This tutorial will provide a primer on quantum computing and quantum algorithms with an overview of state-of-the-art industry roadmaps. He will then describe the interplay between artificial intelligence and quantum computing. One relates to using machine learning in multiple quantum computing aspects like experimental data analysis, quantum error mitigation, quantum error correction, quantum circuit synthesis, and data preparation. Of course, LLMs also have multiple applications in the field of quantum science and technology developments. The other is about the emerging field of quantum-assisted machine learning, where quantum processors pre-process classical data that then feed classical AI or handle clustering and dimensionality reduction, with the potential to provide exponential or polynomial speedups compared to the best classical methods available.