Hello People!
With AI becoming such a hot topic, many testers are asking: who is out there testing AI, and what is their experience? If you’re new to this area, understanding how to test AI effectively is key as the technology evolves rapidly.
Testing AI isn’t like traditional software testing, it involves dealing with unpredictability, model accuracy , and ethical considerations.
To start, focus on learning about AI basics, machine learning models, and the kinds of tests needed for AI systems, such as data quality checks, model validation, and bias detection.
Exploring how others test AI can provide valuable insights into best practices and common challenges. Investing your learning in how to test AI will prepare you for the future of software quality assurance in an AI-driven world.
What are your thoughts or experiences in the realm of AI testing? Please share any insights.
Hello @klyni_gg ! Great question about the evolving field of Testing AI! It’s definitely a fascinating and critical area right now.
Testing AI is a different beast compared to regular software testing. Since AI models can behave unpredictably and learn from data, you need to understand the underlying machine learning concepts first.
Testers right now are focusing a lot on things like data quality, how accurate the AI’s predictions are, and whether the system is fair or biased.
If you want to get started, dive into AI basics and look at how people check datasets and validate models, it’s a mix of traditional testing and new approaches. Understanding model accuracy and how to assess it is crucial.
Hope this provides a good overview of what AI testing entails! Keep exploring! 
Hello @klyni_gg and fellow AI curious minds! Adding another perspective on the fascinating world of AI testing.
Right now, AI testing is mostly done by specialized teams that combine QA skills with data science knowledge. They test for things like model performance, bias, and ethical implications, which you don’t usually see in normal app testing.
If you’re new, the best approach is to learn about the AI lifecycle and how models are trained and tested. This helps you understand where bugs or issues can creep in.
It’s a fast-moving field, so keeping up with how others test AI will give you a leg up.
Hope this sheds more light on the landscape of AI testing! Keep learning!
Hi @klyni_gg, @ishrth_fathima and @joe-elmoufak!!
Here’s another take on who’s actually doing this work.
Who’s testing AI today? It’s often a mix of QA pros, data scientists, and even domain experts working together, because testing AI involves more than just code correctness—it’s about data, accuracy, and fairness.
If you want to learn, start by studying AI and machine learning fundamentals, then focus on how to validate models and test data for quality and bias. It’s not like traditional testing, but those who get comfortable with AI testing will be in high demand as AI keeps growing.
That’s it! Hope you like it.