Executive Summary
- Data recorded today will be harvested for compliance, advanced analytics and model retraining for years to come.
- For many years, storage innovation was primarily defined by increases in capacity. Today, the expectations placed on storage infrastructure are much broader.
- Here, Uwe Kemmer, Director, Field Application Engineering at WD (formerly Western Digital) asks how can we prepare for tomorrow with long-term storage devices?
AI has fundamentally rewritten the data playbook, transforming how organisations create, use and retain data. As businesses deploy increasingly valuable information sets, from LLM training assets and model outputs to logs, the foundational systems that preserve these insights and make them available in future are becoming increasingly valuable too.
For enterprise teams and data centre operators, this is changing the role of storage. Whilst capacity, performance and power efficiency remain fundamental, long-term data integrity and cyber resilience are becoming equally important. Now, the role of infrastructure requires protecting data throughout its operational and retention lifecycle, rather than only serving to accommodate data growth alone.
This challenge extends beyond defending against today’s potential cyber threats. Storage needs to be designed with a longer security horizon in mind, including the potential impact of quantum computing.
Data is a long-term strategic asset, not a short-lived trend
AI is accelerating data growth, but it can also extend the useful life of information. Data recorded today will be harvested for compliance, advanced analytics and model retraining for years to come.
To manage this economically, enterprise architectures rely heavily on high-capacity HDDs. While flash technologies dominate performance-critical hot tiers, HDDs remain the undisputed backbone of large-scale storage, providing the capacity, economics and longevity needed to archive data at scale.
This means that data teams need to consider how the data is being stored today, as well as how value and security will be maintained over its entire lifecycle. If the underlying infrastructure is compromised, the data that organisations are retaining to drive future AI innovation could instead become an organisational, financial and regulatory liability.
The quantum challenge starts today
Current encryption technologies remain effective against conventional threats. However, quantum computing is expected to challenge some of the cryptographic methods used for authentication and key exchange.
This has raised concerns around “harvest now, decrypt later” attacks, where encrypted data is collected today with the expectation that future quantum capabilities could potentially decrypt it later.
For organisations storing sensitive intellectual property, research data or AI training datasets, security decisions made today could have implications well beyond the immediate threat landscape.
Preparing for that future cannot be left until quantum computers become operational. Instead, security leaders and teams need to consider the transition to post-quantum security now, particularly where storage devices may remain in service for many years.
Security must extend into hardware
Data security is often viewed through the lens of data encryption, and with good reason. Self-encrypting drives (SEDs) provide always-on, hardware-based AES-256 encryption that helps protect data at rest without impacting performance.
But encryption is only one part of the storage security equation.
Storage devices themselves must also be trusted. Firmware, authentication mechanisms, provisioning processes and diagnostic tools all play a role in ensuring a drive operates securely throughout its lifecycle.
If attackers compromise a device’s firmware or trust architecture, broader security controls can be undermined regardless of how data is encrypted elsewhere in the system. This makes storage security a critical component of overall cyber resilience.
Building post-quantum resilience into storage
To address these emerging attack vectors, the storage industry is actively embedding post-quantum cryptography (PQC) into hardware architecture of enterprise hard drives. Rather than focusing solely on protecting data, the objective is to protect the trust architecture that underpins the drive itself.
PQC technologies are being incorporated into areas such as secure key establishment, firmware authentication, secure provisioning, and trusted diagnostics. These capabilities are designed in alignment with established NIST post-quantum standards and are implemented using hybrid approaches that combine classical cryptography with quantum-resistant algorithms.
In practical terms, this means that the mechanisms responsible for establishing trust, validating firmware integrity and protecting administrative functions can remain resilient against both conventional and future quantum-enabled attacks. With the operational service life of HDDs often spanning 5 years (or more), implementing PQC today helps protect against quantum-based threats that may not materialise for several years, but that we know are coming.
Importantly, HDDs have long incorporated security controls to defend against today’s threats. PQC does not replace these protections; it enhances them by adding an additional layer of resilience against emerging attack vectors.
Trust as a non-negotiable
For many years, storage innovation was primarily defined by increases in capacity. Today, the expectations placed on storage infrastructure are much broader.
Organisations seek storage platforms that can scale with AI-driven data growth, deliver reliable performance, preserve integrity over long retention periods and withstand an increasingly sophisticated threat environment.
Post-quantum cryptography (PQC) represents an important step in that evolution. By extending protection beyond data encryption and into the trust mechanisms that underpin storage devices themselves, PQC-enabled HDDs help organisations prepare for the security challenges of tomorrow while protecting the data they manage today.
As AI increases the strategic value of enterprise data, security can no longer be a short-term, reactive consideration. Trust needs to be engineered into the infrastructure itself, from data centres right through to the storage device, and designed to withstand not only today’s threats, but the security challenges of the quantum era.
