Convergence of AI, Quantum Risks Is Impacting Cybersecurity
Recent research from Thales highlights how AI adoption and emerging quantum computing threats are putting pressure on existing security measures. The 2026 Thales Data Threat Report: Quantum & AI Trends, based on responses from 3,120 security and IT management professionals across 20 countries, found that 98% are considering how the two technologies affect each other. Thirty percent reported a significant increase in security budgets specifically for AI.
The research, conducted by 451 Research by S&P Global, examines both the risks and potential benefits of the technologies. Fifty-seven percent believe quantum computing will enhance machine learning, while 54% expect it to enable advanced simulations of complex systems. The security findings span data governance, cloud infrastructure, and preparations for quantum-resistant encryption.
Cloud Assets Top the Target List
Cloud-based storage, cloud-delivered applications, and cloud management infrastructure were the three most frequently cited asset types targeted by attackers, at 35%, 34%, and 32%, respectively. The report connects that exposure to the large datasets required for AI training and the rapid expansion of AI infrastructure.
Organizations are also looking to cloud providers for protection: 67% reported investing in their cloud provider’s AI-specific security tools, compared with 63% using an established security provider. Respondents could identify multiple sources of protection, including startups, large language model providers, and internally developed controls.
Encryption coverage remains incomplete. Only 7% of organizations reported encrypting more than 80% of their sensitive cloud data, while 29% reported encrypting more than 60%. The report’s chart puts the average share encrypted at 47% in 2026, down from 51% in 2025.
The findings extend concerns raised in coverage of Thales’ 2025 cloud security research, when AI security already ranked second to cloud security in spending priorities and 52% of respondents reported that AI security spending was displacing existing security budgets. The latest report again places AI security second, while its historical comparison shows average sensitive cloud data encryption coverage falling from 51% in 2025 to 47% in 2026.
AI Spending Meets Data Governance Gaps
AI security was the second-highest prioritized security spending category overall, behind cloud security. But protecting data ranked much lower among the measures organizations use to judge AI projects: Reducing or managing risks of data loss or noncompliance placed sixth among seven success criteria, at 35%.
Improving customer experience led those measures at 68%, followed by reducing employee toil through greater task automation at 63%. Meanwhile, poor data quality or initial data governance was the leading inhibitor to AI adoption, cited by 65%; security risks from exposed data followed at 61%. Another 51% cited AI initiatives moving too quickly to be properly secured.
