看完 1289 个死掉的 AI 产品，我发现这些需求就不该用 AI 解决

Core Insights - The AI application market is experiencing a high failure rate, with many products being labeled as "zombie" or "graveyard" applications due to their inability to sustain user interest and engagement [2][6][24] - A significant number of AI products, particularly in the chatbot category, have been shut down, with 1,289 products reported as closed or inactive, and over 200 new closures expected in 2025 [2][4] - The emotional companionship sector within AI applications is particularly challenging, with few products managing to survive despite the initial hype and interest [16][20] Group 1: Market Trends - The AI application landscape is marked by a rapid turnover, with many products failing to gain traction within 48 hours of launch [1][2] - Chatbots represent nearly 40% of the failed products, while code assistance tools account for over 20% [4] - The emotional companionship category has seen a surge in interest, with 8 out of the top 50 AI applications globally falling into this category [16][17] Group 2: Reasons for Failure - Many failed AI products are criticized for being "shell" products that lack substantial functionality and real-world application [6][9] - The competition is fierce, with startups struggling to compete against larger companies that have more resources and established models [9][10] - Regulatory issues, particularly concerning inappropriate content, have also led to the shutdown of several AI companionship applications [12][20] Group 3: Financial Viability - The monetization of emotional companionship applications remains a significant challenge, with most relying on subscription models that are difficult to sustain [20][24] - Successful products like Replika have managed to maintain a high percentage of paying users, while others like Character.AI struggle with monetization despite having a large user base [24][26] - The emotional companionship market is characterized by a dichotomy: targeting niche users willing to pay versus attracting a large user base with low conversion rates [26]