Notifications
Clear all
Topic starter
20/08/2026 6:10 pm
TL;DR: Quantum computing is turning “harvest now, decrypt later” into an immediate governance problem because organizations often cannot see where sensitive data is encrypted, what keys protect it, or which datasets carry the highest business impact, according to BigID. The practical lesson is that readiness starts with data exposure mapping and key visibility, not an abstract cryptography refresh.
NHIMG editorial — based on content published by BigID: Quantum computing is coming, but most organisations are preparing for it the wrong way
Questions worth separating out
Q: What is the biggest failure mode in quantum readiness planning?
A: The biggest failure mode is treating quantum readiness as a cryptography upgrade project while ignoring data visibility.
Q: When should organisations prioritise quantum risk work over other security projects?
A: They should prioritise it when high-value data has long retention, broad access, or heavy reuse in analytics and AI workflows.
Q: How do security teams know whether encryption monitoring is actually working?
A: They should measure how quickly misconfigured buckets, expired keys and unexpected access patterns are detected and remediated across all clouds.
Practitioner guidance
- Discover encrypted data across all estates Build an inventory of encrypted datasets in cloud, SaaS, and on-prem environments, then tag each by sensitivity, retention, and business criticality.
- Inventory keys, secrets, and service identities Locate encryption keys, key management systems, API keys, tokens, and credentials, including those embedded in code and pipelines.
- Map sensitive data to access paths Connect PII, PHI, financial records, intellectual property, and AI training inputs to the identities and services that use them.
What's in the full article
BigID's full analysis covers the operational detail this post intentionally leaves for the source:
- How to inventory encrypted data across cloud, SaaS, and on-prem systems without missing shadow repositories
- How to map keys, secrets, and cryptographic assets to the identities and services that can reach them
- How to prioritise PII, PHI, financial, and AI data by exposure risk instead of treating all encryption as equal
- How to use a data-centric workflow to sequence remediation before cryptographic migration begins
👉 Read BigID's analysis of quantum readiness and data exposure risk →
Quantum risk is a data visibility problem, not only a crypto problem?
Explore further
20/08/2026 6:46 pm
Quantum readiness is really a data exposure programme. The article is correct to shift attention away from algorithms alone because most organisations cannot govern what they cannot see. Encryption strength matters, but visibility into encrypted datasets, retention, and access paths determines whether that strength has any practical value. Practitioners should treat quantum planning as exposure management, not a future cryptography refresh.
A question worth separating out:
Q: What role do non-human identities play in quantum exposure?
A: Non-human identities often carry the permissions that reach keys, secrets, pipelines, and protected datasets. If those identities are overprivileged or poorly lifecycle-managed, they expand the blast radius of a future cryptographic failure. Quantum planning therefore needs to include service accounts, tokens, and automation paths, not only human users.
👉 Read our full editorial: Quantum readiness starts with data exposure, not just encryption
