AI in Software Development: An In-Depth Look

AI In Software Development An In-Depth Look

In today’s technology landscape, advanced tools and resources, such as generative artificial intelligence (AI), have significantly transformed the ways many individual software engineers and business organizations approach software development, making the process faster and more efficient. 

For many engineers, back in the days when they began their software development journey, which was years ago, the methods of learning were quite different from what we see and know today. Although there were some community forums and websites like Stack Overflow, or GitHub to help with, there weren’t as many resources available online as there are today. Some technical questions asked may not be answered until months (or even years) later. 

The journey was even more challenging for software engineers of the previous generations, who began their career in the late 80s or 90s. Those days involved coding in Cobol and Pascal, learning was done mostly on books (with papers and pens), and courses were held on-site only. Online resources like Stack Overflow, or Code Academy did not exist —crafting the profession required a lot of self-study and discipline. 

When encountering a coding problem, those software engineers couldn’t just “Google” for an answer like we do today. Instead, they had to ask for help from a more experienced colleague or run the loops of trial and error until they found an answer.  

Nowadays, the way developers learned about new topics is very different. Having access to a vast resources of online knowledge available also speeds up the process and learning curve significantly.  

More importantly, currently the most talked about and taking the world like storm, AI could elevate the whole process of software development to a whole new level. 

The Introduction of AI in Software Development 

In 2024, many popular AI tools such as ChatGPT by OpenAI, Claude by Anthropic, and Google Gemini are freely available for software engineers to use to assist with their software development tasks. 

It’s also worth mentioning that one of the first AI that became popular in the software development community was GitHub Copilot.

GitHub Copilot was first introduced to the public in October 2021. It was trained with data by using billions of source code that was publicly available. 

For many industries including the software development sector, the adoption of AI seems inevitable. To stay ahead of the competition, it’s important for tech leaders to be aware and stay abreast of new AI trends. 

AI in Software Development: Opportunities & Considerations 

According to a recent report by Grand View Research, the global AI market size is valued at 196.63 billion in 2023 and expected to reach $1811.75 billion by 2030, growing at a CAGR of 36.6% from 2024 to 2030. 

Not only is AI utilized in the software development industry, but it is also enhancing and/or transforming a variety of business processes in other sectors, including Accounting, Education, Manufacturing, etc. 

AI can be across all stages of the software development life cycle (SDLC), from ideation to development, QA/Testing, and deployment. 

Specifically, to assist with a range tasks of coding, GitHub Copilot, Claude, and GPT-4o are among the most common tools today. Many software engineers and software development companies leverage those tools for tasks such as: 

  • Optimizing existing code, particularly useful for complex compound Boolean expressions.
  • Assistance in understanding the functionality of a specific portion of code.
  • Writing regular expressions.
  • Creating pure functions.
  • Creating unit tests.
  • And many more

Still, there are pros and cons when it comes to using AI for software development. For example, because the tool itself doesn’t fully understand the entire codebase or the context of the project itself, being fully dependent on AI for answers may sometimes produce inaccuracies, or bugs and security vulnerabilities.  

Many AI tools suggest developers with relevant real-time coding solutions, thus considerably speeding up the time and effort required to come up with new lines of code. However, many of the times, those coding ideas are still merely suggestions. It’s important for developers to be cautious and verify before implementing them, especially in the production environment since it may introduce new bugs or security loopholes. 

Furthermore, confidentiality and intellectual property protection is also a huge consideration for many enterprises to consider using AI to support their software development.    

AI Beyond Software Development 

AI tools are designed with the idea of helping its users with a broad range of tasks like studying, researching, writing, and more, beyond coding and software development. Having said that, many software engineers can utilize AI to study new programming languages and software development concepts, accelerating the time to improve their software development skills. 

For the time being, AI can assist with many tasks carried out by software developers but does not entirely replace the role of developers, especially for highly complex tasks which require human creativity and team-working skills. AI supplements and complements software engineers by helping with many mundane and repetitive tasks, ultimately improving productivity and results. 

Moving forward, many believe that this is just the beginning of the stage where AI can help humans with coding. We are expected to witness even more advanced capabilities of AI coming out in the future such as automated code generation and AI-driven software testing and beyond.