Global Modular Laboratory Automation Market, By Equipment and Software (Automated Liquid Handlers, Automated Plate Handlers, Robotic Arms, ASRS, Software, Analysers), Application (Drug Discovery, Genomics, Proteomics, Clinical Diagnostics), Country (U.S., Canada, Mexico, Germany, Italy, U.K., France, Spain, Netherland, Belgium, Switzerland, Turkey, Russia, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia- Pacific, Brazil, Argentina, Rest of South America, South Africa, Saudi Arabia, UAE, Egypt, Israel, Rest of Middle East and Africa) Industry Trends and Forecast to 2028.

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As we enter the age of smart technologies, automated testing has become an indispensable part of modern software development. As the demand for quick and reliable testing grows, integrating AI tools into creating test scripts is becoming a standard practice. Creating efficient test scripts requires a thorough comprehension of the application's design, a strategic approach to tackle different test scenarios, and the ability to modify scripts to adjust to changes in the application. Traditional methods often involve a significant amount of manual work, which can introduce errors and cause delays in the testing process. This is where using AI and related tools revolutionizes the testing landscape. This article explores the significance of AI and ML for automated testing and how it can transform the way testing is executed across various frameworks. Role of AI in Software Testing The role of AI in software testing has skyrocketed since the pandemic. Valued at $736.8 million in 2023, the AI-enabled testing market is expected to grow at a whopping CAGR of 20.7% by the end of 2030. On top of offering some basic enhancements to the testing processes, – improved accuracy, automation of repetitive tasks, enhanced efficiency, etc. - AI-powered tools provide some advanced features to escalate the way testing is executed: Natural Language Processing (NLP): In the coming years, NLP will emerge as a crucial trend that will revolutionize software testing by enabling efficient analysis and automation. AI systems can comprehend and generate test cases, bug reports, and documentation in natural language. This improves communication between machines [...]

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Quality engineering (QE) is at a crossroads in 2024. As cutting-edge technologies and innovative methodologies […]