As software systems grow in complexity and speed becomes a competitive advantage, traditional development practices are evolving toward more intelligent, automated approaches. This session explores how Artificial Intelligence (AI) can be seamlessly embedded across the Software Development Lifecycle (SDLC) to transform the way software is designed, built, tested, and maintained.

The talk will walk through how AI enhances each phase of the SDLC—from intelligent requirement analysis and AI-assisted design to automated code generation, smart testing, and predictive maintenance. It will highlight how modern development teams are leveraging AI-powered tools to improve productivity, reduce errors, and accelerate delivery while maintaining high standards of quality and governance.

Through practical examples and enterprise use cases, attendees will gain insights into implementing AI-driven workflows, integrating AI into existing DevOps pipelines, and overcoming common adoption challenges. The session will also touch on key considerations such as data quality, model reliability, and ethical implications in AI-assisted development.

By the end of this session, participants will understand how to transition from traditional coding practices to intelligent engineering ecosystems—enabling teams to build smarter, faster, and more resilient software systems.