If you're considering your next app development project, you're probably wondering, "Should my app developers be using AI to move faster? Wouldn’t that save me a boatload of money?"
This article helps you understand the factors to consider when working with software teams that might use AI to develop your app. I want to help you know your potential cost savings, avoid the pitfalls of “too much AI”, and set realistic expectations with your app development team.
AI could shave 20%+ off your app development costs
AI is increasing productivity everywhere. More likely than not, the phone you carry in your pocket has it integrated into the experience. It has found its way into search engines, image and video generation and even into your developer's code editor.
All this is saving us time and money, so shouldn’t this apply to app development, too?
The answer isn't straightforward, so I want to break down what it can do, what it can't do, how your team should use it, and ultimately, what it means for your software development project.
I've been building software for almost two decades. In that time, I've seen significant shifts in what we create, from software moving from desktops to the cloud, the rise of software as a service, and the explosion of mobile apps onto the scene. But how we build software hasn't changed much.
Until now.
The rise of AI-assisted tools has been one of the most significant changes to how we work in years. Some say AI will replace developers. Others think it's just the next autocomplete. In my opinion, neither view is quite right.
What we're seeing is a shift in how work gets done, not who does it.
Yes, AI is fast. It saves us time, we think around 20% on average in day-to-day tasks. So in theory, that’s going to save you 20% of your app development cost.
It could be more. According to a recent GitHub survey, some developers are reporting up to a 55% increase in productivity. But no, it's not writing your app while you make a coffee (a.k.a. Vibe Coding). And it doesn't solve complex problems by itself.
AI is replacing books and traditional learning
Before this new wave of tools, developers had to grind through knowledge gaps the old-fashioned way.
If you started as a developer in the early 2000s, your desk was probably stacked with O'Reilly books. Later, online documentation and forums became your most frequently used bookmarks. You would bounce between ten browser tabs, trying to find a blog post that wasn't over 5 years old, or just spend hours trying to understand poorly written code. If you were lucky, someone in the office knew the answer. If not, you talked to a rubber duck and hoped clarity would arrive.
Now? Developers can type a question into an AI assistant and get an answer (not always correct, mind you) in seconds.
Whether it's a code snippet, an architectural summary, or a comparison between two SDKS, the information comes faster.
That doesn't mean you can skip the thinking part, but it does mean less time searching and more time building.
Using AI in app development is good news for customer satisfaction and time to market
If you’re a technology leader, you’ll know that poor code quality will eventually cost you; adding new features will take ages. Customers will report more bugs. Costs will go up, and everything will take twice as long.
AI means that today's development environment is more streamlined, more productive, and, in the right hands, more creative. Tools like CoPilot can autocomplete entire functions. ChatGPT and Claude can explain complex code, help debug tricky issues, or generate test cases in minutes.
Other tools, like Cursor, even embed AI directly into your coding workspace, allowing you to refactor or document code without leaving your editor.
And it's not just about code; these tools can also help developers:
- Write clearer documentation/unit tests
- Understand unfamiliar codebases
- Explore APIs faster
- Onboard into new projects without slowing others down
This means positive things for you and your app venture, which we’ll explore next.
AI development is great news for product quality, customer satisfaction and go-to-market timelines
These are no longer just gimmicks; they offer real advantages that are only improving over time. The Aider Polyglot benchmark is designed to test the ability of various AI models to complete over 255 exercises in different programming languages. This benchmark has seen accuracy improve from just 3.6% to over 70% in under a year. Note, however, that these are discrete questions focused on siloed exercises, rather than interwoven, complex problems to be solved.
Recently, I needed to debug an issue in an old app of ours. Nobody on the team was available who had originally worked on it, and it was written for a platform I have no working knowledge of. This could have taken me hours to work through and solve, but using these tools, I had a summary of what the code did and the likely cause of my issue in seconds, not hours.
AI helps speed up app development
Slow development can kill any app venture. Luckily, AI is excellent at automating the repetitive and routine parts of development, making them faster.
Generating boilerplate code, scaffolding out components, or building rough drafts of new features, all of that gets easier. I have several routine tasks that I need to complete before submitting my code for review. They're not taxing work, but they do take time, and now they can be done with the help of AI, instantly.
It's also great when you're exploring something new. You can ask, "What's the difference between X and Y?" or "How do I structure a project for platform X?" and get a reasonable answer that would've taken you much longer to arrive at on your own.
And when you just need an answer to the question, "Is this even possible?" AI helps you move from idea to concept much quicker.
But there's a ceiling, which we look at next.
What AI can't do for software development projects
If you’ve built a tech team or worked closely with one, you’ll know that accumulating knowledge is crucial for development speed and uptime.
This knowledge is where AI falls down.
It doesn't know you, your product or, more importantly, your customers (as Anna wrote recently on the dangers of using AI for user research).
You can certainly provide it some information about these things, but it can't understand the nuances of your domain, the quirks of your existing systems, or the decisions your team has already made. It won't know that your customers care more about reliability than speed, or that one of your services is still running on an outdated third-party system with its quirks.
You probably also care about uptime and offering bug-free software. AI won’t always help here. It struggles with complex debugging. It can make educated guesses, but it can't trace subtle bugs through multiple services or understand why a system fails intermittently only in production.
Remember we talked about time-to-market? Well, the right software architecture can make all the difference. Sadly, AI doesn't make great architectural decisions. Not only that, but it won't warn you that your code sprawl is getting out of hand, or that your current approach will blow up as it scales.
Above all, AI doesn't write maintainable, understandable code that fits into a broader team culture.
That still takes skilled people who can balance budgets, tradeoffs and quality.
A Human in the loop is non-negotiable
Most tech leaders want to benefit from AI to reduce costs and speed up. The best results come from leveraging the strengths of humans and AI.
A good developer does more than write code. They ask questions, understand the problems, identify issues early, and design solutions that stand the test of time. None of that goes away with AI.
If anything, it's more important now than ever.
You still need humans to review what AI suggests. We already have a practice where we review each other's code, and AI is no different. In fact, it often requires more scrutiny because its suggestions look correct, even when they're subtly wrong.
Beyond reviewing code, humans need to be involved to make the real judgment calls, such as:
- Does this feature fit the product vision?
- Will this scale?
- Will this make sense to the end user?
- Is this solution secure?
That's where experience and product intuition come in. AI can assist, but not replace that kind of thinking.
The risks of over-reliance on AI in software development
You might remember that I already touched on the issues that will occur when people treat AI as a magic wand; code gets shipped without proper review. Teams rely on it too heavily and start to lose understanding of their systems.
This happened without AI, too. Before AI, people would copy and paste from Stack Overflow without fully understanding what the code did. The result was fragile products, technical debt, and plenty of firefighting down the line.
AI takes that risk and amplifies it. If you're not careful, you can bake critical issues into the foundation of your projects that only show up when your app is live, or worse, when you scale.
There's also the risk of exposing sensitive data or intellectual property. Depending on which tools you use and how you configure them, your prompts or code snippets could be shared with external companies. That matters when you're dealing with internal logic, business rules, or customer data.
To combat this, we’ve created our own AI policy that governs how and when we will integrate AI tools into our development process.
Tobin, our Managing Director, often reminds me that we’re not just a software company, we’re a communications company. 90% of what goes into building successful apps is all about communication.
So, should AI build your app? Yes, to a degree.
As a tech leader, encourage and enable your product development team to get close to AI and learn when, and more importantly, when not to use it.
AI is here and it's here to stay. It's fast, helpful, and getting better all the time. But it's not a substitute for experience, critical thinking, good product knowledge, or effective communication. It's becoming one of the most valuable tools in our toolbox, but it still needs direction. It can't build the thing you're imagining unless someone experienced is leading the way.
Expect them to think, collaborate and make decisions on tough problems. We’re not alone in this view, and that’s what we do.
If you need a team that enhances productivity with AI without losing the all-important human touch, get in touch!
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