SEALSQ Corp, a company specializing in semiconductors, PKI, and post-quantum technology solutions, has clarified that recent advancements in enterprise artificial intelligence, including Anthropic’s Claude Opus 4.6, do not alter the current quantum computing threat landscape. While the release of advanced AI models marks significant progress in classical computing capabilities, SEALSQ emphasized that these developments do not impact the technical requirements needed for quantum-secure cryptographic systems.
To begin with, SEALSQ highlighted that Claude Opus 4.6 remains a classical large language model that operates within traditional computing environments. The system runs on standard CPU and GPU infrastructure and relies on floating-point numerical optimization methods. In addition, it follows classical information theory and computational complexity limitations. As a result, its capabilities focus on probabilistic reasoning, pattern detection, symbolic processing, and generating structured outputs based on trained data models.
However, quantum computing operates on an entirely different scientific foundation. Unlike classical AI systems, quantum computers rely on quantum mechanical properties such as superposition, entanglement, and quantum interference. Furthermore, cryptographically relevant quantum computing requires highly specialized hardware components, including scalable qubit architectures, advanced error correction systems, stable coherence times, and low-error quantum gate operations. Importantly, SEALSQ noted that advancements in classical AI do not contribute to or accelerate any of these quantum hardware requirements.
Cyber Technology Insights: Landis+Gyr Strengthens North American Smart Grid Security with SEALSQ Collaboration
Moreover, the company stressed that large language models cannot execute quantum algorithms regardless of their scale or reasoning complexity. For example, Claude Opus 4.6 cannot run Shor’s algorithm, which is used for breaking encryption methods like RSA and elliptic curve cryptography. Similarly, it cannot create efficient attacks against post-quantum cryptographic systems such as lattice-based, code-based, hash-based, or multivariate encryption approaches. Therefore, the potential cryptographic risks associated with quantum computing remain dependent on the development of large-scale, fault-tolerant quantum machines.
As a result, SEALSQ confirmed that the global quantum threat model remains unchanged. Governments, defense agencies, and global standards organizations continue to base their security risk timelines on the future development of cryptographically relevant quantum computers. Additionally, recent AI announcements have not contributed to improvements in qubit scaling, logical qubit stability, or quantum error correction capabilities. Likewise, they do not influence the foundation of NIST’s post-quantum cryptography standardization efforts.
From a cybersecurity architecture standpoint, SEALSQ emphasized that post-quantum cryptography and hardware-based security solutions remain essential. Technologies such as secure elements, trusted platform modules (TPMs), hardware security modules (HSMs), quantum-resistant PKI frameworks, and satellite-grade key management systems continue to play a critical role in maintaining digital trust. These solutions protect systems at physical, cryptographic, and lifecycle levels, which classical AI technologies cannot replace.
Cyber Technology Insights: SEALSQ and SEALCOIN AG Collaborate to Secure AI Agents Against Quantum Threats
Meanwhile, SEALSQ noted that market reactions to advanced AI announcements mainly reflect shifts in enterprise software and SaaS economics rather than changes in foundational security technologies. In particular, AI is expected to automate software development, knowledge-based tasks, and content generation. However, secure silicon, cryptographic hardware, and sovereign security infrastructure remain governed by physical limitations, regulatory certification frameworks, and long-term risk modeling.
Interestingly, SEALSQ pointed out that the rapid adoption of advanced AI may actually increase the urgency for quantum-secure infrastructure. As AI accelerates automation, it also expands the digital attack surface, speeds up vulnerability discovery, and enhances large-scale cyberattack capabilities, including social engineering and automated exploitation techniques. Consequently, post-quantum cryptography becomes even more critical for maintaining long-term security resilience.
Ultimately, while advanced AI continues to reshape how organizations process information and automate decision-making, quantum-secure technologies ensure that identity, data confidentiality, system integrity, and digital trust remain protected. Regardless of how powerful classical AI systems become, mathematically and physically grounded quantum-resistant security will remain a foundational requirement for future digital ecosystems.
Cyber Technology Insights: SEALSQ, Quantix Edge Partner on Spain’s First $25 Million Post-Quantum Chip Personalization Center
To participate in our interviews, please write to our CyberTech Media Room at info@intentamplify.com
