ChatGPT Sees Broader Use Outside Work Hours
One sign of this shift is how people are using AI assistants like ChatGPT. Last year, most usage happened during weekdays. This was common among tools designed for jobs or school. But this year, ChatGPT’s weekend usage has grown. The pattern looks more like general search apps, which people rely on whether they are working or not.
Lifestyle Prompts Overtake Educational Tasks
Prompt data shows a rise in lifestyle and entertainment queries. Topics such as wellness, travel, shopping, and meal planning have grown. These prompt types now take up a larger share compared to 2024. Educational and technical queries remain popular, but their share has declined. People are using AI in more personal ways.
Functional Apps Face Pressure from General AI Tools
Many category-specific apps are now competing with flexible AI platforms. Apps for budgeting, nutrition tracking, and study help are seeing some users shift to general chatbots. These chatbots can answer many kinds of questions, so people explore them for a broader range of needs.
AI Mentions Surge Across App Stores
Thousands of mobile apps launched with AI-related keywords this year. Software tools remain the most active category for these updates. Apps in wellness, employment, learning, and finance also added AI references. Developers are adapting to the demand for smarter app experiences.
Mixed Outcomes for Traditional App Subgenres
Some mobile app subgenres are growing despite the presence of AI competition. A few are even seeing better performance on user metrics. The difference seems to depend on how they use AI. Apps that add task-specific AI tools tend to hold their ground. For example, nutrition apps now include image-based calorie tracking powered by AI. This gives users quicker results than traditional logging.
Tailored Features Help Apps Stay Competitive
Generic chatbot tools can handle many tasks, but often miss the fine detail users expect from niche apps. To compete, developers are building features that solve narrow problems more efficiently. Apps that respond to this need may retain their users. Those that don’t may be replaced.
H/T: Sensor Tower.
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