Artificial intelligence is not just some buzzword anymore, it’s becoming the reality of many businesses and firms. According to NewScientist, there is a 50% chance that machines will start outperforming humans at their jobs by the year 2060. Machines will be better at translating languages, driving trucks and even writing a best-selling novel. The development industry is not immune to this shift. In fact, despite its disruptive capacity, AI provides plenty of potential for improving both software development and testing. Weaker versions of AI have been used in the industry for quite some time, but advances in AI and machine learning mean that applications will be able to learn autonomously and react to complex scenarios, without intervention.

Turning an idea into code has never been an easy task for developers, even with initiatives like Agile and DevOps. But advances in artificial intelligence (AI) are about to make it a whole lot easier. Advanced AI is going to help developers find the data they need to fix, simplifying the testing process. Plenty of developers consider testing the most important phase in the SDLC, firms will be able to implement AI to increase automation in testing and achieve high quality results.

DevOps often spend hours, or even days, trying to pick out the faulty code in a software project. Automated AI will be able to find that data for them, and suggest possible changes, and how to apply them to the software development life cycle (SDLC). It will also allow text recognition in any software model. This kind of technology is a real boon for those working with custom software development, allowing them bring up similar development cycles to reference, as well as error phases and flaws, giving the team valuable resources to improve the current project.

AI will improve communication between developers too. Sometimes it can be difficult to pinpoint who worked on a section of code, AI will solve this problem by tracking and recording who works on what data and making it easily accessible.

Currently, programming languages like JavaScript, Ruby, and Python allow templating of businesses policies and best practices. AI and rule-based learning can enable better implementation of policies like these, which aren’t confined to a single problem. This cuts down on business costs, as coding policies through traditional language can be an expensive task.

While the days where developers will be able to tell a computer to create a program, sit back and watch the magic happen are still a way off, the new advances in AI technology will allow programmers to create better, safer software than those currently created in traditional environments. Software development is never going to stop needed tech-savvy professionals with the capacity to think outside the box. But understanding the shift towards AI and knowing how to apply it is going to become an important skill in both quality assurance and other development jobs. Developers will need to be comfortable with machine learning, data science and deep learning, and eventually they’ll be building applications that learn all on their own.