The Role of AI in Software Development

Since exploding onto the scene in late 2022, Generative AI (GenAI) in software development has helped create innovative solutions that have accelerated production across almost every industry.

Healthcare AI, for example, has helped providers improve their quality of care and overcome challenges in interoperability, security, and compliance.

GenAI has even caused a major technological shift in custom software development.

A survey on GitHub reported that 92% of software developers based in the US use AI-driven coding tools to accomplish professional and personal work. About 70% also believe that AI coding tools have given them an edge at work, helping them be better team players while avoiding personal burnout.

The Stack Overflow Developer Survey 2024 noted that 76% of developers reported using AI in their development process. Roughly 82% of respondents AI to write code, while 57% rely on it for debugging. Only 12% use it for project planning.

AI skyrockets productivity in terms of complex coding tasks. A study showed that programmers using AI could code up to 126% more projects weekly.

These numbers and advances are not merely trendy shifts but fundamental changes in how software is developed and distributed. Let’s explore the growing role of GenAI in software development.

3 Examples of AI in Software Development

Software developers benefit from AI operational efficiency, thanks to AI’s robust computing power and large storage, which process data quickly and efficiently. Here are the top ways AI streamlines and accelerates a developer’s work.

Code Optimization

AI algorithms excel in analyzing massive amounts of code to identify patterns, disorganizations, and possible optimizations. A software development company can use AI tools to refactor code, boost performance, and reinforce maintainability using these identified sets. AI tools can also uncover bugs in the code that may cause problems in the future, as well as suggest ways to fix or improve the problematic code. Further, they can make the code operate faster and better independently. Ultimately, AI helps software engineers write code that is easier to understand, fix, and update.

Debugging

One of the critical aspects of custom software development, as well as mobile app development, is debugging. AI tools can identify potential errors using code patterns, look into historical data, and evaluate user behavior. Using AI and predictive analytics, developers can pinpoint where the bugs are likely to transpire, suggest solutions, and tackle them based on severity. AI facilitates a proactive approach to finding and fixing bugs before they cause major problems, making the software or app more reliable and stable.

Natural Language Processing

Another excellent example of AI in software engineering is using natural language processing (NLP) in coding. NLP technologies let developers create and refine code using natural human language, making writing and understanding code more natural and accessible. For example, an AI-powered code completion tool can create snippets using natural language descriptions, making coding faster and minimizing human errors. Additionally, NLP can help improve code by figuring out what the code should do and offering suggestions to improve it (refactoring).

Collaboration and Delivery

AI makes continuous delivery possible. Agile teams can use AI to quickly write code and create pull requests for their teammates to review. AI tools can also improve communication and knowledge sharing among team members. This dual approach boosts productivity and helps avoid delays. By working better together, AI can help teams be more flexible and quick, allowing them to provide value to customers faster and more efficiently.

Opportunities for Growth and Associated Dangers

AI brings both growth opportunities and risks to custom software development. To see its full impact, let’s examine the opportunities and dangers of AI.

Opportunities

Software developers cannot fully rely on AI to develop software. They can instead optimize its use via quality prompts. A software development company can use the expertise of a prompt engineer to create inputs that produce the most relevant and insightful responses. Here are sample prompts that AI in software development excels in.

• Repeated Tasks: AI can complete repetitive tasks with well-defined prompts. Having an AI tool handle repeated tasks frees developers to focus on complex processes that AI can’t handle.
• Initial Draft: Sometimes, software engineers also get writer’s block. When developers aren’t sure how or where to start or having problems with a flow state, an AI-generated code can be a good place to start.
• Minor Edits: AI tools in coding can handle small edits and refreshes. Developers can use AI routinely to scan for bugs, update prewritten programs, and adjust codes based on fresh criteria.
• Improve Cycle Times: AI can accelerate the software development lifecycle. It provides fast feedback and helps analyze business plans. By tracking how projects are doing, AI can make better predictions and find the best way to finish tasks.

Dangers

Despite the advancements of AI in software development and DevOps, it can’t outpace human developers. AI weaknesses include:

• Manage Complex Coding: Some programs require developers to multitask. While AI can juggle multiple prompts, it still struggles with complex coding requirements.
• Context and Nuances: Because AI is a machine, it doesn’t understand a team’s unique preferences, needs, workflows, and quirks. AI lacks the contextual awareness to ensure that the responses it produces meet the standard and security of the team. It also doesn’t understand nuances, so its responses may not perform well in the real world. For instance, it may produce technically acceptable code but not consider specific security protocols to protect sensitive data. This misalignment can be costly in the end.
• Autonomous Action: AI relies heavily on user prompts. It can’t produce an output without an input, and its response is only as “smart” as the prompt it received.

The Value of AI in Software Development

Artificial Intelligence isn’t going anywhere. It has already proven its value in various industries. Beyond healthcare, AI-powered tools are becoming go-to solutions in finance, real estate, transportation, manufacturing, and software development. AI can create major changes in software engineering practices. To keep up with your competition, your business needs to adapt to these changes.

But let’s be clear: AI can’t completely replace human developers. Even with its advancements, it has major limitations, so knowing when and how to use AI effectively is essential. A smart investment is working with a custom software development company that employs skilled developers familiar with AI.

The best results still come from a combination of AI’s efficiency and human creativity. You can achieve outstanding results by integrating AI’s productivity with developers’ intuition and problem-solving abilities. Contact us to learn more about AI in software development.