From documents dealing with the early exploration of the Americas to numerous sources crucial to understanding the affairs of Hernando Cortés, the history of early colonial Mexico, and the activities of the inquisition, the Library of Congress (LoC) holds a varied but significant collection of Spanish American colonial documents in its Manuscript Division. While the library has carried out the enormous task of digitising hundreds of folios in their collections and making these available online, the documents in this division still pose a significant challenge. These are written in Early Modern Spanish, with calligraphies that only highly specialised scholars can decipher and, therefore, access. Furthermore, without available digital transcriptions, it can take scholars and specialists years to query, find, and connect the information in these documents on a large scale or between different collections. These documents contain vital information to understand how the Spanish Empire governed the Americas, the role and establishment of the church in the viceroyalties, living conditions, acts of contestation, social structures and knowledge of the indigenous cultures. However, this information remains "locked" and accessible only to a few. New developments in Artificial Intelligence (AI) now allow us to train computers to carry out the automated transcriptions of these documents. They also facilitate new ways of identifying, querying, extracting, mapping and analysing information through annotating specific words and knowledge categories. Using linguistic means, these approaches now enable us to automatically identify place names, people names, dates, institutions, and other complex concepts of historical interest. Using the Hans P. Kraus collection in the Manuscript Division of the LoC as the main case study, the proposed fellowship will: 1) Implement Handwritten Text Recognition models to accomplish the automated transcription of the digital material available in the collection from the sixteenth and seventeenth centuries; 2) Create an annotated version of the collection using Natural Language Processing techniques, enabling the identification and analysis of information in a text mining style; 3) Present these approaches, train staff, and establish a pipeline at the LoC for implementing these methods with the other Spanish American collections; and 4) Carry out a feasibility study for creating citizen science programs using AI approaches to historical collections with users and members of the LoC, the LC Labs, and the Hispanic Reading Room.