The creation and processing of large amounts of data -- coupled with expanding innovations, such as artificial intelligence and machine learning -- present many opportunities for organizations to make better use of their data and find trends to inform business decisions. But there are also many challenges with AI storage architecture, including planning for large data stores and heavy compute needs. Planning storage for AI can be a difficult task. Chinmay Arankalle, senior data engineer at Energy Exemplar and co-author of The Artificial Intelligence Infrastructure Workshop, hopes the book will bring clarity on how to implement AI and storage for AI. The authors wrote that, when designing an AI system, organizations should consider storage requirements upfront to fit the type of analysis they intend to perform.