In today’s fast paced software development world where AI agents and LLM (Large Language Model) are writing or assisting in code development, methods like Agile and DevOps demand faster, more efficient testing and early testing that are commonly known as shift-left testing. To deliver reliable, high-quality software early to market. Traditionally, In SDLC (software development life cycle) phase, testing comes late in the development process and leads to late and costly bug fixing. Shift-left testing means early testing in the software development lifecycle to identify and mitigate defects early. In this paper we are exploring the potential of Agentic AI in Shift left testing approach. A new wave of artificial intelligence frameworks designed to automate and revolutionize shift-left testing. By employing AI or Gen AI and machine learning (ML) techniques, these frameworks get trained directly from human testers, using trained classifiers to recognize application states, NLP (natural language processing) models learn and automate test workflows, and adaptable test-case generation models. In the 21st century, the AI era is going to redefine the software testing approach and AI-driven automation framework with the integrating of Agentic AI framework. Additionally, the paper demonstrates real-world benefits experienced by enterprises adopting Agentic AI and shift-left testing strategies, not only reduce costs, fewer delays but also provide next generation software testing approach and framework. Finally, this paper highlights areas for future research and practical insights into optimizing Agentic AI for more effective, efficient, responsible and this will change the future software testing with AI-driven shift-left testing framework.