AI in Software Development: Revolutionizing the Coding Landscape

Artificial intelligence (AI), particularly large language models and generative AI can make it easier for software developers to design, create, test, and deploy software programs. Using this technology, you can increase your productivity and coding efficiency while reducing errors in your code, development costs, and time to market. You can use AI to help you complete many tasks associated with developing software, from generating whole blocks of code to automated code testing, review, and project management. 

Explore the benefits and challenges of using AI in software development and examples of AI software development tools you can use to speed up the development process. 

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What is AI in software development?

Generative AI models can be used to create text, images, videos, audio, and more, including generating code in various programming languages. 

When you use natural language to interact with generative AI, it uses math and statistics to understand the relationships between words and predict the most appropriate response, which looks to human eyes like something created by a human using logic and reasoning. However, the AI model doesn’t understand language like humans do—only how to create something similar to natural language. 

AI in software development processes code in a similar way. While the model doesn’t understand the coding principles and logic like a human programmer, it can analyze programming language documentation to recognize patterns and syntax, predict what comes next, and suggest how to improve your code.

Benefits of using AI in software development

Using AI in software development can help you write code faster with fewer errors, reducing the time to market and lowering development costs. You can also use AI to help improve project management and decision-making by gaining access to insights from data. Below are several examples of how AI can power these improvements for your team:

• Increased efficiency and reduced time to market: AI software development programs help you write and develop code faster, shortening the time it takes your team to perform each step of development, reducing the time it takes to go to market, and ultimately reducing costs. 

• Enhanced code quality and reliability: You can use AI to catch errors and bugs in your code that you may have otherwise missed or would have to spend labor hours tracking down and fixing. AI software development models can also suggest improving security and other aspects of your software. 

• Lower development costs through automation: Another way to shorten the time it takes to go to market and lower development costs is to use automation. AI in software development can help you turn mundane processes into automated tasks that your team doesn’t have to spend time manually completing. 

• Better project management and decision-making: AI models can help you streamline project management tasks like allocating resources and finding ways to schedule tasks and processes more effectively. You can also use AI to optimize your pipeline to consistently deliver value to your customer or client. 

How is AI being used in software development?

AI can be used on many steps of the software development process, including creating new code from scratch or automatically closing the statement you’ve written, automated testing, bug detection, and fixing, suggesting improvements to code, managing your project, and documenting code using natural language. 

Code generation

AI can assist with code generation, from auto-completing statements to creating entire code blocks. Depending on your tools, you can describe the function or logic you need in natural language, and the AI will generate relevant code. Like autocomplete on a smartphone, AI can also predict and suggest the next lines of code based on what you've already written.

Automated testing

Using AI in software development can help conduct automated testing. For example, AI can analyze how users interact with a website, generate test cases based on what it learns, and conduct testing to detect potential problems or vulnerabilities. The AI model can analyze metrics from previous testing and problems to offer continuous suggestions for improvement. AI can also automatically detect errors in your code and make suggestions as you write so you can write code with fewer errors the first time. 

Project management

You can also use AI to improve software development project management. The AI model can help you schedule tasks more efficiently, allocate resources, and estimate the time required to complete a task. AI can automate routine aspects of the project management process, giving you more time to focus on solving problems and creating solutions. 

Documentation

AI models can write documentation in your code in natural language, making it easier for other team members to understand what each piece of code does. Documenting code can be tedious, but AI models can automatically create documentation as they write code, using your natural language prompt to supply the descriptions. 

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Who can use AI in software development?

One of the biggest advantages of using AI in software development is that it allows people with less technical backgrounds to access tools that can help them code and develop their own programs. While AI can’t teach you to code, it can bridge the gap between what you know and don’t know to help you create functional programs faster. 

The roles below may be particularly well-suited to use AI in software development.

Software developers

Average annual salary in the US: $104,983 [1]

Job outlook (projected growth from 2023 to 2033): 17 percent [2]

As a software developer, you design and build software programs. You can work in many industries creating different software solutions, including those specific to your company or that might appeal to a larger end-user base. In this role, you can use AI models to help you in your work in many ways, including generating and improving code as you write and helping you with documentation. 

AI developers

Average annual salary in the US: $111,730 [3]

Job outlook (projected growth from 2023 to 2033): 17 percent [2]

An AI developer is a software developer working specifically to create software programs that use AI models. You can work in the same variety of locations and industries as a software developer. Still, you'll focus on applying AI principles to solve problems or offer value to the end user. 

Project managers

Average annual salary in the US: $90,780 [4]

Job outlook (projected growth from 2023 to 2033): 7 percent [5]

As a project manager in a software development project, you lead your team and manage the resources, timeline, and project scope to deliver a quality piece of software to your client or end user. In this role, you can use AI tools to help you manage and optimize scheduling and automate routine tasks. 

AI software development tools

You can choose from many AI programs to improve and automate your software development. Three examples of AI for software development include: 

• OpenAI Codex: Codex is an AI software development program offered through OpenAI. You can access the program directly or use the API to integrate Codex into your code environment. 

• Amazon Q Developer: Q Developer is an AI-powered assistant offered by Amazon you can integrate into your coding environment to act as an expert chatbot assistant. 

• Google Gemini Code Assist: Code Assist from Google is another AI integration you can add to your IDE to provide code generation and assistance and to chat about your code base. 

Learn more about AI in software development on Coursera.

Using AI in software development can help your team write code faster with fewer errors, reducing the time it takes to go to market and the development cost. If you want to learn more about using AI software development tools, IBM’s AI Developer Professional Certificate on Coursera can help you learn how to build and deploy AI applications and chatbots. 

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Voice Assistants, Chatbots, Python Programming, Software Engineering, Software Architecture, Agile and Scrum, Software Development Lifecycle (SDLC), Career, Software Engineer, Coding Challenge, interview Preparation, Full Stack Developer, Artificial Intelligence (AI), ChatGPT, Large Language Models (LLM), Natural Language Generation, Generative AI, Prompt Engineering, prompt patterns, Web Development, JavaScript, Web, Cascading Style Sheets (CSS), Application development, Web Application, Flask, Software Development, Code generation, AI prompts, Data Science, Data Analysis, Numpy, Pandas, AI ethics, Natural Language Processing, Machine Learning, Artificial Intelligence