The Top 100 Most Used AI Apps in 2025

Full Title

The Top 100 Most Used AI Apps in 2025

Summary

The podcast discusses the fifth edition of the Consumer AI Top 100 list, focusing on real consumer adoption trends in AI-native products.

Key findings include the stabilization of the AI app ecosystem, the rise of "vibe coding" and companionship categories, significant entries from Google and Chinese companies, and the growing importance of product experience over proprietary models.

Key Points

• The Consumer AI Top 100 list tracks the most used AI-native products based on global website visits and mobile active users, providing a gauge of consumer adoption beyond revenue.
• While the mobile AI app landscape initially saw dominance by ChatGPT copycats, iOS ecosystem changes have led to a broader range of new entries, indicating a maturing market.
• The web list shows signs of ecosystem stabilization with fewer new companies compared to previous editions, suggesting that established AI products are retaining their user base.
• "Vibe coding" has emerged as a significant new category, with companies like Lovable and Replit demonstrating strong user engagement and impressive revenue retention, even surpassing 100% in early months.
• Companionship AI applications, including services like Character AI and SpicyChat, continue to be a dominant category, with several new entrants joining established players on the list.
• Google made a significant debut with multiple properties, including Gemini at number two and AI Studio in the top 10, highlighting their increased focus on AI-native consumer products.
• Chinese AI companies are increasingly prominent, appearing both as domestic solutions for the Chinese market (due to bans on foreign services) and as global exporters of AI models and products, particularly strong in image and video generation.
• "All-star" companies that have consistently appeared on the list since its inception demonstrate that product experience and workflow integration are as crucial as foundational models, with many leveraging third-party models or acting as aggregators.
• The trend of consumer AI products transitioning to "prosumer" and enterprise use cases is growing, with companies offering team plans and advanced features, creating stickiness and a bottom-up adoption model.
• Future trends to watch include verticalization of AI products, the continued growth of "vibe coding," more sophisticated productivity tools where accuracy is paramount, and the emergence of AI-native social platforms, edtech, and personal finance applications.

Conclusion

The AI app landscape is maturing, with established players holding strong and new categories like "vibe coding" gaining significant traction.

Product experience and user workflows are increasingly critical for consumer AI success, even when leveraging third-party or open-source models.

The future will likely see further diversification and specialization within AI applications, particularly in productivity, social, and niche sectors like education and finance.

Discussion Topics

• What new AI categories or use cases do you predict will break into the Top 100 list in the next year?
• How important is the user interface and product experience compared to the underlying AI model for consumer adoption?
• With the rise of "vibe coding" and AI companionship, what are the most exciting or concerning trends you're seeing in consumer AI?

Key Terms

AI-native

Products or services built from the ground up with artificial intelligence as a core component.

Gen AI

Generative Artificial Intelligence, AI models capable of creating new content like text, images, or audio.

LLM

Large Language Model, a type of AI model trained on massive amounts of text data to understand and generate human-like language.

Vibe coding

A term used to describe platforms that allow users to create and share AI-generated content or experiences, often with a focus on aesthetic or creative output.

ARR

Annualized Recurring Revenue, a metric used to track the predictable revenue a company expects to receive from its customers over a year.

Cohort

A group of users who share a common characteristic or experience within a defined time period, used for tracking behavior and retention.

Network effects

A phenomenon where a product or service becomes more valuable as more people use it.

Hallucinations (in AI)

When an AI model generates plausible-sounding but factually incorrect or nonsensical information.

Prosumer

A user who bridges the gap between consumer and professional, often using advanced tools for personal or semi-professional projects.

Timeline