Tech Talk: Transforming enterprise quality engineering practices

The San Francisco Bay Area chapter of the IEEE Computer Society invites to our free and open Virtual Tech Talks (no IEEE membership required):
Eventpage: https://www.eventbrite.com/e/transforming-enterprise-quality-engineering-practices-tickets-1985250279026?aff=oddtdtcreator
Speaker: Jyotheeswara Reddy Gottam ((https://www.google.com/url?q=https://www.linkedin.com/in/gjreddy/&sa=D&source=calendar&ust=1774063921225418&usg=AOvVaw3p1OTEbWpnyMYwpkfkEjs-))
Title: The Triple Threat: Transforming enterprise quality engineering practices with Generative AI, Predictive Analytics, and Self-Healing Automation
Abstract: Modern software teams face mounting pressure to release high-quality applications faster while managing increasing system complexity and continuous delivery expectations within modern CI/CD pipelines. Traditional testing approaches often struggle to keep pace with rapid code changes, expanding regression suites, and the rising cost of maintaining automation frameworks. These challenges frequently lead to delayed releases, increased testing costs, and defects escaping into production.
This presentation explores how the “Triple Threat” of AI-driven testing technologies—generative AI for test script creation, machine learning–based predictive defect analytics, and self-healing automation frameworks—is transforming enterprise quality engineering practices.
First, generative AI accelerates test development by automatically generating test cases, scripts, and data from requirements, user stories, or code changes, significantly reducing manual scripting effort. Second, predictive defect analytics powered by machine learning analyzes historical defect patterns, code churn, and previous test outcomes to identify high-risk components and prioritize testing efforts where failures are most likely to occur. Third, self-healing automation frameworks intelligently adapt to UI or API changes, minimizing brittle test failures and reducing the costly maintenance typically associated with large automated test suites.
When deployed together, these technologies reinforce one another: generative AI expands test coverage, predictive analytics focuses testing on the most critical risk areas, and self-healing automation ensures test suites remain resilient despite frequent application updates. Applied across API testing, functional testing, integration testing, and end-to-end testing, this integrated approach enables organizations to modernize their testing strategy while improving reliability.
The combined impact allows enterprises to reduce testing costs by up to 40%, accelerate release cycles by 30%, and improve defect detection rates by over 50%, demonstrating how AI-driven testing can deliver measurable improvements in both quality and delivery speed across enterprise software systems.
Bio: Jyotheeswara Reddy Gottam is a Software Engineering Leader with over a decade of experience in the retail and e-commerce industry. Currently a Senior Software Engineer at Walmart Global Tech, he leads end-to-end testing strategies for high-traffic marketplace platforms, driving scalability, reliability, and performance for systems handling millions of daily transactions. He specializes in Gen AI, ML, AI agents, RAG, test automation, performance engineering, and CI/CD enablement. Throughout his career, he has architected scalable automation frameworks, reduced regression cycles significantly, improved release velocity, and ensured platform stability during peak traffic events. He has also led cross-functional initiatives across payments, inventory, personalization, and mobile platforms.
Speaker(s): Jyotheeswara Reddy Gottam
Virtual: https://events.vtools.ieee.org/m/548913