Prof. (Dr.) Dattatraya Vishnu Kodavade is a distinguished academician and researcher currently serving as Professor & Head of the Computer Science & Engineering Department, and Dean (Projects & Consultancy) at DKTE Society's Textile and Engineering Institute,India. With over 32 years of teaching experience, he has made significant contributions to engineering education, research, and institutional development. He is a member of Association for Computing Machinery and actively contributes as a technical reviewer for several reputed international journals and conferences in the domains of Artificial Intelligence, Machine Learning, and High-Performance Computing. He has authored more than 40 research papers in leading international journals. Dr. Kodavade serves on the Board of Studies in Computer Science & Engineering at Shivaji University and is also a member of Academic Councils and Boards of Governors at various institutions across India. His research interests include Artificial Intelligence, Cybersecurity, Machine Learning, High-Performance Computing, IoT, and Robotics applications. He has contributed as a Data Auditor for the World Bank-funded Technical Education Quality Improvement Programme and is currently the Editor-in-Chief of an international journal in Knowledge-Based Systems. Additionally, he has been nominated as a ‘Margdarshak’ by All India Council for Technical Education for accreditation of engineering institutions in India.

Generative AI Beyond the Hype: Real Applications, Challenges and Opportunities Generative Artificial Intelligence (GenAI) has rapidly evolved from a trending concept into a transformative technology with practical impact across industries. Beyond the hype, GenAI is reshaping how organizations create content, automate workflows, enhance decision-making, and deliver personalized user experiences. From healthcare diagnostics and drug discovery to intelligent customer support, software development, education, finance, and cybersecurity, real-world applications demonstrate its growing value in improving efficiency, innovation, and productivity. However, the adoption of Generative AI also introduces significant challenges. Issues such as data privacy, model bias, misinformation, intellectual property concerns, lack of transparency, and high computational costs remain critical barriers to responsible deployment. Organizations must address these concerns through ethical AI frameworks, robust governance policies, human oversight, and sustainable infrastructure. At the same time, Generative AI presents vast opportunities for future growth. It has the potential to democratize creativity, accelerate research, bridge skill gaps, and enable new business models powered by intelligent automation. Emerging trends such as multimodal AI, domain-specific foundation models, and human-AI collaboration are expected to redefine industries and societal interactions in the coming years. This paper explores the reality of Generative AI beyond exaggerated expectations by examining its practical applications, current limitations, and future opportunities. It aims to provide a balanced perspective for researchers, practitioners, and policymakers seeking to harness GenAI responsibly while maximizing its benefits for innovation and sustainable development.