A sharp rise in new mobile apps is pointing to a shift in how software gets built – and who is building it. Recent data shows that AI coding tools are changing the scale of app creation.
According to data reported by Apple and cited by 9to5Mac, the number of new app submissions to the App Store has surged in recent months. The report notes that submissions increased drastically, including an estimated 84% increase in a recent quarter, while total new apps reached nearly 600,000 globally. The spike has been linked in part to the rising use of AI-assisted coding tools.
This increase reflects a broader shift in how software is produced. Tools that generate code, suggest fixes, and build features from prompts are lowering the effort needed to create a working app.
Lower barrier to entry
For years, building an app required a variety of skills: programming, design, testing, and deployment. AI coding tools are not removing those steps, but they are reducing the time required to complete them.
Developers can now generate scaffolding code in seconds. They can ask tools to write functions, debug errors, connect APIs, and, in some cases, build features through prompts before refining them with manual edits.
The increase in submissions suggests that more independent developers, small teams, and non-traditional creators are taking part.
From productivity tool to production tool
AI coding assistants first gained attention by helping developers in writing code more quickly through suggestions, line completion, and task automation.
The latest wave of tools is moving beyond assistance into execution. Instead of only suggesting code, they can generate components, manage dependencies, and help structure projects. In some workflows, the developer acts more as a reviewer. This shift changes how development time is spent, with less time going into writing code and more going into checking outputs, refining logic, and testing behaviour.
It also raises new questions regarding quality. If more code is generated rather than written, developers must ensure that it works as intended and does not bring up unexpected problems.
Platforms are adapting to the volume
Apple’s App Store review process has long relied on automated checks and human review. With submission numbers rising, that system faces more pressure. Reports cited by 9to5Mac indicate that Apple is using AI tools internally to help scale parts of its review process.
AI tools help developers produce more apps, while platforms use AI to manage the increased volume. The challenge is maintaining quality and safety. More submissions increase the risk of low-quality apps, duplicate ideas, or malicious code slipping through. Automated review can help filter obvious issues, but edge cases still require human judgment.
A larger number of apps does not necessarily mean better software. When it becomes easier to create and publish apps, duplication tends to increase. Multiple apps may provide similar features with minor differences, making discovery difficult for users and developers.
A shift in who gets to build
In the past, building an app required formal training or significant experience. Today, people with basic technical knowledge can produce working applications with the help of AI tools.
More people can experiment, build prototypes, and publish ideas. This move has the potential to reshape the developer ecosystem, leading to more competition and more diversity in the types of apps being created.
How the role changes
The rise in app submissions is a signal, not just a statistic. It shows that AI coding tools are changing the production side of software development.
Developers are likely to spend less time on routine coding tasks and more time reviewing generated code, designing architecture, and managing workflows that include AI tools.
The role is shifting from writing every line to guiding the overall process. At the same time, core skills remain important. Understanding how code works, how systems interact, and how to debug problems is still essential.
A broader shift
The increase in App Store submissions is one of the clearest signs that AI coding tools are affecting real-world output. They are not just speeding up development. They are expanding who can ship software and how often it happens. If the current trend continues, the next challenge will be managing volume and maintaining quality.
(Photo by Fotis Fotopoulos)
See also: How AI and modern languages boost developer team efficiency
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