AI in Coding: What Does the Future of Programming Hold

With the release of ChatGPT and similar platforms, artificial intelligence (AI) it’s now possible to generate content on a large scale in seconds — including software code.

This may be the turning point many companies were waiting for before implementing AI in the workplace.

For many software developers, AI has the potential to improve their processes and make them more productive while relieving most of the heavy lifting from their programmer’s hands.

But what exactly does the future of AI and programming hold? Let’s take a deep dive and find out.

Can AI Change its Code?

So, AI tools can write code, which means they may have the potential to create new programs from scratch.

But can AI platforms change their own code?

Before answering that, it’s important to understand the trajectory of this breakthrough.

At the end of 2022, Google’s engineers created an AI platform that could write lines of code.

Although the code was relatively simple, this represented a significant advancement as AI had the potential to be used to enhance human work in programming, just like in healthcare and other areas.

With the above in mind, the initial iteration of the coding-capable platform was simple. For instance, it was able to solve 34% of the problems presented to it through code, which is impressive. However, this is still below-average human performance.

The resolution rates of AI platforms have undoubtedly increased since then, but we’re yet to see an AI tool in a live environment that’s capable of writing complex code.

Likewise, we still have not been introduced to an AI tool that’s capable of self-modifying its model architecture, learning dynamics, or computational capacity.

Can AI Write Better Code Than Humans?

As we just explained, AI’s ability to create code is relatively new. This means that this feature has not been perfected.

In simple words–AI can’t write better code than humans. But it’s also important to understand that this isn’t the ultimate goal of AI usage in programming.

Instead, AI developers are creating tools that will help other programmers and creators build powerful solutions with less effort.

How AI is Changing Software Development?

AI tools like chatbots have the potential to increase productivity by as much as 40% in certain business processes. So, what can it do for software programming?

As for now, AI is already a great tool that helps developers do their jobs more efficiently.

Rather than taking away opportunities, AI technology will aid programmers in completing necessary yet repetitive tasks during the coding process.

In this sense, AI works more similarly to a superior work tool, like a traditional farmer who purchases their first tractor or harvester.

This means that developers still have to do the leg work, like collecting data. This may include steps like analyzing Nord vs Surfshark VPN to access GEO-blocked resources or getting other tools to write sufficient code. Check out this guide to learn more about VPN.

What is the Future of Coding with AI?

It’s estimated that 30% of all developers already use AI bots during the testing and quality assurance phases of their software development processes.

Tools like GitHub Copilot or Tabnine are preparing to enable embedding in integrated development environments.

This will allow developers to leverage AI more often in their coding, improving both the efficiency of these tools and AI adoption rates in software development.

Pros and Cons of AI in Coding

More than 90% of leading businesses invest in further developing their AI, which indicates that smart technology can represent a huge competitive advantage.

However, there’re certain setbacks to using AI in coding. Let’s take a look.

Advantages of AI in Coding

1. Better Debugging and QA Processes

Debugging and quality assurance (QA) is necessary to ensure the success of every software project. AI can handle the heavy lifting, alerting programmers to areas needing attention.

2. Improved Software Testing

Similarly to the processes above, testing ensures that your platform operates as intended. Smart tools can handle the most work-intensive part of the test, allowing you to focus on spot checks and report verification.

3. Superior Security Levels

Adhering to rules like the GDPR regulations and maintaining high-security levels is essential. Fortunately, AI tools can help you test for vulnerabilities and create robust security systems within your applications.

4. Boost in Code Accessibility

Code accessibility can be described as how easy it is to implement software tools into your business. AI has boosted accessibility across the board thanks to solutions like chatbots for both external and internal requests.

Disadvantages of AI in Coding

1. Inaccuracies During the Data Learning Process

The knowledge of an AI tool depends directly on the database it has access to. Since no database is fully comprehensive, all AI systems have the potential for inaccuracies of various degrees.

2. The Black Box Model Issue

Advanced AI models that veer from linear combinations are extremely difficult, if not impossible, to explain. Since the computing system can’t be dissected, it creates what’s known as the “black box issue,” which reduces transparency in the code.

3. Lack of Creative Oomph

So far, AI has demonstrated a lack of creativity, which is necessary to create complex software architectures.

4. Elevated Costs

Finally, the computing power required to run smart software translates to elevated energy consumption. This, in turn, contributes to the high cost of AI tools.

Conclusion

Undoubtedly, AI is already influencing how we code software, and this impact will only grow.

But to what extent will AI impact software development?

As we mentioned earlier, tools that employ machine learning and other forms of artificial intelligence are ideal for performing repetitive tasks.

So, rather than taking over jobs, these tools will actually enable programmers and developers to spend less time reviewing and editing written code.

With that said AI should be viewed as a great resource by developers.

In addition to simplifying time-consuming manual tasks, this technology can also reduce review and testing time significantly. However, it also has certain limitations that may be resolved in the nearest future. The most important thing is to ensure that your team understands its current limitations while staying updated with and adapting to new capabilities as they roll out.

It’s likely for software development and technology as a whole to be among the main industries that utilize AI for the majority of tasks.