62% of respondents cite data sovereignty and privacy risks as the biggest factor slowing AI projects in the public cloud

Core Insights - Data sovereignty and privacy risks are now the primary barriers to AI adoption for network protection, with 62% of organizations citing these as the biggest factors slowing AI projects in the public cloud [3][9] - One in six organizations (16%) lack access to facilities with guaranteed data sovereignty, highlighting the urgency of addressing these issues for effective AI implementation [3][9] Group 1: Survey Findings - A survey conducted among Mobile World Live readers revealed that 62% of respondents identified data sovereignty and privacy risks as the main obstacles to AI projects in the public cloud [3][9] - Only 8% of organizations can rely on guaranteed data sovereignty at edge locations, indicating a significant gap in current capabilities [7][9] - 80% of respondents expect to utilize confidential computing to achieve data sovereignty in cloud or edge locations within the next 12 months, with 41% planning deployments across both environments [9] Group 2: Industry Context - As AI becomes integral to network operations, security teams face increasing pressure to manage sensitive data while ensuring it remains under sovereign control [2][5] - The integration of AI into network security is essential for detecting anomalies and enhancing network resilience, but it complicates data sovereignty due to the need for data sharing across various platforms [5][6] - Delays in AI transformation are already impacting operational efficiency (53%), competitive advantage (48%), and customer experience (45%) [9] Group 3: Company Initiatives - Arqit is focused on protecting data in motion across complex environments, aiming to help organizations enhance network security without compromising sensitive data control [7] - At MWC 2026, Arqit and Intel will showcase solutions that enable organizations to safely leverage AI for network safety while ensuring end-to-end data sovereignty [7]