Safety
Organisations should assess both the reliability of quantum-enabled AI and the potential exposure of sensitive data to future quantum attacks. Security planning should distinguish demonstrated threats from speculative capabilities.
AI governance & regulation IWIB4AI session Needs review
The Impact of Quantum Computing in AI
Integrating quantum computing into AI raises questions about capability, cybersecurity, governance and equitable access.
Draft – legal and case law references not yet verified
Summary
This use case examines how quantum computing could support AI development and how access to quantum technology might be broadened. Practical advantages remain application-dependent and uncertain, while sufficiently powerful quantum computers could undermine widely used public-key cryptography protecting AI systems and data. Responsible adoption therefore requires evidence-based capability assessment, security planning and attention to who can access and benefit from the technology.
The Problem
How can organisations explore quantum-enabled AI without overstating its capabilities, weakening data protection or concentrating access among well-resourced actors? Governance must accommodate uncertain technical progress while preparing for security risks that may require substantial advance planning.
Ethical Grounds
Inclusion
Specialist infrastructure, expertise and costs can restrict participation in quantum-enabled AI. Efforts to democratise access should address skills and meaningful opportunities to use the technology, not merely infrastructure availability.
Transparency
Claims of quantum advantage should identify the task, comparison baseline and limitations. Clear communication helps decision-makers distinguish experimental promise from established operational benefits.
Accountability
Organisations combining quantum services with AI should assign responsibility for validation, data protection and security across providers and deployers. Technical novelty does not remove existing governance obligations.
Legal Compliance
| Framework | Provision | Relevance |
|---|---|---|
| EU AI Act | Arts. 9 and 15 | Where a quantum-enabled AI system qualifies as high-risk, applicable risk-management, accuracy, robustness and cybersecurity requirements apply irrespective of its computing architecture. |
| GDPR | Art. 32 | Where personal data are processed, controllers and processors must implement risk-appropriate security measures, taking account of the state of the art and relevant developments affecting cryptographic protection. |
| NIS2 | Art. 21(2)(a) and (h) | For entities within scope, cybersecurity risk-management and cryptography policies provide a basis for assessing quantum-related threats and planning proportionate protective measures. |
Sources
No sources linked to this use case yet.
Key Takeaways
- Validate claimed quantum advantages against credible conventional AI baselines.
- Inventory cryptographic dependencies and assess priorities for post-quantum migration.
- Assign clear governance and security responsibilities across AI and quantum service providers.
- Pair broader technology access with training and safeguards for sensitive data.
Related Use Cases
From the Session
Use Case – The Impact of Quantum Computing in AI
Speakers
Caryn Lusinchi
Sr Non-Resident Fellow in AI Governance, Global Governance Institute, Brussels
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