Mlambo, Tlangelani PZuva, T2026-09-232026-09-232026-09http://hdl.handle.net/10204/14944As digital technologies rapidly advance and data generation accelerates across sectors, effective data governance has become a critical enabler of organizational performance and innovation. However, despite substantial investments in digital transformation, many organizations continue to experience fragmented data practices, weak governance structures, and inconsistent data quality, limiting their ability to leverage data as a strategic asset. While numerous data governance frameworks exist, there remains limited consolidated evidence on their effectiveness within dynamic, AI-driven digital environments. This study addresses this gap by systematically evaluating contemporary data governance frameworks and their ability to support key dimensions such as data integrity, security, interoperability, accountability, and value creation in modern digital ecosystems. Adopting the PRISMA 2020 guidelines, the study reviews peer-reviewed literature published between 2022 and 2026, sourced from major databases including ResearchGate, ACM, Elsevier, IEEE, and Scopus. After applying rigorous inclusion and exclusion criteria, 10 relevant studies were selected from an initial pool of 50 articles. The findings reveal that data governance frameworks designed for cloud-based, metadata-driven, and real-time architectures are better suited to the demands of the digital and generative AI era. In particular, the Atlan Data Governance Framework emerges as highly adaptable due to its alignment with these characteristics. More broadly, the study highlights the critical features required for scalable and resilient governance in complex digital environments. By providing an evidence-based assessment of current frameworks, this research contributes to both academic literature and industry practice, offering actionable insights for organizations seeking to strengthen data governance and maximize data value. The study further recommends the adoption of modern, flexible governance models tailored to AI-driven ecosystems. Future research should expand the analysis to other technological and organizational contexts beyond digital environments for broader findings.FulltextenData GovernanceDigital environmentDigital governanceDigital transformationData ProtectionPRISMAConference Presentationn/a