Confidential Computing Expands from CPUs to GPUs, Containers, and Agentic AI as Enterprise Demand Accelerates
ABI Research finds Confidential AI is moving beyond niche deployment as performance gains, new hardware protocols, and
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NEW YORK, Sept. 10, 2026 (GLOBE NEWSWIRE) — Confidential computing is becoming a foundational security layer for AI, with protection expanding from CPUs into GPUs, multi-GPU environments, containers, and emerging agentic AI workflows, according to global technology intelligence firm ABI Research. The firm finds that GPU-based confidential computing has become a major catalyst for Confidential AI adoption as organizations look to protect data, models, and memory while AI workloads are actively running.
“Confidential computing is no longer a CPU-only conversation,” says Aisling Dawson, senior analyst at ABI Research. “As AI deployments scale and enterprises face growing pressure to secure data in use, the market is shifting toward Confidential AI architectures that can protect inference, training, and increasingly agentic workflows without sacrificing the performance needed for production environments.”
ABI Research notes that CPU-based confidential computing is closest to mass-market adoption, but GPU-based deployments are seeing especially strong momentum because they address one of the biggest gaps in AI security: protecting data while it is being processed. The firm also highlights rising interest in confidential containers alongside confidential virtual machines, as enterprises running cloud-native and Kubernetes-based environments seek lower complexity, reduced attack surfaces, and more flexible deployment models for AI workloads
The vendor landscape reflects that momentum. NVIDIA continues to set the pace in confidential GPUs with advances spanning Hopper, Blackwell, and Vera Rubin platforms, while Intel, AMD, and Arm are strengthening the CPU and heterogeneous compute foundations needed to support broader Confidential AI deployments. On the software side, companies including Anjuna, Red Hat, Fortanix, Decentriq, and IBM are developing platforms and controls that help enterprises secure AI model weights, enable attestation, support confidential containers, and address new agentic AI governance requirements
“Agentic AI is creating a new security inflection point for the confidential computing market,” Dawson says. “While confidential computing will not solve every agentic risk, it is emerging as one of the most credible hardware-rooted approaches for securing agent execution, protecting sensitive memory, strengthening auditability, and building trust in high-value enterprise AI systems. Vendors that pair strong attestation, performance optimization, and ecosystem collaboration will be best positioned to capture this opportunity.”
These findings are from ABI Research’s Confidential Computing and AI report, part of the company’s Quantum Safe Technologies research service, which includes research, data, and ABI Insights.
About ABI Research
ABI Research is a global technology intelligence firm uniquely positioned at the intersection of technology solution providers and end-market companies. We serve as the bridge that seamlessly connects these two segments by providing exclusive research and expert guidance to drive successful technology implementations and deliver strategies proven to attract and retain customers.
ABI Research是一家全球性的技术情报公司，拥有得天独厚的优势，充当终端市场公司和技术解决方案提供商之间的桥梁，通过提供独家研究和专业性指导，推动成功的技术实施和提供经证明可吸引和留住客户的战略，无缝连接这两大主体。
For more information about ABI Research’s services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com.
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