From 2024 to 2026, the field of AI toys was like a continuously heating-up performance, with dazzling stage lights and continuous applause from the audience. However, the plot behind the scenes remained unclear. You would notice that new products emerged almost every few weeks - talking plush toys, smart robots with large models, and so-called "digital companions" that claim to accompany children throughout their growth... They took turns making appearances at press conferences, exhibitions, and media reports, and financing news was frequently reported. Nevertheless, behind all this excitement, there is an unavoidable reality that is hard to ignore: the vast majority of AI toys have not truly entered consumers' daily lives. They are more often regarded as novelty items for a brief experience rather than becoming long-term household possessions.

This raises a thought-provoking question - why are these toys, which seem to be full of technological and futuristic elements, difficult to generate a strong purchasing desire among consumers? Is it because the technology is not yet mature? Or is it because the underlying model capabilities are insufficient? Or is it because users' understanding of these products is not yet complete? These explanations seem reasonable, but if we delve deeper, we will find an explanation that is less appealing but closer to the truth: The biggest weakness in the current AI toy industry is not funds, technology, or market education, but the lack of a truly "product manager".
The "product manager" referred to here is not merely a position within the company's organizational structure, but rather a responsibility role and a way of thinking that inquires into and takes responsibility for the fundamental reasons for the existence of a product. We need someone to truly answer these key questions: Why is this product being made? What specific problems does it solve? Does this demand really exist? Or is it just something we think exists? At the same time, someone is also needed to make clear choices and show restraint within the boundaries of AI capabilities, rather than blindly adding functions and showing off skills. If these questions are not seriously considered and answered, no matter how advanced the model is or how touching the story is, such a product is essentially just a "seemingly lively technical experiment", rather than a genuine product that can be accepted by users.
Observing the current industry situation, we can find a common and alarming path dependence: the birth of many AI toys is based on "what we can do" rather than "what the users need". For instance, when seeing that AI can have conversations, it immediately leads to the idea of making a companion chat toy; when the model has memory function, it follows suit to launch "growth partners"; after the emergence of emotion recognition technology, it is packaged as "emotional companions". Once the technology is introduced, the product is easily made, as if as long as the technology exists, the product must be valuable. But few people ask in reverse: if AI is not used, does this demand still hold? If the ability of AI can only reach the passing mark, can this product still exist independently and be recognized by users? Under such a mindset, naturally, a large number of "logically plausible but practically useless" products will appear in the market.
The deeper problem is that many AI toys even have difficulty clearly defining "who the users are". In product introductions, "users" are often an extremely vague collection: children, parents, young people, even the entire family. But the real product manager must make a harsh choice - who is the first user? Who has the final decision-making and veto power? In what emotional state and scenario will this toy be used? Does it solve frequent practical problems or only remain in imagined needs? If these basic questions have not been seriously considered and clearly answered, then the failure of the product is almost inevitable.
Another seriously overlooked misconception is that many AI toys even have difficulty clearly defining "who the users are". In product introductions, "users" are often an extremely vague collection: children, parents, young people, even the entire family. But the real product manager must make a harsh choice - who is the first user? Who has the final decision-making and veto power? In what emotional state and scenario will this toy be used? Does it solve frequent practical problems or only remain in imagined needs? If these basic questions have not been seriously considered and clearly answered, then the failure of the product is almost inevitable.
Another overlooked misconception is that many AI toys even have difficulty defining "who the users are". In product introductions, "users" are often an extremely vague collection: children, parents, young people, even the entire family. But the real product manager must make a harsh choice - who is the first user? Who has the final decision-making and veto power? In what emotional state and scenario will this toy be used? Does it solve frequent practical problems or only remain in imagined needs? If these basic questions have not been seriously considered and clearly answered, then the failure of the product is almost inevitable.
In the past two years, the development speed of the AI toy industry has exceeded the expectations of many people. The technology has become increasingly mature, costs have gradually decreased, and product forms have become increasingly diverse. When an industry reaches this stage, what is most urgently needed is no longer to discuss "can it still be done", but to seriously think about "how to make it a real product". In this sense, when AI toys move towards 2026, what they urgently need is not just more advanced algorithms and richer functions, but to return to product thinking, so that each product can clearly answer: for whom is it made, what problem does it solve, and why is its existence irreplaceable.
