How IBM watsonx Code Assistant impacts AI-powered software development

Software development is undergoing a profound transformation, fueled by the rapid advancements in artificial intelligence (AI). AI-powered coding assistants are at the forefront of this shift, enhancing productivity, improving code quality and streamlining workflows. These intelligent tools cannot only augment human capabilities but also redefine best practices, accelerate development cycles and drive greater efficiency.

According to Gartner® Magic Quadrant™ for AI Code Assistants, 90% of enterprise software engineers will use AI code assistants by 2028, a sharp increase from less than 14% in early 2024.¹

Also, Markets and Markets research states that the global market for AI Code Tools Market is projected to grow from USD 4.3 billion in 2023 to USD 12.6 billion by 2028 at a compound annual growth rate (CAGR) of 24.0% during the forecast period.  

AI will influence the future of software development and every stage of the development lifecycle. From code generation and unit test automation to code transformation, bug detection and autonomous fixes, AI-driven assistants and intelligent agents can revolutionize the way developers work. These technologies will not only enhance efficiency but also establish new industry standards, with the potential to make software development faster, more reliable and increasingly automated.

The fast pace of AI development has accelerated coding assistants to evolve from emerging technologies to tools within the developer’s toolkit. AI-powered assistants, such as IBM® watsonx Code Assistant™, provide developers with intelligent code suggestions, automated bug troubleshooting and code optimization, empowering them to write clean, efficient code at an accelerated pace.

By seamlessly integrating with popular integrated development environments (IDEs), such as Visual Studio Code and JetBrains, AI assistants help minimize context-switching, enabling developers to receive real-time insights and suggestions directly within their coding environments. This seamless workflow enhancement can help boost productivity and enable developers to focus on innovation rather than routine coding tasks.

However, the impact of AI on software development can extend far beyond automating routine tasks. Beyond handling repetitive tasks with machine learning capabilities, AI coding assistants can learn from vast codebases, offering contextually relevant suggestions that align with the project’s architecture, coding style and best practices. This can result in not only syntactically correct code but also a more holistic approach to software development, making it easy for developers to streamline workflows, enhance code maintainability and accelerate software delivery.

One of the most immediate benefits of AI coding assistants is the increase in developer productivity. Based on an internal IBM test, IBM developers using IBM watsonx Code Assistant projected that they could see a 90% time savings on code explanation*, 59% time reduction on documentation** and 38% time reduction in code generation and testing.

** Learn how IBM developers tested watsonx Code Assistant.

By automating coding tasks for software developers and software engineers, AI coding assistants can help alleviate the burden of mundane coding activities, allowing developers to focus on the aspects of the software development lifecycle that require critical thinking, creativity and problem-solving. AI-generated code gives programmers the time to concentrate their efforts on tasks that require a human touch and human ingenuity. This shift not only enhances productivity but can also lead to improved job satisfaction, as developers can engage more with innovative projects rather than tedious bug fixing or boilerplate code writing.

IBM watsonx Code Assistant is a critical tool in enhancing code quality. With real-time feedback and suggestions, it helps developers proactively identify potential issues and detect bugs early in the development process. Its ability to offer best practice and optimize code structure can lead to fewer errors, enhanced maintainability and strengthened software reliability and security.

Poor code quality can result in bugs, security vulnerabilities and costly maintenance. AI-powered coding assistants can help mitigate these risks by identifying issues early, so software remains robust, scalable and easier to maintain. By integrating AI-driven insights into the development workflow, organizations have an opportunity to improve code quality, reduce technical debt and accelerate software delivery.

AI coding assistants also play a pivotal role in fostering collaboration, particularly in distributed and remote development teams. With features—such as real-time code suggestions, shared knowledge bases, AI-driven feedback loops and output sharing—tools such as IBM watsonx Code Assistant are designed to enhance communication among team members. These capabilities allow teams, especially those working across different time zones, to collaborate effectively and align on best practices.

By automating mundane tasks and providing support for more complex tasks, coding assistants can also help standardize code quality and practices so that all team members are on the same page, regardless of their experience level or geographic location. This consistency can help promote collaboration and accelerate the development process.

Perhaps one of the most promising outcomes of AI-powered coding assistants is their potential to lower the barrier to entry for new developers. By automating routine tasks, such as code snippet generation and code completion, and providing code reviews and intelligent suggestions, tools such as IBM watsonx Code Assistant can make it easier for beginners to learn new programming languages and contribute to projects with greater confidence.

For those just starting their coding journey, AI coding assistants with natural language processing capabilities provide real-time feedback, offer helpful resources and suggest improvements, helping to make the learning curve less daunting and more engaging.

Looking ahead, the potential for AI-driven development is immense. As AI technology continues to evolve, coding assistants will continue to become even more advanced, moving beyond code suggestions to anticipate a developer’s needs, understand project context and provide proactive assistance.

The growing trend of personalized learning can make AI coding assistants even more adaptive to individual software developers’ needs. By tailoring suggestions and feedback based on a developer’s style, preferences and skill level, these AI tools will offer a more customized and enjoyable coding experience.

As AI coding tools, such as IBM watsonx Code Assistant, continue to evolve, they can help to further enhance developer productivity, elevate code quality and promote greater collaboration within development teams. This integration of AI into the development process represents not just a technological trend but a fundamental shift that can redefine the way we build software.

To learn more about IBM coding tools powered by Granite™ AI models and advanced automation, visit the watsonx Code Assistant webpage.

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*Internal testing with optimal bandwidth and response time for watsonx Code Assistant.

**The IBM watsonx Challenge is an IBM-internal, corporate sponsored event. Listed results are based on self-reported data from participating teams.