Why you shouldn’t use AI built apps … Yet

We’re hearing plenty of hype about AI-built apps. Quick, cheap, no-code promises are everywhere. But in reality, whilst these apps are launching, there are very few succeeding in the market. Before you dive in, it’s worth understanding the risks and trade-offs in 2025.

Can AI build apps today?

AI can generate basic web and mobile apps, useful for:

• Prototyping ideas
• Validating concepts
• Demoing to family, friends, or early stakeholders

So yes, AI can build apps, but not to a production quality standard.

Where AI-built apps fall short

The core functions in which AI consistently underperforms are:

• Code quality and maintainability– Firstly, AI code often lacks clear structure and patterns. This builds hidden technical debt that becomes expensive to fix.

• Limited testing and bugging– AI doesn’t automatically write exhaustive tests or handle edge cases thoroughly. As a result, your generated app might work in ideal conditions but break easily in production.

• Security Concerns – AI-generated code can use third-party tools that collect and share user data without clear visibility, sending information to unintended external services.

• Scalability and performance – AI built apps likely lack robust infrastructure, which can impede scale and performance

All of this affects one key thing –  how your users actually experience your app. A slow, buggy, or insecure app is a fast way to lose customers and trust.

Why Human Developers Are Still Essential

Even with AI, an experienced human team is critical to:

• Architect the right data models to avoid long-term technical debt.
• Design polished user experiences that align with your brand and create trust.
• Review and optimise code for quality, performance, and scalability.
• Ensure security best practices are followed from day one.

Without this, it’s impossible to deliver a production-ready app that can scale or attract investment.

Where AI canbe used in app development

AI significantly aids in prototyping and accelerating app development, particularly for smaller, repetitive tasks such as:

• Generating boilerplate code
• Auto filling seed/dummy data for testing
• Glue logic for integrations
• Completing unfinished code sections

But AI should accelerate development, not replace human expertise.

The future of AI technologies in app development

If your app is just a weekend project, AI may be fine. But if it’s a real business –  something you want to scale, sell, or raise capital for, then the shortcuts can backfire hard.

AI is evolving rapidly. Over the next few years, we’ll likely see specialised models that tackle specific development tasks such as infrastructure, UI, API design with greater efficiency. But integrating them safely and effectively will remain the challenge.

The fundamentals of great products haven’t changed: performance, clarity, user experience, and scalability. AI can help, but it can’t replace the thinking that goes into building something strong and sustainable.

The role of AI in app development is growing, and at Devika, we are paying close attention.

Building a tech product and unsure where AI fits in?

Book a free product review – we’ll help you identify what’s solid, what needs work, and where AI can (and can’t) give you leverage.