Abstract
Artificial Intelligence is increasingly shaping the practice of biobanking by influencing how biobanks evolve and operate, especially when it concerns their relationship to data. By assessing four key parameters-size, site, speed, and access-this paper analyzes the impact of AI technologies on biobanks, presenting them as dynamic boundary objects that produce biovalue by transforming biological material and data into intangible assets of the data-driven bioeconomy. Historically rooted at the intersection of health research and healthcare, biobanking is continually reshaped by emerging technologies, policies, and societal expectations. While biobanks were originally defined as collections of samples and associated data, they have recently evolved into complex infrastructures for both data and samples.