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AI is already helping some threat groups automate and speed up cyber operations, while also offering ways to strengthen defense. Quantum computing is a different, longer-term concern: today’s quantum computers cannot break the cryptography discussed by the U.S. Government Accountability Office (GAO), but a sufficiently capable future machine could threaten some widely used cryptographic systems. Organizations should address AI risks in current security operations and begin planning cryptographic migration separately.
How AI and quantum computing change cyber threats
These technologies affect cybersecurity through different mechanisms and on different timelines. AI can help people carry out existing kinds of attacks more efficiently, and it can create new risks when AI systems or their supply chains are compromised. Quantum computing could eventually undermine certain cryptographic protections if a future machine reaches the necessary capability.
| Technology | Threat addressed | What the evidence establishes | Practical response |
|---|---|---|---|
| AI | Malicious use of AI, and attacks on AI systems and their supply chains | ENISA reports threat-group use of AI in activity during July 1, 2024–June 30, 2025. | Threat-model AI use, secure AI systems, and include AI-related vulnerabilities and incidents in security operations. |
| Quantum computing | Future compromise of certain cryptography used for authentication and data confidentiality | GAO says current quantum computers cannot break the cryptography discussed in its October 2026 report; the arrival date of a capable future machine is uncertain. | Inventory vulnerable cryptography, test post-quantum replacements, and plan a staged migration. |
These workstreams are not substitutes for one another. Post-quantum cryptography (PQC) does not prevent AI-assisted social engineering, and AI-based defense does not update cryptography that may be vulnerable to a future quantum computer.
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AI as an operational aid
ENISA’s October 2025 threat-landscape report describes threat groups using commercial large language models (LLMs) and diverted models to support operations. Reported uses include automating social engineering, accelerating malicious-tool development, conducting research and reconnaissance, and helping evade anomaly detection. The report also describes synthetic identities or communications and malicious lures created with AI.
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Using AI to assist an operation is different from directly compromising an AI system. ENISA says public evidence of AI misuse as a tool is more common than evidence of direct compromise. It also discusses threats involving compromised AI supply-chain components and proof-of-concept attacks on model behavior; these are risks to account for, not evidence that every AI system is compromised.
What the broader 2025 figures do—and do not—show
ENISA’s 2026 threat-landscape summary analyzes incidents from January 1 through December 31, 2025. It reports 4,709 hacktivist claims against EU Member States; a claim is not the same as a verified successful intrusion. It also reports more than 48,000 new CVEs in 2025, a 22% increase from the prior year. These figures describe different units and populations, and neither establishes that AI caused the activity or vulnerabilities.
The earlier ENISA report covers July 1, 2024 through June 30, 2025, not calendar year 2025. Its AI examples should be read within that reporting window rather than combined with the 2026 summary’s full-year figures.
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Can quantum computers break encryption now?
No, not the cryptography covered by GAO’s October 6, 2026 report. GAO states: “Today’s quantum computers cannot yet break this cryptography.” The concern is a future cryptographically relevant quantum computer—one capable of breaking certain cryptographic systems—not a demonstrated ability of machines available today.
If such a machine is developed, it could threaten some cryptography used to authenticate users and protect data confidentiality. One planning concern is “harvest now, decrypt later”: an attacker may capture and store encrypted data now in the hope of decrypting it in the future. This scenario does not mean every encrypted data type or algorithm is equally vulnerable.
GAO reports that expert estimates vary widely. Most industry experts it cites believe a cryptographically relevant machine could be developed as soon as the 2030s, but that is an estimate, not a guaranteed arrival date. See GAO’s report on federal preparation for the quantum threat.
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What post-quantum cryptography means
Post-quantum cryptography is cryptography designed to protect systems against attacks from both conventional computers and future quantum computers. It is software-based cryptography, not a quantum computer and not a way to stop AI misuse.
NIST says three PQC standards are ready for implementation. Its migration guidance describes moving from quantum-vulnerable algorithms to post-quantum digital-signature and key-establishment schemes. The transition involves finding where vulnerable algorithms are used, selecting and testing replacements, and updating systems while preserving interoperability.
NIST’s overview says federal agencies are required to use the standards; it also notes that many governments, national cryptographic authorities, and standards organizations have adopted them. Those statements describe the scope of NIST’s overview, not a universal legal requirement for every private organization or country. NIST’s IR 8547 transition document is an initial public draft published November 12, 2024.
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What organizations should do to prepare
Manage AI risk in current operations
- Identify where staff, products, and security teams use AI, and assess how those uses could affect access, sensitive information, and operational decisions.
- Include AI services, models, and third-party components in security review and supply-chain risk management; monitor for vulnerabilities and compromises.
- Ensure incident-response processes can track and handle AI software vulnerabilities or compromises, including reporting and sharing relevant indicators where applicable.
- Use AI defensively where it fits the organization’s capabilities and controls. The White House’s June 6, 2025 executive order identifies vulnerability discovery, scaled threat detection, and automated cyber defense as potential benefits, not guaranteed outcomes.
ENISA likewise notes that AI can aid security operations and help mitigate adversarial attacks, but emphasizes the need to ensure the trustworthiness and security of the AI systems themselves. Its July 7, 2026 Frontier AI publication offers initial recommendations for authorities, defenders, and service providers to build capabilities for machine-speed threats; ENISA says these recommendations are not an all-inclusive checklist and are expected to be refined.
Start cryptographic migration planning
- Build a cryptographic inventory. Locate systems, applications, services, and suppliers that use cryptography, including the algorithms and protocols on which authentication and data protection depend.
- Prioritize exposure. Identify information that must remain confidential for a long time, systems that are difficult to update, and dependencies that could delay a transition.
- Plan and test replacement. Evaluate NIST’s PQC standards in the context of the organization’s systems. Test interoperability, performance, recovery, and supplier readiness before broad deployment.
- Fund and govern the work. Assign owners, budget for updates and testing, and track dependencies and milestones across a migration that may take years.
These steps follow NIST’s advice to identify vulnerable-algorithm use and plan system replacement or updates. GAO’s October 2026 review shows why a standards announcement alone does not complete the work: none of 24 selected U.S. federal agencies fully addressed the preparation practices evaluated. GAO identified gaps in cryptographic expertise, inventory processes, funding identification, and PQC testing plans. That result applies to those selected agencies and that review, not to every public or private organization.
Which U.S. policy dates apply?
The June 6, 2025 White House executive order gives directions to U.S. federal agencies; it does not establish a universal private-sector deadline. It directs CISA, in consultation with NSA, to publish and regularly update product categories in which PQC-supporting products are widely available. It also specifies that agencies support TLS 1.3 or a successor as soon as practicable and no later than January 2, 2030. Organizations outside the federal requirements should not treat that date as a general legal deadline, though government requirements may matter to their contracts or systems.
The same order describes AI’s potential to “rapidly identify[] vulnerabilities, increas[e] the scale of threat detection techniques, and automat[e] cyber defense.” It also directs federal agencies to incorporate management of AI software vulnerabilities and compromises into vulnerability-management processes, including incident tracking, response, reporting, and indicator sharing. Read the executive order for the government-specific directions.
Quick Recap
How to set priorities
- Address AI exposure as part of current security operations. The reported uses are already operational, while the evidence does not imply AI is necessary for every attack.
- Begin PQC preparation before a quantum breakthrough. Inventory and migration planning take time, while the arrival of a capable quantum computer remains uncertain.
- Keep the plans distinct and coordinated. Assign separate owners and milestones for AI security and cryptographic migration, while coordinating procurement, incident response, system upgrades, and supplier engagement.
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