SPECIAL FEATURE | AI, cloud drive data sovereignty concerns: report
AI systems are increasingly used to analyze large volumes of security data across enterprise networks, cloud platforms and endpoints.
Artificial intelligence (AI) is becoming central to cybersecurity and network operations, but concerns about data sovereignty are slowing adoption, according to a briefing document published by Mobile World Live in partnership with Arqit and Intel.
The report, “Data Sovereignty in an AI and Cloud-Centric World: A Briefing Document for CTOs,” is based on interviews with more than 200 global IT and security leaders and examines how organizations are managing sensitive data in distributed computing environments.
It found that while most organizations consider AI a strategic priority for improving network security, deployment remains limited. Only a small percentage of companies say AI is not important to their operations, but many are still testing the technology rather than fully deploying it.
AI systems are increasingly used to analyze large volumes of security data across enterprise networks, cloud platforms and endpoints. The technology can identify patterns of malicious activity, automate threat detection and help analysts respond more quickly to cyberattacks. It can also function as a digital assistant, allowing security teams to query systems using natural language and receive actionable insights.
Despite these advantages, organizations face multiple challenges when integrating AI into cybersecurity infrastructure. According to the survey, the most common barrier to progress is concern about data sovereignty and privacy risks, cited by 62 percent of respondents. Other factors include secure data sharing, regulatory compliance and intellectual property theft.
Data sovereignty refers to the principle that digital information is subject to the laws of the country where it is collected or stored. However, the report notes that the concept has become more complex in modern cloud-based environments dominated by global service providers.
Even when data is stored within national borders, it may still fall under foreign jurisdiction if the infrastructure is operated by a company based in another country. Regulations such as the European Union’s General Data Protection Regulation (GDPR) also impose strict requirements on how organizations store and process data regardless of location.
As AI systems increasingly rely on large data sets that may cross national boundaries, chief technology officers must ensure that data governance practices comply with multiple legal frameworks.
The report argues that organizations need to move beyond the traditional view of sovereignty as simply a matter of where data resides. Instead, companies must focus on controlling who can access the data and how it is protected throughout its life cycle.
One emerging approach is confidential computing, which protects data while it is being processed by isolating workloads inside secure hardware-based environments known as trusted execution environments.
Intel’s confidential computing technologies, such as Intel SGX and Intel TDX, provide hardware-level protections that prevent unauthorized access to data even from cloud service providers. This approach helps organizations maintain control over sensitive workloads in public cloud and edge computing environments.
According to the survey, 80 percent of technology and security leaders expect to use confidential computing to support data sovereignty in the public cloud, edge environments or both within the next year.
The report also outlines three key tests organizations can use to evaluate whether a vendor supports genuine data sovereignty: confidentiality, availability and portability.
Confidentiality ensures that data remains protected from unauthorized access, including cloud service providers themselves. Availability means organizations must always be able to access their data, while portability ensures they can move workloads between providers without restrictions.
In addition to regulatory pressures, companies must also consider the competitive risks of delaying AI adoption. Survey respondents warned that postponing AI-driven security initiatives could affect operational efficiency, customer experience and overall competitiveness.
The report concludes that while data sovereignty concerns are legitimate, existing technologies can help organizations deploy AI securely without delaying innovation.
As cloud and edge computing environments continue to expand, the ability to manage data sovereignty effectively is expected to become a key priority for technology leaders overseeing AI-driven infrastructure.
