There isn't a lot of information relating to AI and Software testing out there, and most of it is, um, lets just call it'lacking' in technical depth, and this causes even more confusion and angst. Below are some links to help demystify AI / machine learning in the context of software testing. My hope is that folks that care will go through most of the material below and move from being "AI Curious" to "AI Aware". Most of the links below should be accessible to people without a math degree or programming background. My hope is that more people will be able to discern the carnival barkers from the real deals, understand the humble reality of AI today vs the hype, and think of ways they might be able to apply AI to their own software testing problems.

Appvance has announced a breakthrough using artificial intelligence algorithms to automatically create and maintain scripts for testing software applications. By modeling human testers, including manual and test automation tasks such as scripting, Appvance has developed algorithms and expert systems to take on those tasks, similar to how driverless vehicle software models what a human driver does. AI-driven test automation is available to preview today, commercially in October, and requires no changes or added code in applications under test. Most software testing today is manual (up to 90% based on recent industry surveys). The rest is semi-automated by writing scripts in various languages such as Selenium or Java to repeat actions for future tests.