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14/09/2026 10:09 am
TL;DR: Long-lived sensitive data, not just quantum-vulnerable algorithms, is the real prioritisation problem in post-quantum cryptography planning, according to Ground Labs. The article argues that data intelligence should determine which records, copies, and exposure paths matter first, because replacement, confidentiality lifetime, and propagation shape quantum resilience more than retention alone.
NHIMG editorial — based on content published by Ground Labs: How to identify long-lived sensitive data for quantum readiness
By the numbers:
- Google Cloud is targeting full quantum readiness by 2029.
Questions worth separating out
Q: How should teams prioritise data for post-quantum cryptography migration?
A: Prioritise data by confidentiality lifetime, replaceability, and exposure spread.
Q: Why is long-lived sensitive data more important than data retention?
A: Retention tells you how long data is kept.
Q: What are the signs that sensitive data will remain exposed after encryption changes?
A: Look for duplicated records in backups, exports, collaboration tools, archives, and downstream analytics environments.
Practitioner guidance
- Classify data by confidentiality lifetime Build a classification step that separates retention requirements from exposure harm, then tag biometrics, identity attributes, health records, and regulated records as enduring data where appropriate.
- Map propagated copies across environments Use discovery across on-premises, cloud, backups, archives, and collaboration tools to find duplicates, exports, and shadow copies that extend exposure beyond the source system.
- Pair cryptographic inventory with data intelligence Link algorithm and certificate inventories to the datasets they protect so PQC migration can be prioritised by business harm, not by technology count alone.
What's in the full article
Ground Labs' full blog post covers the operational detail this post intentionally leaves for the source:
- Detailed examples of how data intelligence identifies long-lived records across structured and unstructured stores
- Operational distinctions between retention timeline, confidentiality timeline, and exposure timeline in practice
- How the Enterprise Recon approach is used to locate unexpected duplicates and exported copies
- The article's full framing of quantum readiness priorities across backup, archive, and cloud estates
👉 Read Ground Labs' article on identifying long-lived sensitive data for quantum readiness →
Long-lived sensitive data and PQC readiness: what should teams do first?
Explore further
14/09/2026 10:10 am
Long-lived sensitive data is the real quantum-readiness control point. The article is right to move the discussion away from algorithm lists and toward data that remains harmful if disclosed years later. For identity programmes, biometrics, identity attributes, and regulated personal data are especially important because they cannot be reissued the way many credentials can. The practitioner conclusion is simple: data longevity must shape quantum prioritisation, not just cryptography inventories.
A question worth separating out:
Q: What should security teams do first when planning for quantum-safe data protection?
A: Start with discovery of long-lived data and then connect that discovery to the cryptography protecting it. That sequencing helps teams focus limited remediation effort on irreplaceable records and on environments where copies have spread beyond current control assumptions.
👉 Read our full editorial: Quantum readiness starts with long-lived sensitive data discovery
