Experts are warning that artificial intelligence (AI) must be carefully evaluated and governed before it is adopted widely in healthcare, saying rapid advances do not automatically translate into safe use for patients.

Engineering researchers have developed a mathematical framework that can be used to help hunger-relief organizations get food to households that need it more efficiently than conventional methods. The advance, which has already been incorporated into an app, could also lead to improved efficiency for other businesses that face logistical challenges associated with deliveries and volunteer assignments.

AI is rapidly entering classrooms worldwide, but current education governance models are not designed to manage its systemic impact. A new study argues that AI should be understood not merely as a teaching tool, but as a governance actor that reshapes authority, accountability, and professional autonomy in education systems. The article proposes a reconfigured hybrid governance framework to help education systems harness AI’s benefits while protecting democratic values, learner autonomy, and professional judgment.

The School Digital Renewal Process (SDRP) has evolved from infrastructure-focused adoption to deep pedagogical transformation centered on personalized, competence-based learning. Traditional indicators—such as device availability or connectivity—lose relevance at advanced SDRP stages. This article proposes a novel, evidence-based approach to constructing indicators that capture shifts in learning content and organization through automated analysis of schools’ digital footprints (publicly available digital materials) using AI tools. Drawing on Bloom’s Revised Taxonomy and empirical data from international schools, we demonstrate the feasibility of tracking second-order educational change without relying on teacher surveys. The framework supports comparative monitoring of digital transformation aligned with the demands of the AI era. The article introduces a groundbreaking innovation: the use of AI tools for gathering and analyzing indicators from publicly available digital sources in education institutions. This approach offers a scalable and cost-efficient way to track and evaluate SDRP at later stages of its development.