Yoram Novick, CEO, Zadara, explains how healthcare providers can adopt Artificial Intelligence securely without losing control of sensitive patient data.
It comes as no surprise that Artificial Intelligence is redefining healthcare today in myriad ways, enhancing diagnostics, personalising treatments, streamlining operations and improving patient outcomes.
AI is helping care providers deliver faster and more efficient services from radiology image analysis to virtual health assistants. As adoption of AI accelerates, so does the concern over where and how sensitive healthcare data is stored and analysed.
Hospitals and research institutions manage some of the most highly regulated and confidential data in existence. Electronic health records, clinical trial information and related data must be handled with the utmost care to comply with regulations such as HIPAA, GDPR and various national data privacy laws. The pressing question is: how can healthcare organisations embrace AI without relinquishing control over the sensitive data that powers it?
One emerging solution is the use of sovereign AI clouds – AI-ready platforms deployed on-premises or in regional data centres that preserve full jurisdictional control over healthcare data. These clouds allow organisations to benefit from the power of AI while keeping sensitive information local, compliant and secure.
The complexity of AI in healthcare
It is clear that AI holds tremendous promise for healthcare. AI applications can detect tumours in imaging scans with great precision, compare with past scans and personalise treatment plans based on that data. AI can also automate administrative tasks like coding and billing and reduce errors.
These functions depend on access to massive volumes of high-quality healthcare data. However, processing and analysing that data, especially on public clouds, raises questions about compliance, control and risk. Healthcare organisations must protect patient privacy, ensure that data does not leave its jurisdiction and maintain full transparency over how it is used. In many cases, existing public cloud offerings cannot cover these requirements.
Why data sovereignty matters
Data sovereignty means that data is subject to the laws and governance of the country where it is collected and processed. In healthcare, this is not just a technical concern, it is a legal and ethical imperative. Patient trust depends on privacy and governments have strict controls on how data is shared and stored.
Many AI tools require data to be sent to centralised cloud environments for processing which may exist in other countries, creating risk for healthcare organisations. Even if the cloud provider stores healthcare data in a local data centre, backups, metadata or other copies may still be transferred to data centres in other countries.
In some cases, even anonymous data can present a threat if it is stored in regions with weaker privacy laws. For this reason, regulators and health institutions are turning to localised infrastructure to ensure AI does not become a compliance liability.
Sovereign AI clouds
Sovereign AI clouds are purpose-built environments that offer AI capabilities while ensuring healthcare data stays within national borders. These platforms are operated under local laws, with data centres located in-country utilising security protocols that align with domestic healthcare standards.
With sovereign AI clouds, hospitals and health systems can run and train AI models and process diagnostic information without transferring data to third-party cloud environments that are potentially overseas. This ensures that data sovereignty is preserved while still enabling the full functionality of AI for healthcare.
These environments also support Edge AI, allowing real-time inference to occur at the point of care. For example, radiology scans can be analysed instantly on-site to flag anomalies or wearable health data can trigger alerts for early intervention, all while remaining securely within the hospital’s infrastructure.
Building AI resilience
Beyond compliance, sovereign AI clouds offer resilience. They reduce dependence on foreign infrastructure, enable faster response times and provide healthcare organisations with more direct control over their digital assets.
They also support the integration of cybersecurity best practices such as zero-trust architectures and data backups that are essential in an era of ever-growing ransomware threats. These platforms can also track changes in patient data over time to identify subtle signs of corruption or fraud. This kind of insight depends not only on large datasets but also on the ability to verify the integrity of that data.
AI must be trained and used responsibly with clear rules around data quality and governance. By keeping data local, secure and compliant, sovereign AI clouds enable healthcare institutions to fully embrace AI while upholding the ethical and legal responsibilities that define the industry.
With the right infrastructure in place, healthcare providers can unlock the life-saving potential of AI safely and responsibly.
