State of AI applied to Quality Engineering 2021-22

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Over the past few years AI^[1] (Artificial Intelligence) has become a reality for most of us. Self-driving cars, facial recognition, chatbots, and deep-fake image production are just a few of today's commonplace examples. The advances in computing power combined with storage cost efficiency is driving more AI developments at increased pace.

Parallel to the growth of AI, the software development industry has been profoundly impacted by the increase in technological sophistication, the reduction of delivery cycle time, and the imperative of the user experience. And the number of potential combinations of digital products has now reached unfathomable proportions. All these competing forces create a chasm in terms of quality engineering. Many of us have turned to Continuous Testing to help close this gap. However, looking forward, we realise this is becoming insufficient.

 

[1] Put simply, AI is the ability of machines to carry out tasks and activities we would consider "intelligent". Artificial intelligence, broadly defined, is the ability for an intelligent agent to observe its surroundings and carry out specific tasks to maximise its ability to achieve some goal. Source: https://www.tmap.net/node/319