We’ve seen how artificial intelligence (AI) can support human developers in the development lifecycle, however, AI is now on the verge of redefining how software development works. In fact, experts are suggesting that developers can use AI algorithms to improve everything from project planning and estimation to quality testing and the user experience (UX).
More companies are using AI than ever before to test scripts, produce low-code development platforms, and use the technology to create development tools.
In May, IBM announced Project CodeNet, a 14-million-sample dataset to develop machine learning models that can help in programming tasks that the company’s AI research division released. With Project CodeNet, the researchers at IBM have tried to create a multi-purpose dataset that can be used to train machine learning models for various tasks. CodeNet’s creators describe it as a “very large scale, diverse, and high-quality dataset to accelerate the algorithmic advances in AI for Code.”
As AI augmented software development tools are slated to grow, there are a few approaches companies that employ software engineers can take to ride the new wave of AI.
First, AI augmented software development calls for employing software engineers, rather than letting the technology replace them. Its best to find developers whose tasks can be automated, and then reassign them to different work or train them to achieve higher value tasks. This is especially important as lower-skilled development work becomes automated.
Software development service businesses also need to take stock of how they prepare for AI-augmented software development. One such way of doing so is to employ developers awaiting their next billable assignment to quantify the effort savings from AI automation tools.
Companies that outsource software engineering to external service providers are also affected by the disruptions of AI-augmented software. While there will always be a market for traditional custom software development services for building unique customer experiences, unique operational processes, or unique product features, generative AI will play an increasingly larger role in delivering these services.
Software engineering managers who outsource engineering should require incumbent software engineering suppliers to propose AI-augmented automation innovations at least every quarter as part of a continuous improvement process.
Ultimately, AI and software intelligence tools aim to make software development easier and more reliable. The next step is to figure out how to combine AI-augmented software development with current software engineers to maximize output and performance.