinking one step ahead. That’s why I’m having thoughts of exploring AI engineering (to be safe, you know 😅). It’s about moving from being a user of the tools to a builder of the systems themselves.
At the same time, I’m keeping an eye on fields AI won’t easily dominate. If you can blend AI expertise with grounded, real-world skills, you become incredibly hard to replace.
7. The Bigger Picture
The AI wave isn’t just a tech trend. It’s a workforce reshaper, a creativity disruptor, and an economic filter that separates surface innovation from real depth.
Many companies will fade because they’re riding the hype without moats.
Many workers will need to reinvent themselves, not because they’re not intelligent, but because relevance moves fast.
Many careers will be born at the intersection of human effort + intelligent systems.
We’re watching a historic shift happen in real time. The key is not to fear it, but to understand its patterns and position ourselves intelligently.
Final Thoughts
Yes, this is an AI bubble. But bubbles aren’t inherently bad. They create noise, yes, but they also accelerate infrastructure, expose weak ideas, and force evolution.
The ones who will thrive are those who:
Build moats, not wrappers.
Keep learning, not just performing.
Bridge AI’s strengths with uniquely human abilities.
And honestly… that future is exciting.
The AI era won’t reward static mastery. It will reward strategic adaptability. Whether you code, build, write, or paint houses, your edge will lie in how you leverage this wave, not just how you survive it.
