Creativity and Innovation Techniques (CIT) play a vital role in fostering ongoing development across industries, yet their practical implementation remains challenging. Traditional CIT methods often require substantial expertise, are limited by human knowledge, and lack clear procedural guidelines. TRIZ, a well-established creative problem-solving methodology, offers a structured approach but does not fully address problem definition and solution generation. This research explores how integrating AI-driven frameworks, such as ChatGPT, with TRIZ can enhance innovation by expanding the knowledge discovery process and supporting solution selection beyond conventional expertise. The proposed framework leverages machine learning to define contradictions, establish evaluation criteria, and streamline innovation. A case study demonstrates its effectiveness in solving engineering challenges, highlighting its potential to improve decision-making and problem-solving across diverse fields.