Since the release of ChatGPT, there has been a great deal of hype around generative AI and how companies can leverage it to cut costs and democratize software and application development. Naturally, with discussions of cost-cutting and democratization come whispers about what will happen to software developers.

This is a real and valid concern, but software developers’ skills, expertise and creativity are still very much needed.

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While generative AI and AI code generation tools like ChatGPT have shown some promise and potential benefits, they are still in their infancy—like many other innovative technological advancements. We also don’t know what scenarios they may present down the road or their true abilities when the technology matures. For instance, how will it integrate with other technologies? We don’t know what will happen when a ChatGPT-generated line of code breaks or needs to be changed. We don’t know if it can provide a novel solution to a unique problem or what security threats it will present.

Given these unknowns, technology executives should think twice about replacing experienced and creative technology talent, such as software developers, with AI code generators.

Will ChatGPT create novel code to solve a unique problem never encountered before? Probably not.

A Tale as Old as Time (Or at Least a Decade)

The technology industry has been searching for and developing new ways to make certain software development tasks much easier and more streamlined for years. One example of this is low-code/no-code.

The notion of simplifying application development and replacing software developers with laypeople (citizen developers) has been around for more than a decade now, as low-code and no-code solutions have grown more popular. These solutions have promised that companies don’t need technical talent to get their software and app projects off the ground.

However, if you look at the impact of these solutions today, their use can result in large amounts of technical debt and almost always require the skill of experienced software developers.

The reason? Building complex software and applications is extremely difficult; it’s an art.

Low-code and no-code solutions have their rightful place and can make things easier if a company is looking to launch a simple app or static web page. These solutions can increase the pace of development and time-to-market and enable everyday people without any development skills to facilitate them. However, they are not actually a complete solution and often overlook aspects of development that a human software developer would typically address. Without a skilled expert involved, low-code/no-code platforms often can’t solve a unique problem a company has.

So, how does this relate to AI code generators like ChatGPT? Here’s how.

A Similar Situation—With One Key Difference

When thinking about their place in the development process, AI code generators are not that different from low-code or no-code solutions. The thinking is that they will also enable non-technical individuals to create software and applications with ease.

Yet, there is one key difference—they promise expertise, too. But is the expertise coming from the AI code generator or the person piloting it? The answer is simple; it is not from the code generator.

There have been examples of companies and individuals that have tried using ChatGPT to build code, and they have appeared to be successful. However, without the input of the individuals using it, it never would have been able to create the code on its own unprompted.

This means that the expertise of skilled, human software developers is still very much needed, especially when building intricate software and apps that require complex functionality such as optical character recognition (OCR), internet-of-things (IoT) connectivity and more.

A Future With Software Developers

Because of the expertise still required to create elaborate and innovative software and applications, AI code generators will not replace software developers anytime soon, if ever.

The technology used in these tools is still in its infancy, presenting many lingering questions and potential challenges. We will see this confirmed by the trials and tribulations experienced by the few companies and executives attempting to replace software development teams with tools such as ChatGPT.

Knowing AI code generators follow a similar path as low-code and now-code solutions, companies and executives should use them as developer enablement tools. These tools should complement the work of software developers by empowering them to focus on the complex tasks software and apps today require.