Information access systems, especially search engines and recommender systems, play a vital role in the access to information that is crucial for decision-making and action in the world. The emergence of Generative Artificial Intelligence (GenAI) has led to more advanced user experiences in these systems with natural user-system interactions and auto-generated answers and suggestions, potentially saving people time and cognitive effort, while improving task outcomes. This chapter explores the synergies between GenAI and information access and provides a framing for the rest of the book. GenAI technologies, such as transformers and large language models, have revolutionized various fields, including creative writing, software development, and multimodal content generation. We briefly discuss ongoing GenAI-related research in search and recommendation that is exploring areas such as generative document retrieval, grounded answer generation, generative recommendation, and generative knowledge graphs, enhancing the capabilities of information systems. We also cover other topics such as combining information interaction modalities (e.g., data types, interaction paradigms) in different ways to create unified, so-called “panmodal” GenAI-powered information experiences that leverage the strengths of different interaction modes and highlight the growing interest and collaboration in GenAI and its applications in information access. We conclude by discussing the ethical considerations and challenges that come from the rise of this new technology, emphasizing the need for responsible development and deployment to harness its potential while mitigating risks.