Gartner defines AI-augmented software testing tools as enablers of continuous, self-optimizing and adaptive automated testing through the use of AI technologies. The capabilities run the gamut of the testing life cycle including test scenario and test case generation, test automation generation, test suite optimization and prioritization, test analysis and defect prediction as well as test effort estimation and decision making. These tools help software engineering teams to increase test coverage, test efficacy and robustness. They assist humans in their testing efforts and reduce the need for human intervention in the different phases of testing.
Task mining is a technique by which enterprises can infer meaningful information by scraping desktop-level event data. This data may be from individual users or a cohort of individuals (e.g., in a call center) and takes the form of screen recordings, keystrokes, mouse clicks and data entries. Additional mining capabilities interpret the data by applying natural language processing and optical character recognition to correlate data in different ways. Task mining helps an enterprise identify inefficiencies and automation or AI potential, improve task execution and enhance the employee experience.