Artificial Intelligence (AI) in software testing shows great promise in ensuring high-quality software without the manual drudgery of endless units and integrated proofing. With AI, delivery times will be reduced from minutes to seconds, and vendors and customers will experience a software renaissance of inexpensive and user-friendly computer applications. Unfortunately, the luxury of inexpensive storage space, blazing fast processing rates, readily available AI training sets, and the internet have converged to turn this promise into overblown hype.
Googling "AI in software testing" reveals an assortment of magical solutions promised to potential buyers. Many solutions offer to reduce the manual labor involved in software testing, increase quality, and reduce costs. In addition, vendors promise that their AI solutions will solve software testing problems. The Holy Grail of software testing — the magical thinking goes — is to take human beings, with their mistakes and oversights, out of the software development loop and make the testing cycle shorter, more effective, and less cumbersome. The question is - should that be the main focus, and is it even possible?