1. It's Not "Intelligent"
Despite the name, most AI is not intelligent. It’s statistical pattern matching. It doesn’t think, it predicts. LLMs like ChatGPT don’t "understand" you. They autocomplete your thoughts based on trillions of examples. Impressive? Yes. Intelligent? No.
2. Productivity Gains Are Exaggerated
AI is pitched as a magic bullet for productivity. In reality:
- Time saved using AI is often lost validating or fixing its output.
- For many businesses, the cost of integration outweighs short-term benefits.
- "Automation" hype rarely includes the human time needed for prompting, reviewing, or editing.
3. AI for Everything? Nonsense.
Most "AI transformation" projects are overkill:
- A POS system doesn’t need AI. You need reliability and speed, not sentiment analysis on why a kid bought candy.
- AI gets thrown into dashboards just to make them look "smart".
- Fancy UI, zero real value.
4. VC and Big Tech FOMO
Let’s not forget the money trail:
- VCs pumped billions into AI startups without real product-market fit.
- Big Tech overhired in AI and now needs to justify it — hence, the "AI-everywhere" narrative.
- The public gets the illusion of progress while core tech remains unchanged.
5. It’s a Business Model, Not a Breakthrough
Most current "AI" products:
- Lock you into proprietary APIs
- Sell your data to "improve models"
- Offer expensive subscriptions with marginal gains over basic automation
The SCAM is simple: take old automation, rebrand it as AI, add a chatbot, slap a usage-based fee on it.
6. Exceptions Exist — But Rarely Justify the Noise
Yes, AI is useful in:
- Fraud detection
- Medical imaging
- Predictive maintenance
But that’s not 95% of businesses. For most SMBs or internal tools, a well-written SQL query or rule-based workflow will outperform AI.