Machine learning (ML) and artificial intelligence (AI) are frequently imagined to be the gateways to a futuristic world in which robots interact with us like people and computers can become smarter than humans in every way. But of course, machine learning is already being employed in millions of applications around the world--and it's already starting to shape how we live and work, often in ways that go unseen. And while these technologies have been likened to destructive bots or blamed for artificial panic-induction, they are helping in vast ways from software to biotech. Some of the "sexier" applications of machine learning are in emerging technologies like self-driving cars; thanks to ML, automated driving software can not only self-improve through millions of simulations, it can also adapt on the fly if faced with new circumstances while driving. But ML is possibly even more important in fields like software testing, which are universally employed and used for millions of other technologies. So how exactly does machine learning affect the world of software development and testing, and what does the future of these interactions look like?

Artificial Intelligence solutions have completely transformed the landscape of modern enterprise and changed the outlook of everything, including software development and testing. To understand the role of artificial intelligence in software development and testing, we need to analyze what has changed. There has been a phenomenal increase in data; heightened computational power at reduced costs and breakthroughs in technology, AI is now becoming a reality. It is no longer a buzzword. Machine learning is the ability to develop capabilities and improve their performance over time without the need to follow explicitly programmed instructions.