AI in Software Development: Real Use Cases, Tools & Benefits

“AI streamlines software development processes by automating coding, testing, debugging, and project planning, helping developers build high-performing software faster and more efficiently.”

What if developers could build high-quality software in a fraction of the time with minimal bugs and less manual effort? Today, this is becoming possible by using AI in software development. 

For ages, development teams have struggled with repetitive coding tasks, slow testing cycles, and manual debugging that ultimately delay projects. But AI has changed the game completely with smarter automation. 

Now, software development teams can deliver high-performing software solutions easily with the help of AI. This blog will share with you the real use cases, tools, and benefits of using AI in software development.

Understanding the Role of AI in Software Development

Earlier in November 2022, when ChatGPT was released, predictions were made that software developers’ jobs are now under threat. However, that turned out to be the biggest notion. In reality, ChatGPT turned out to be a powerful assistant for software developers. 

This is exactly what AI was introduced for in software development. From recommending correct syntax to detecting bugs and creating text scripts, the introduction of AI in software development has helped streamline every development stage. This is why the global AI market in software development is estimated to reach USD 15,704.8 million by 2033 at a CAGR of 42.3%.

Think about how, in the late 2000s, developers had to code and test software applications manually. This used to be time-consuming. Moreover, developers were unable to identify each bug and resolve it efficiently. 

But after the launch of AI in software development, coding became faster, and testing and debugging were simplified with automation. The result was that developers were able to deliver high-performing software solutions quickly and efficiently.

Amazing Benefits of Using AI in Software Development

Here’s how AI benefits in software development.

1. Faster Development Cycles

Software development involves several repetitive tasks like boilerplate code, generating documentation, and debugging common errors. 

Before AI, such repetitive tasks used to consume a lot of time and energy from developers. But now AI automates such mundane tasks, so developers can easily focus on more complex and creative tasks.

2. Improved Code Quality

Software development codes are too long. In such long lines of code, it becomes challenging for developers to find all the errors. 

AI simplifies this through its data analytics tools. AI-powered tools can analyze huge amounts of code for potential bugs and vulnerabilities in no time. The analytics tools work very efficiently and can easily detect issues that are often missed by humans.

3. Cost-Efficient Development

What if a tool could test the code as you write? It would save a lot of time for developers. This is what AI does in software development. AI-powered test automation tools automatically run tests on the code. 

This helps teams complete custom software development projects faster. Moreover, automated testing tools help software development companies save the cost of hiring large QA teams, which eventually ensures lower development costs.

5 Most Popular AI Tools Used for Software Development

Till now, we have seen how AI helps streamline the software development process smartly and efficiently. Now it’s time to see how AI does it. Here is the list of the five most popular AI software development tools. 

1. GitHub Copilot

GitHub is the most popular developer platform that allows developers to create, store, manage, and share their code. 

The leading developer platform was alone proving to be a helpful medium for developers across the globe. But it became a revolutionary platform when it merged with OpenAI and became GitHub Copilot. 

Today, this platform has become a popular AI-powered coding assistant that uses large language models to understand the context of your code and suggest real-time code completions, full functions, and sometimes even entire code files. This eventually helps developers save time and increase productivity with ease.

2. Tabnine

After GitHub Copilot, Tabnine becomes another AI code completion tool. What makes this AI-powered tool stand out is its ability to predict the next line of code based on the current coding style. 

Moreover, it also provides support for multiple programming languages. GitHub Copilot is trained on a large dataset of publicly available code from open source projects. But Tabnine can be trained on your team’s private code so that it can easily adapt to your unique coding style and architecture choices that are specific to your organization or project.

3. AWS CodeWhisperer

Software development is of varied types, out of which cloud-based SaaS development is the one. AWS CodeWhisperer is an AI assistant designed specifically for cloud-based development. 

It becomes helpful for software developers building solutions on AWS architecture. 

Through its powerful analytical abilities, AWS CodeWhisperer automatically identifies and fixes security vulnerabilities. 

Moreover, the leading coding assistant easily integrates with IDEs like VS Code and JetBrains. Due to this, AWS CodeWhisperer becomes a must-have tool for cloud engineers who want to build software solutions faster but without compromising security.

4. Selenium + AI-Based Testing Add-ons

Selenium is considered to be one of the most popular automation testing frameworks known to be the right hand of most software testers. 

The popular testing tool became more powerful when it paired with AI add-ons. AI technology in Selenium auto-detects failures and fixes broken test scripts. 

For instance, if a button’s position changes after a UI redesign in a custom web portal, AI in Selenium automatically adjusts the locator instead of requiring manual test updates. This helps quality testers improve testing efficiency.

5. Testim

After Selenium, Testim is another widely used AI-based testing tool. This tool usually focuses on smart test creation and maintenance. Based on its AI-powered analytical skills, Testim learns how software applications behave and updates test scenarios accordingly. 

For instance, if a new feature affects the login workflow, then Testim instantly modifies test paths without manually rewriting the code. This smart testing tool helps QA teams reduce testing time and also improve product quality.

Real Use Cases of AI in Software Development

1. AI-Powered Code Generation and Auto Completion

One of the major uses of AI in the software development process is smart code generation, in which AI tools actually help developers write code automatically. 

These tools, using AI-powered data analytics, can easily analyze what you are typing and suggest the next line of code or entire function blocks by predicting what you might need next. This ultimately helps in eliminating repetitive coding and also reduces the chances of syntax errors.

2. Project Planning and Resource Management

Just like software solutions need to be high-performing, developers need to deliver projects on time. 

For this, using AI in software development becomes very helpful. AI easily evaluates specific developer productivity, workload, sprint velocity, and task complexity to build project plans. 

Moreover, AI also helps project managers to plan the software development project more accurately by analyzing historical performance data and predicting delivery risks. This allows software development projects to be completed on time with perfect accuracy.

3. Automated Software Testing

Testing is an important phase of the software development process. However, it is time-consuming. AI helps in automating testing processes by running test cases, analyzing UI behavior, predicting failure areas, and identifying bugs. 

Moreover, AI automation also helps in automatically updating test scripts when software changes, which manual testers take hours or sometimes days to do.

4. AI for UI/UX Design and Prototyping

Designing different wireframes or prototypes manually for a software becomes time-consuming and error-prone. But AI does this in the snap of a time. It automatically generates layouts, color palettes, and user flow suggestions. 

It can even turn written descriptions into ready-to-edit wireframes or prototypes automatically and recommend improvements accordingly. This helps in shortening the design cycles and delivering more user-friendly software solutions.

5. AI-Assisted Debugging

What if every software developer could have a personal assistant to debug every line of code? While it might seem impossible for human assistants, an AI debugging assistant comes to the rescue. 

AI-based debugging tools hold the power to analyze huge lines of different code patterns in no time and find where errors originate. Moreover, AI-based debuggers also suggest intelligent fixes, ensuring faster issue resolution.

Final Say

With AI being the present and the future, it is transforming every industry, including the software development industry. It is helping software developers deliver high-performing software solutions in an affordable way with faster coding, smarter testing, and high-end security. 

Thinking of developing an AI-based software solution? Technocrats Horizons becomes your perfect partner. Our software development company is known for the quality and precision of solutions we deliver. With an agile development approach and leading AI technology, we build quality software solutions perfectly aligned with your needs.

Contact us now to develop AI-based software to bring your vision to life.