This study explores the integration of artificial intelligence and nanotechnology, examining how artificial intelligence techniques, including machine learning, deep learning, and neural networks, enhance the efficiency, precision, and scalability of nanotechnology applications. Main artificial intelligence This study examines the integration of artificial intelligence and nanotechnology, focusing on how AI techniques, including machine learning, deep learning, and neural networks, enhance the efficiency, precision, and scalability of nanotechnology applications. Key AI applications in nanotechnology include accelerating nanomaterial discovery and design optimization, improving drug delivery systems, and utilizing AI-driven nanosensors for biological and environmental monitoring. Furthermore, AI is applied to predict material properties, supporting innovations in energy. This study also assesses the challenges, opportunities, and potential of AI and nanotechnology integration for transformative progress in fields from healthcare and materials science to environmental sustainability. Ethical issues, including algorithmic bias, data privacy, and societal impact, are discussed, highlighting the necessity for transparent regulations and ethical frameworks to ensure the responsible application of AI-driven nanotechnology.