“The real opportunity lies in how effectively governments operationalise the vast volumes of data they already hold,” said Matthias Nijs.
A potential shift toward an AI-native government in the United Arab Emirates will depend heavily on how effectively unstructured data is managed and activated, according to new commentary from Datadobi.
The company highlights that while governments are accelerating AI adoption, a significant portion estimated at 80–90% of enterprise and public sector data remains unstructured, spanning documents, emails, videos, and legacy systems. Much of this data is fragmented, unclassified, and underutilised, limiting its readiness for AI-driven initiatives.
This creates both operational and security challenges. Without clear visibility into data environments, public sector organisations risk compliance gaps, inefficiencies, and increased exposure to cyber threats. Datadobi stresses that governments must shift from passive data storage to active data management, including classification, metadata enrichment, and policy-driven automation.
The commentary also underscores the importance of vendor-neutral strategies, particularly in complex government ecosystems that span multiple ministries and hybrid cloud environments. Such approaches can help avoid vendor lock-in while ensuring flexibility, control, and auditability across systems.
With the right data foundations in place, unstructured data can evolve from a liability into a strategic asset enabling AI systems to deliver improved decision-making, faster service delivery, and more citizen-centric outcomes.
As the UAE advances its AI ambitions, the ability to govern and operationalise data at scale will be critical in determining the success of its AI-led public service transformation.
