How big of a role would be to test LLM agents in the future?
As AI takes on more testing tasks, how will experienced testers need to redefine their roles to focus on higher-level strategic tasks, such as quality coaching, test design optimization, and risk assessment?
What does mentorship look like in this new AI-driven space , is it still human-led, or do you see AI playing a role in guiding careers?
How to use AI effectively in testing ?
How can a testing professional become an internal champion both for AI adoption and for their own career paths and fellow team members, as AI assumes some of their Q/A and testing task loads?
How is AI affecting entry-level opportunities for people aspiring to start a career in QA?
Vibe coders with a basic understanding of development will replace experienced SDE’s ?
Will software produced by artificial intelligence in the future no longer require testing?
What role do communities play in ensuring transparency of AI-based testing decisions?
How AI will decide if specific functionality is bug or not. That is only upto the developers who are more familiarize with the application?
With AI’s help , right now everyone with a technical background can become tester, devops, developer etc. How soon a time will come where just 1 single technical expertise cannot be enough to survive ?
How do you see AI helping communities without replacing the human connection that people need?
How can testing communities leverage AI to improve knowledge sharing and mentoring?
How long it will take when all the companies in IT Industires will switch to AI Agents for their testing needs? Also if a person is hunting for a job in testing which AI tool he or she should master as there are lots of AI tools evolving now a days?
Exploratory testing thrives on curiosity and context. Do you believe AI can ever replicate that or will it always remain a uniquely human skill?
When AI misinterprets natural language test steps, the risk is silent failures. How do we build guardrails so critical business workflows aren’t incorrectly tested?
In what ways are companies going to shift their hiring criteria for QA Engineers? What parameters will they evaluate testers on?
Do you think in the next 5 years, AI will shift QA from ‘test execution’ to ‘risk prediction’? What might that transition look like?
If AI becomes the primary driver of QA, how do we avoid bias, where AI only tests scenarios it has seen before and misses the true edge cases?
What’s the ethical line in using AI for testing, for example, if AI discovers a production vulnerability, who’s accountable: the tester, the AI, or the organization?