Weâre now on Day 5 of our 30 Days of AI in Testing challenge! Over the past few days, weâve built foundational knowledge about AI in testing. Today, weâll take a look at how our discoveries play out in real-world settings by exploring case studies or sharing personal experiences.
Task Steps
Option 1: Case Study Analysis
- Search for a real-world example of where AI has been used to tackle testing challenges. This could be a published case study or an example shared in an article or blog post.
- Select and analyse a case study that seems relevant or interesting to you. Make a note of the company and context, how AI was applied in their testing process, the specific AI tools or techniques used and the impact on testing outcomes/efficiency.
Option 2: Personal Experience Sharing
- If you have personal experience with using AI tools or techniques in your testing activities, you can share your own journey and learnings.
- Describe the context, the AI tools or techniques you used, how you applied them, and the outcomes or challenges you faced.
Share your Discoveries!
- Whether you choose Option 1 or Option 2, share your discoveries by replying to this post. Here are some prompts to guide your post:
- Brief background on the case study or personal experience
- How was AI used in their/your testing?
- What tool(s) or techniques did they/you leverage?
- What results did they/you achieve?
- What stood out or surprised you about this example?
- How does it relate to your own context or AI aspirations?
Why Take Part
- See AI in Testing in Action: By exploring real-world examples, we gain insights into whatâs possible and begin envisioning how AI could transform our own testing.
- Deepen Your Understanding: By exploring a case study or personal experiences, youâll gain a deeper appreciation for the complexity and nuance of integrating AI into testing workflows.
- Share the Knowledge: Sharing your case study findings or personal experiences and discussing them with others offers a chance to learn from each otherâs research, expanding our collective knowledge and perspectives on AIâs role in testing.