AI-Washing in the Pet-Tech Aisle: A Critical Look at "Smart" Marketing

Walk down any electronics aisle, physical or virtual, and you will be inundated with two letters: A.I. From “AI-powered” televisions to “AI-enhanced” toothbrushes, the term has become the technology industry’s favorite seasoning, sprinkled liberally over products to imply a level of futuristic intelligence. The pet-tech sector is no exception. We see devices like the SKYMEE AI-C20 Owl Robot promising “AI intelligent tracking” and its competitors offering an “AI Dog Nanny.” The term is everywhere, yet its meaning has become dangerously diluted. This pervasive and often misleading use of the “AI” label has a name: AI-washing. It is a marketing strategy that preys on consumer excitement and technical ambiguity to sell products that are often far less intelligent than they appear.

AI-washing can be defined as the practice of rebranding older, simpler technologies—most often basic automation and rule-based systems—as “Artificial Intelligence.” This is highly effective because, as a 2023 Consumer Reports survey indicated, over 60% of consumers admit to not fully understanding what the term “AI” actually entails in a product context. This knowledge gap allows marketing departments to create a significant “expectation gap,” where a customer purchases a device expecting a learning, thinking companion and instead receives a device that merely follows a set of simple, pre-programmed instructions. This isn’t just a matter of semantics; it’s a fundamental issue of technological transparency.

To see AI-washing in action, we can examine a product that wears its supposed intelligence right in its name. The “SKYMEE AI-C20 Owl Robot” claims to use AI for tracking pets. Let’s look under the hood. The product’s own documentation reveals that this “tracking” is primarily triggered by a PIR (Passive Infrared) sensor. This is the same, decades-old technology used in automatic security lights and motion detectors. The system operates on a simple, deterministic “if-then” logic: IF the PIR sensor detects a moving heat signature (the pet), THEN execute a pre-programmed action (pivot the robot’s body toward the motion and send a notification). This is automation, and while useful, it is not intelligence. The system does not learn the pet’s behavior, it cannot distinguish a cat from a dog, and it certainly cannot understand the context of the motion. It is a simple trigger-and-response mechanism, cleverly rebranded as “AI.”

This stark difference between marketing claims and technical reality is not meant to single out one company, but to illustrate a widespread problem. So how can a non-technical consumer begin to tell the difference? It helps to think of “smart” features as existing on a spectrum of intelligence, which can be broken down into three general levels.

Level 1: Automation (Not AI). This is the most basic level, involving devices that react to sensor inputs with pre-defined actions. This includes the SKYMEE’s motion tracking, a thermostat that turns on when the temperature drops, or a light that turns on at sunset. There is no learning or adaptation involved.

Level 2: Machine Learning (Emergent AI). This is the first real step into intelligence. Here, the system is trained on vast amounts of data to recognize patterns. A pet camera with machine learning can be trained on millions of images to reliably identify a cat versus a dog, or to distinguish the specific sound of a “bark” from other household noises. The system learns and its performance can improve over time with more data. This is a significant leap from simple motion detection.

Level 3: Contextual AI (True Smartness). This is the pinnacle of what we currently expect from smart devices. The system not only recognizes patterns but also begins to understand their context. A truly smart pet companion would not just detect that your dog is barking. It might learn that barking combined with pacing near the door between 4 PM and 5 PM signifies separation anxiety, and could then initiate a calming action or send a more specific, insightful alert to the owner. This level of understanding, which combines pattern recognition with a semblance of reasoning, is what the term “AI” so often incorrectly implies.

The term “AI” should not be a magic wand waved over a product to inflate its value. It is a specific field of computer science. As consumers, our best defense against AI-washing is to cultivate a healthy skepticism and to ask more precise questions. Instead of being impressed by the “AI” label, we should ask, “How does it work? Does it learn from my behavior or my pet’s? Can it distinguish between different events?” By demanding this level of clarity, we not only protect ourselves from misleading marketing but also push the entire industry toward more honest and truly meaningful innovation.