Will AI Replace Computer Programmers?

AI tools are reshaping programming, automating tasks from bug fixing to full code generation, and leaving many developers wondering if their jobs are safe.

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Have computer programmers innovated themselves out of a job? That’s the fear driving theories that AI will remove the need for humans who can write computer code.

Today’s most sophisticated large language models like GPT-4o and Claude Sonnet are just as fantastically efficient at coding as they are at drafting emails and essays in human languages.

Anthropic CEO Dario Amodei recently said he believes AI will soon be writing 90 percent of all code. And Amazon CEO and President Andy Jassy said his company will hire fewer software engineers thanks to AI.

So does this mean that learning to program—since the start of the computer age, an accessible gateway to a lucrative career for many—is pointless now?

Regardless of the capabilities of today’s AI, is there any way that someone setting out to learn software development now can hope to be able to compete with the AI coders of five years in the future?

With 30 percent of coders saying they believe that AI will replace them, there’s fear and uncertainty in the air, but how does this affect the reality of the situation? Let’s take a look:

Why Are Programmers Worried They Will Be Replaced?

Evidence certainly seems to be growing that generative AI tools can carry out many of the tasks associated with coding and programming. Commonly cited use cases include creating new code, optimizing existing code, detecting bugs, explaining code, maintaining documentation and detecting security vulnerabilities.

Although quantitative research is limited at this point, one study found that programmers assisted by Microsoft’s AI coding assistant, GitHub Copilot, have been able to complete tasks 55 percent faster than those without.

It’s frequently speculated that entry-level programming roles are the most likely to be affected because their work is more easily automated. Senior roles such as team leaders and lead engineers, requiring a broader skillset and the ability to deal with strategic challenges, may be less exposed. But there’s still the question of where the next generation of human software development leadership will come from if there are no jobs for beginners!

According to the Washington Post, computer programmer jobs have declined by almost 30% compared to the previous two years. It’s important to note that this isn’t reflected in the figures for software development as a whole, which has declined by only around 3%. Jobs with the title of “programmer”, however, are more likely to be entry-level roles that can more easily be replaced by automation.

This does point towards the possibility of major shifts in the labor landscape. But it also gives anyone who programs computers for a living useful clues about what they need to do to stay relevant.

Evolving Roles

The truth is that the role of the programmer, in line with just about every other professional role, will change. Routine, low-level tasks such as customizing boilerplate code and checking for coding errors will increasingly be done by machines.

But that doesn’t mean basic coding skills won’t still be important. Even if humans are using AI to create code, it’s critical that we can understand it and step in when it makes mistakes or does something dangerous. This shows that humans with coding skills will still be needed to meet the requirement of having a “human-in-the-loop”. This is essential for safe and ethical AI, even if its use is restricted to very basic tasks.

This means entry-level coding jobs don’t vanish, but instead transition into roles where the ability to automate routine work and augment our skills with AI becomes the bigger factor in the success or failure of a newbie programmer.

Alongside this, entirely new development roles will also emerge, including AI project management, specialists in connecting AI and legacy infrastructure, prompt engineers and model trainers.

We’re also seeing the emergence of entirely new methods of developing software, using generative AI prompts alone. Recently, this has been named “vibe coding” because of the perceived lack of stress and technical complexity in relation to traditional coding.

In truth, these are really just new methodologies that require developers to focus on more strategic tasks like project management and program architecture, rather than the nuts and bolts of getting code to do what we want it to do.

The term is sometimes used by traditional coders in a derogatory way to imply that those coding with AI are scared of getting their hands dirty with “real” coding. However, the practice also serves as an indicator of how software development is likely to change, and what skills coders and engineers should be developing now if they want to remain relevant.

A glimpse of one potential future is provided in this quote from Adjrej Karpathy, director of AI at Tesla: “A large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feed neural networks.”

Myth Or Reality?

Software development and programming jobs are not going to disappear, in the short term at least.

But the role will change immeasurably, and there are firm clues in place as to the direction of that change.

What’s the key learning here? I’d say it’s that the ability to learn new skills and continuously stay ahead of change is the one skill everyone involved in programming, software engineering and development needs to develop if they don’t want to be left behind.

Creativity, innovation and real-world problem-solving skills are vital to ensuring AI can be used to improve people’s lives. While I believe emerging and future generations of AI technology will deliver wonders, humans will still be at the heart of the process. Partly this is down to the ethical responsibility to ensure there is always human oversight.

But also because it will be some time (if ever) before AI has the strategy-focused, people-centric skills needed to replace programmers.