Is AI Going to Replace Programmers (Answers all your questions)

Anywhere you look, somebody is talking about AI. AI has made a game-changing impact in the last 3 years to the world and to the software industry. From writing code snippets to helping make more important decisions. Is AI going to replace developers? It's a fair concern. After all, automation is everything. Automation saves time and money. In fact, a 2021 McKinsey estimate suggested that "45 million U.S workers can be displaced by some kind of automation by 2030."

So, no one should judge the people who are asking these questions.

Why are programmers worried

Well, AI tools are capable of producing code, aren't they? They can mimic human conversations, so it's natural to wonder if software developers will be one of those replacement guys.

The big picture of AI replacing programmers

AI is all about automation eff, efficiency, and cost reduction. So it's not about making something that does our job in higher quality. It's about making something that can harness the computing power to do things faster, and thus, it'll be more accessible. It's an important thing to remember. The goal of AI is not making a robot that does things better than you; it's about making something that can think and reason faster and more efficiently; it's not about quality. It's about time.

So, if you think about it for a second, you will realize that even if (and that's a big IF) AI would replace someone, it probably won't be due to its higher-quality output. For example, it can replace taxi drivers but not race car drivers. So, the first thing that comes to mind is to be a rally car driver in your field.

To understand what I mean by that, let's first check what AI can and cannot do now at the march of 2025

What is AI capable of in the software industry (march of 2025)

• It can generate boilerplate code for tasks
• It can debug code and detect problems
• It can generate code snippets
• It can help you make better decisions by weighing out the options
• It can give solutions to a pre-existent and pre-solved problem

What AI isn't capable of in the software industry

• It can't guarantee the quality of an app
• it can't design High-level system architecture (without fault)
• It can't guarantee the security of a code snippet
• It can't suggest truly creative solutions to problems
• It can't turn ambiguous or fuzzy requirements to models
• It can't lead your software team
• It can't be accountable or responsible for it's codes or solutions
• It can't detect context-dependent bugs

To wrap it up, it can't do what higher roles of software engineering do at all, and it can't do what mid-level or senior developers do without supervision. Let's talk about why is that. Why it can't do that yet?

The WHY behind AI's limitations

I'm not an AI expert, but I know AI's knowledge is based on the model it has been trained with. A pre-existing model can only have pre-existing knowledge of the world. So, AI will probably always be a step behind when it comes to true innovation.

Let's list the why behind AI's limitations:

Limited Holistic understanding

AI works by detecting patterns in data without understanding the broader context; that's just how it works. This means it can't guess or have a true grasp of how different parts of a system affect each other, especially in the long term. That's why, in some countries, using AI-generated code in software products that can impact people's health or safety is highly discouraged and even prohibited in some companies.

Difficulty interpreting Ambiguity

AI models need clear, well-defined input because they understand you through analyzing the language. They can't interpret ambiguous or incomplete requirements, and they sure as hell can't guess or prioritize requirements from listening to a customer's tone of voice. And many times in software engineering, you will encounter that. That's kind of the whole point of the RE and analysis phase, to understand what the user needs or wants and turn it into a software model that designer would understand.

No emotional intelligence or team skills

Emotional intelligence involves having feelings, subjective experiences, and self-awareness. AI systems are basically algorithms that process data; they do not have consciousness or personal experiences, so they cannot feel emotions like a human.

How do developers feel about AI

Based on a survey in 2023, 92% of developers are using AI coding tools only 13.4% of them feel threatened by AI.

The reasons we've just went through are why the vast majority of developers think that AI will not replace humans. But will enhance the efficiency of programmers.

Will AI take any job in the software industry

Well, in my opinion, it has already taken jobs away! Note that It's a different question than "Will AI Replace me". in our latest project, we did a website redesign and I had all of our frontend developers working on another project. First, I considered adding a freelancer developer just to do this project, and my co-worker pointed out to me that since the AI can create the boilerplate theme's code from our design, it can be done quicker than we thought!

Well, that's just a simple example of how improved efficiency can reduce the need of scaling up and hiring new developers. But:

New AI fields need new programmers

The AI will create new categories of work, and whether they will be exactly like the old jobs or not is unclear. These two horizons here are the most arguments:

1-      AI would make it easier to create software. Therefore, the cost of the software would be reduced a bit, and more businesses would need software of some kind, and the demand would rise.

2-      AI would be a necessity for businesses, and therefore, they need to make some kind of software so they can use or offer the AI on that platform.

Will those numbers beat the jobs that AI will destroy?

There are numerous sources that support that, but we can't predict the future precisely.

One of them is the World Economic Forum, which said that 85 million jobs "may be displaced by a shift in the division of labor between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines and algorithms." 

I am not sure what those jobs would be; in my opinion, it's not possible to predict all the categories that would be created if AI reaches a certain level, let alone predict the number of job demands in that area. Because it's not there yet! Maybe that's simplistic thinking, and an AI expert can elaborate more on this, but all I'm seeing on the internet are vague guesses or general research that are not specified in the tech industry.

So what should we do?

We should use AI as a tool and learn and take a more human-oriented, nonautomationable approach to software engineering if we want to be completely safe. AI has serious limitations, whether it's holistic or even power generation problems (not enough power in the world to support commonizing a true AGI). They will play a role in the future of the software industry. The most solid argument against AI taking over the programming world is that a software engineer has skills that AI cannot reach due to its limitations. So, being a software engineer is the best way.

Now, let's talk about the effect of AI in certain software job positions.

AI in Backend Development

Backend developers write the server-side logic that powers applications — everything from database interactions to API endpoints. These tasks often involve a lot of boilerplate code and repetitive patterns. Here, AI shines as a productivity booster. One of the most compelling advantages of AI in backend development is its ability to automate repetitive and time-consuming tasks, allowing developers to focus on higher-level challenges.​

For example, modern AI-powered code generators (like GitHub Copilot or Amazon CodeWhisperer) can whip up routine code snippets in seconds. If you need a quick function to handle user authentication or an API call, an AI assistant can suggest a template almost instantly. This not only saves time but also reduces human error in writing mundane code. As a result, the backend engineer can spend more energy on designing robust system architecture and optimizing performance rather than typing out boilerplate for the hundredth time.

AI in Frontend Development

Frontend developers build the parts of software that users see and interact with — web pages, user interface components, mobile app screens, and so on. It's a discipline that blends technical skills with creativity and understanding of user experience. How does AI factor in here?

From Design to Code

One exciting use of AI in front-end development is bridging the gap between design and code. We now have AI tools that can analyze a design mockup (say, a screenshot or Figma file) and automatically generate the corresponding HTML/CSS code. For example, experimental AI systems can take a picture of a website design and spit out a rough HTML/CSS layout that matches it. This kind of design-to-code automation has huge potential to speed up the slicing of designs into working web pages. Instead of hand-coding every CSS style from a designer's specs, a frontend dev could let AI draft it and then refine the result. Similarly, AI-driven frameworks can suggest UI component code (like React or Vue components) based on common patterns.

However, today's generative AI isn't a frontend panacea. Seasoned developers will tell you that automatically generated HTML/CSS often needs significant tweaking. Layouts need to be responsive to different screen sizes (an area where AI often falls short), and ensuring cross-browser compatibility or accessibility requires careful human oversight. In practice, AI can quickly produce the first 80% of the frontend code, but a human developer is usually required to polish the remaining 20% to meet quality standards. The AI is going to replace programmers for tedious tasks like converting a style guide into CSS classes, but it's not replacing the creativity and precision that go into a refined user interface.

AI in Mobile Development

Mobile app developers write software for smartphones and tablets, working with platforms like iOS and Android. These roles often require knowledge of native SDKs (Swift/Objective-C for iOS, Kotlin/Java for Android) or cross-platform tools like Flutter and React Native. How is AI impacting mobile development, and could AI replace mobile programmers?

Rapid Prototyping and Code Generation

One way AI aids mobile developers is through rapid prototyping. There are AI-powered app builder platforms emerging that let you describe an app idea in plain language and get a working prototype out. For example, you might tell an AI, "build a to-do list app with user login and a task list," and it could generate a basic app structure with some screens and navigation. This sounds magical — and it is a great starting point — but these AI-generated apps are usually very rudimentary. They handle generic features but lack the polish and custom logic real-world apps need. A mobile developer can use such a prototype as a foundation then manually implement the nuanced functionality (like integrating a unique business logic, optimizing performance, or simply following best practices of the platform). In short, AI can jump-start mobile app development by handling boilerplate setup, but it doesn't replace the need for an experienced app developer to finish the job.

AI coding assistants (like Copilot) also work in mobile development environments. An Android developer in Android Studio or an iOS developer in Xcode can use AI suggestions to write code faster. Need a quick function to fetch data from an API or a snippet to format a date in Swift? AI autocompletion can often provide a correct answer in real time based on patterns learned from countless open-source projects. This speeds up coding significantly. As with other domains, AI's strength is in writing those common, repetitive pieces of code so developers can focus on app-specific functionality.

AI Features in Apps vs. AI as a Developer

It's useful to distinguish between AI as a feature in mobile apps and AI as a developer tool. Many modern apps have AI-powered features (like voice assistants, photo filters, or personalized content feeds). Mobile developers increasingly integrate machine learning models into apps to enhance user experience. This means the mobile dev role now often involves working with AI — but on the implementation side (using AI APIs, tuning models for the app), not ceding the programming work to AI.

Could an AI someday completely build a complex mobile app from scratch? Possibly in the far future, but not today. Building a successful mobile application involves more than just writing code: it requires understanding user needs, following platform design guidelines, rigorous testing on many devices, and iterative refinement based on user feedback. AI doesn't have the intuition for user expectations or the creative vision for an app's identity. So, while AI might generate chunks of Swift or Kotlin code, mobile developers are still very much in charge of the overall app development process. In reality, AI is going to replace programmers in the mobile space no more than an iPhone's autocorrect replaces a writer — it speeds things up and prevents mistakes, but the ideas and critical decisions come from the human.

AI in UI/UX Design

Not all roles in software development are strictly about coding. UI/UX designers focus on user interface and user experience design – deciding how an application should look and feel and how users should navigate through it. With AI tools now capable of generating designs and even artwork, some designers wonder if AI will replace them, too. Let's see what the landscape looks like for design roles.

AI Design Tools and Their Limitations

AI is making impressive forays into design. Tools like generative adversarial networks can create UI layouts or suggest improvements. There are AI-driven design assistants that can shuffle around elements in a layout for optimal spacing, or even platforms where you sketch a rough wireframe and an AI turns it into a polished visual design. Additionally, generative image models (like DALL-E or Midjourney) can produce unique icons, images, or design assets based on prompts. This has led to speculation that a future AI might handle end-to-end design tasks.

However, the general consensus is that AI will not remove the need for UX design, nor will it replace human UX designers.​

Why? Because design is deeply human-centric. Good UX design hinges on understanding human emotions, empathy, and user behavior — areas where AI has no genuine intuition. Designers excel at conducting user research, feeling the frustrations and needs of users, and translating that into better interfaces. An AI can crunch data and even mimic a style, but it doesn't truly understand why a design works or not on a human level. As the UX experts put it, UX design is one of the most human-centric jobs; it requires empathy and an understanding of human psychology that "only humans can offer."​

It's hard to imagine an algorithm, no matter how advanced, fully replacing the creative collaboration and user empathy that goes into UX work.

Collaboration of Designers and AI

Instead of replacement, what we're seeing is collaboration. AI is becoming a helpful design assistant. It can generate lots of design variations quickly, helping designers explore ideas. It can handle tedious tasks like resizing assets for different screen sizes or checking color contrast for accessibility. AI can analyze heaps of user data (click patterns, heatmaps) and highlight areas of a UI that might be causing user pain points, which a designer can then address. In essence, AI can provide the data and drafts, and the designer provides the vision and final judgment.

Some designers are already leveraging AI tools to boost their efficiency. For example, AI plugins in tools like Figma can suggest design tweaks or even generate dummy content for mockups. These speed up the workflow but still keep the designer in control. Rather than fearing "AI design robots" taking over, many UI/UX professionals see AI as another tool — much like how software engineers see Copilot. It does the heavy lifting for certain tasks, but the creative, high-level work remains with the human. So, while AI might change how designers work (just as Photoshop did decades ago), it isn't poised to make designers themselves obsolete. Human creativity and empathy are still the cornerstone of great design, and those aren't skills you can download to a machine (at least not anytime soon).

Conclusion: The Future of Programming

So, is AI going to replace programmers? Based on everything we've seen across various roles, the answer is no — at least not in the foreseeable future. AI is undeniably changing how programming is done. It's writing code, catching bugs, and even making design suggestions. It's making developers of all stripes more productive. However, the core value of human programmers remains. As one industry report succinctly put it, "The true value of a programmer is knowing what to build" — understanding problems, devising solutions, and interpreting business needs — and it will be a long time before AI can fully grasp that level of understanding​

The human programmer will always play a role in steering the ship.

In fact, many experts argue that fears of AI displacing programmers are overblown. We've seen automation fears in the past (remember when people thought high-level languages or IDEs would eliminate programming jobs?), yet new technologies usually create new kinds of jobs rather than only destroying old ones. The introduction of AI is following a similar pattern. The World Economic Forum predicts AI will displace some jobs but create even more new ones — about 97 million new roles by 2025 in tech and related fields, including roles for people who can harness AI effectively. In the programming world, developers who know how to work alongside AI will be in higher demand. Already, we're seeing new specializations emerge (AI ethics, prompt engineering, AI model integration specialists, etc.), which are opportunities for today's coders to upskill rather than signs of unemployment.

Crucially, AI tools still need supervision. Developers are finding that while AI can generate a lot of code, it's not always correct or optimal. In one survey by Codesignal, 55% of software engineers expressed concerns about the quality of AI-generated code.​

In other words, AI isn't here to take your programming job — it's here to make it more interesting. 🤖