Preparing Data and Cultivating a Data Culture for AI Success

Data, a strategic asset

Ensuring data is managed effectively is an often overlooked prerequisite for making AI work as intended. Creating the right conditions means treating data as a strategic asset: organizing it, cleaning it, and having the right policies in place so it stays reliable over time.

“CIOs should focus on data quality, integrity, and relevance,” says Paul Smith, CIO at Amnesty International. His organization works with unstructured data every day, often coming from external sources. Given the nature of the work, the quality of that data can be variable. Analysts sift through documents, videos, images, and reports, each produced in different formats and conditions. Managing such a high volume of messy, inconsistent, and often incomplete information has taught them the importance of rigor.

“There’s no such thing as unstructured data, only data that hasn’t yet had structure applied to it,” Smith says. He also urges organizations to start with the basics of strong, everyday data-governance habits. That means checking whether the data is relevant, and ensuring it’s complete, accurate, and consistent, and outdated information can skew results.