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AI Powered software testing

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Srinivas R Lead (SDET / Quality Engineering - Full stack)| Dayforce Inc (Fomerly Ceridian HCM)
I am developing my skills on AI powered script less automation testing. But I want to know what percentage of global organizations have currently enacted this. I see still most of the organization are following the tradition automation tools for testing
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Abolfazl Yousefi Darestani Manager, Quality and Continuous Improvement| Hörmann-TNR Industrial Doors Newmarket, Ontario, Canada
Yes, it takes time to reach to a point that the majority of tasks are being delegated to AI.
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Sergio Luis Conte Helping to create solutions for everyone| Worldwide based Organizations Buenos Aires, Argentina
AI is a board term. I am just writting this because some people confuse generative AI with AI while it is just a subset. AI in software testing is used from long time ago. When I write software testing I am refering to the whole testing process. You can implement AI entities to cover the whole process including it free of cost tools.
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Verónica Elizabeth Pozo Ruiz RYLAI Access Control Quito, Pichincha, Ecuador
I agree that AI is a broad term, but generative AI is also AI since it's a subtype.

Generative AI works with predefined models and data and has fewer autonomous decision-making capabilities. Traditional AI, on the other hand, has the principal characteristic of being capable of making decisions, learning from experiences, and having true autonomy.

Nowadays less Than 50% of Companies are using AI capabilities for automation testing. The incorporation of AI in this process would be a great opportunity to increase efficiency.
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Kathleen Campbell TestingXperts Mechanicsburg, United States

AI-powered software testing is indeed transforming the QA landscape. It’s not just about speed or automation anymore—it’s about intelligent testing. From predictive analytics to self-healing scripts, AI is helping teams catch defects earlier, reduce test maintenance, and adapt faster to changing requirements.



What I find most exciting is the rise of agentic AI systems that reason and adapt, going beyond rule-based automation. They can identify risk areas in real time, suggest new test cases, and even prioritize based on historical defect trends.

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