Systems | Development | Analytics | API | Testing

Businesses are seeking ways to collect all the data from their digital sources and draw out patterns that can reinterpret human participation with automation. A vanguard in this attempt is the emergence of large language models (LLMs) powered by artificial intelligence (AI).

According to a survey by Markets and Markets, the EdTech sector is seeing an unparalleled upswing, with the worldwide market size expected to reach an astounding $232.9 billion by 2027 at a CAGR of 13.2% over the period 2022–2027. This extraordinary expansion highlights the critical need for Edtech software testing services as well as a revolutionary change in how we study and access educational information.

The pace of change in the world is rapidly accelerating. Technology companies must prioritize speed to market to stay ahead of this curve, but speed can sometimes come at the expense of risk. The recent CrowdStrike incident is a sobering reminder that even the largest and most capable organizations are not immune to errors that can lead to significant downstream impacts.

Test automation is no longer a cutting-edge technology. It is now a standard for any QA team looking to bring product quality to the next level. However, some testers are hesitant. They pose questions: does test automation actually bring ROI? Or perhaps they’re wary of the struggle with maintaining automation test scripts that break every time a new update is rolled out. It is those questions that deter business leaders from making the final decision, but they have a reason to be wary.