Everything was AI at CES, even when it wasn't

Walking the CES showroom floor, you couldn’t turn your head without seeing the letters "AI" plastered across a booth.

From the Rabbit R1 to LLM-powered car assistants, artificial intelligence took over the entire event. But look a little closer beneath the marketing buzz, and a lot of this "groundbreaking" tech wasn’t actually what people thought it was.

The great rebranding wave

Generative AI is currently in its throw-it-at-everything phase. Companies want to believe it is the ultimate differentiator, which is why we saw Walmart pitching AI to restock pantries and automakers cramming ChatGPT into dashboards just to give drivers something to chat with.

However, many of these features have been around for years. Algorithms that used to be called machine learning or pattern recognition are suddenly wearing fresh "AI" badges because companies want to look ambitious and forward-thinking.

Take the robotics on display, like Samsung’s rolling companion Ballie or LG’s household robot. Both are legitimate feats of engineering, but their real brains rely heavily on traditional robotics and computer vision, not frontier large language models. Nobody even talks about machine learning anymore because it sounds too old-fashioned.

The danger of overpromising

Slapping an AI label on everything creates real risks for the tech industry.

Arun Chandrasekaran, an analyst at Gartner, pointed out that there is now a conflation between generative AI and other forms of AI. To most regular consumers, AI has become strictly synonymous with ChatGPT, meaning people expect every AI-branded product to reason like a human chatbot.

Chandrasekaran warned that marketers might be shooting themselves in the foot by creating expectations their products simply cannot meet. When buyers realize an "AI feature" is just a basic recommendation engine, frustration quickly sets in.

Still, Chandrasekaran noted that every technology passes through these lifecycles. Once the inevitable disillusionment hits and the hype clears, that is usually when truly practical use cases finally emerge.

Why it matters

We think this flood of AI branding looks more like corporate FOMO than genuine product innovation. Companies are terrified of appearing behind, so they are slapping generative labels on deterministic code and traditional sensors.

For users, this means keeping your wallet guarded. You do not need to jump at every gadget bragging about artificial intelligence right now, because half of them are just rebranded legacy algorithms wrapped in shiny new copy.

The real risk here is consumer trust. Overpromising what an AI companion can do will only accelerate user fatigue and fuel backlash against the technology as a whole.

That said, the coming hangover could be healthy. Once the market realizes that not every household gadget needs a chat window or an LLM, engineering teams can stop writing gimmick prompts and get back to building software that quietly works.