New data shows that AI-powered apps can make money, but they have a hard time sustaining it over the long term

With major app stores filled with AI apps, developers may think their best bet for making a profit is to integrate AI technology into their own products. However, a new study focusing on the ecosystem of subscription apps across iOS, Android, and the web calls this assumption into question.

RevenueCat, a company that provides subscription management tools used by more than 75,000 app developers, said in its 2026 State of Subscription Apps report that AI integration is no guarantee of long-term retention. Instead, AI-powered apps struggle to retain subscribers, with people canceling their annual subscriptions — a metric known as “churn” — 30% faster than non-AI-powered apps, on average, according to the report.

The report is based on an analysis of subscription app providers that use RevenueCat tools to manage more than 1 billion in-app transactions, generating more than $11 billion in revenue for developers annually. As one of the most popular tools in this field, its data represents a healthy sample in terms of trend analysis.

Among the many interesting findings, the report noted that most applications using the company’s platform are not yet powered by artificial intelligence. AI-powered apps represent 27.1% of apps across all categories, compared to 72.9% for non-AI-powered apps. However, it’s a growing category, with nearly one in four apps now powered by AI.

(To be clear, the AI-powered app category includes not only popular AI-powered chatbots, like ChatGPT and Gemini, but also any app that markets itself as being AI-powered.)

Photo and video apps have the largest share (61.4%) of AI-powered apps, while games have the smallest share at 6.2%. Travel (12.3%) and business (19.1%) are also sectors with low AI.

The most surprising numbers relate to the ability of AI applications to retain their paying customers. RevenueCat data shows that AI apps perform poorly in user retention on both monthly and annual levels.

The annual retention rate, a metric that focuses on an app’s ability to retain subscribers after 12 months, was 21.1% for AI apps, compared to a higher rate of 30.7% for non-AI apps. Monthly, AI apps saw retention rates of 6.1%, versus 9.5% for non-AI apps, a difference of 3.4 percentage points.

The only area where AI led to data retention was on a weekly basis, where AI apps achieved retention rates of 2.5% compared to 1.7% for non-AI apps. It’s worth noting that weekly subscriptions are not the most popular option for AI apps.

These metrics can be affected by the rapidly changing state of AI technology, which can cause users to switch between different AI applications more quickly, as they try to find the one that has the latest technology under the hood.

As customers experiment with an increasing number of AI applications, they are also likely to find that some do not meet their needs. The report indicates that AI apps have 20% higher recovery rates (4.2% vs. 3.5% on average) than non-AI apps.

The upper end of refund rates for AI apps is also higher (15.6% vs. 12.5%), indicating “greater volatility in revenue generated and deeper issues in user value, experience and quality over the long term,” the report notes.

The data suggests that there are some benefits to being in the AI-powered application pool.

RevenueCat found that AI apps convert users from trials to paying customers 52% better than non-AI apps (8.5% vs. 5.6% on average), and AI apps monetize their downloads nearly 20% better than non-AI apps (2.4% to 2.0% on average).

AI applications also generate 39% or higher monthly realized value (RLTV), a metric that measures the actual net worth of the average paying user over time. AI apps on this metric average $18.92 per month, compared to $13.59 for non-AI apps. AI applications also maintain 41% or higher RLTV year over year, at $30.16 versus $21.37, which is also on average.

The general takeaway from the report’s findings is that AI can drive strong, early monetization, but these applications struggle to maintain their value with customers over time.