The Consumer Electronics Show (CES) 2026 undeniably showcased technological progress. Screens displayed more vivid images, gadgets became lighter and more portable, and sensors achieved new levels of sharpness. Yet, the most dominant theme echoing across the exhibition floor wasn't a genuine breakthrough. It was a habit. The term "AI" has become the default label companies use to make a product sound complete and advanced, often when the underlying concept remains underdeveloped.
From Haircuts to Health: When AI Promises Clash with Reality
The most telling moments at the event were not the polished demonstrations. They emerged when simple, practical questions caused elaborate pitches to falter. Does the device function without an internet connection? What user data does it collect? Who is accountable when the system makes an incorrect judgment?
Take the example of Glyde's smart hair clippers. They address a common anxiety: many people struggle to give themselves a clean fade haircut at home. The product claims an AI coach guides your hand and the clippers adjust automatically. However, a haircut is a physical, personal task relying on feel and subtle judgment, not just instructions. A tool that sounds confident does not guarantee correct advice, and the consequence of a mistake is immediate—a patchy haircut that takes weeks to grow out.
Another concerning trend is the use of clinical language for non-medical products. SleepQ, for instance, combines pills with AI. It analyses data from a smartwatch to suggest when to take a sleep supplement. While this is essentially a personalised reminder system, its framing can misleadingly imply medical treatment. Timing advice is not a cure, and wearable data is not a diagnosis. Brands venturing near health must transparently state their capabilities, limitations, and the evidence behind their claims.
The Trust Deficit in Smart Homes and Children's Tech
Even repairability, a positive trend, can be twisted. Deglace's Fraction stick vacuum claims to predict part failures and assign "health scores," making replacement easy. The concern arises when the same system declaring a part 'unhealthy' is also the one selling the new component. Without transparency on how these scores are calculated, consumers are asked to trust a black box with a clear financial incentive. This trust gap appeared elsewhere too, in microwaves offering AI cooking guidance or drink machines attempting to assess age and sobriety via a camera.
Perhaps the most critical questions are reserved for AI targeting children. A device that engages kids in open-ended chat and reacts to a camera feed is not a simple toy feature. It's a system that can shape a child's understanding of trust and interaction. The issues go beyond the risk of inappropriate replies. Companies in this space must provide clear answers: What data is stored, who can access it, can parents fully disable the camera, and what happens to chat logs?
Asking the Right Questions Before You Buy
The core issue is not AI itself, but vague, unexplained AI. If a brand cannot plainly explain what its system does, what data it requires, and how it handles errors, the label "AI-powered" should be treated as a warning. Before purchasing any such gadget, consumers should ask three fundamental questions:
- Where does my data go? (Data privacy and storage)
- What core functions still work offline? (Dependency on the cloud)
- What happens when the AI makes a wrong call? (Accountability and recourse)
If the answers sound like marketing copy instead of clear, factual information, it's best to walk away. The real innovation needed now is not more AI buzzwords, but greater transparency and responsibility.
