High-Performance Data Architectures

Chapter 4. The Impact of Artificial Intelligence on Databases

Things are moving fast with artificial intelligence, with continuing growth in areas spanning from embedded intelligence to the democratization of AI through platforms such as ChatGPT. This is changing the roles and functionality of databases both from an operational and service-delivery standpoint, resulting in a mutually beneficial relationship. First, AI can be employed to boost database performance, enabling autonomous and near-autonomous operations and delivery of data services. Second, databases serve as the lifeblood of AI and ML, elevating the roles of databases to manage and provide the right data, at the right time—data that is trustworthy and of the highest quality.

AI for Better Database Performance

From a performance perspective, AI and ML promise to deliver significant gains for databases of all types. AI can play a role in discovering, processing, and searching data sets, delivering rapid results. According to Thomas Davenport and Thomas Redman, writing in MIT Sloan Management Review, “Artificial intelligence is quietly improving the management of data, including its quality, accessibility, and security.”¹ They continue: “Managing data…is a labor-intensive activity: it involves cleaning, extracting, integrating, cataloging, labeling, and organizing data, and defining and performing the many data-related tasks that often lead to frustration among both data scientists and employees without ‘data’ in their ...