• Mr. Dheeraj Panchal
• Ms. Muskan Vaswani
• Ms. Riya Vihol
• Mr. Tirth Shah
• Ms. Bhavana Hotchandani, Dr. Akshara Dave

Software testing guarantees that programs operate safely and correctly, but conventional techniques are labor-intensive and time-consuming. Through process automation, defect prediction, and increased test coverage, AI is transforming testing. While requiring less human labor, AI-powered solutions may produce test cases, identify patterns, and improve software quality. This study examines how AI affects software testing, stressing its advantages, difficulties, and prospects. Even while AI improves productivity and expedites testing, issues like data dependency and confidence in AI judgments still exist. Organizations may improve software quality and deploy software more quickly by understanding AI-driven testing. This research explores the growing impact of artificial intelligence on the future of software testing and quality assurance practices.

Artificial Intelligence, Software Testing, Automation, Machine Learning, Neural Networks, Natural Language Processing (NLP), Human-AI Collaboration

"Software Testing in the Age of AI: Overview, Opportunities, and Myth-Busting Insights", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.291-298, December-2025, Available :http://www.jetir.org/papers/JETIRHE06036.pdf

"Software Testing in the Age of AI: Overview, Opportunities, and Myth-Busting Insights", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. pp291-298, December-2025, Available at : http://www.jetir.org/papers/JETIRHE06036.pdf