Data Security Technologies: Encryption and Classification Gaps in Mature Platforms and Modernizing Your Tech Stack

With multiple factors impacting data security strategies and platforms, many organizations face gaps. Those are often prominent in the areas of encryption and classification. When these exist, challenges arise related to compliance, risk, and workflow disruption. A new era of data security technologies seeks to close these.

Mature systems often haven’t delivered much innovation. If you feel stuck and exposed because of this, it’s a great time to modernize your tech stack.

Traditional integrated data security platforms have classification and encryption features. However, they may not be as comprehensive or consistent as you need. Let’s investigate these shortcomings.

Classification Disparity

Classification describes labeling data based on its sensitivity. It’s an essential function for any security strategy. Once you categorize information, you can then deploy the necessary safeguards to meet regulations. Many platforms enable this to be automatic and policy-driven for consistent application.

Mature platforms often miss some of this vital functionality. Obstacles in the Data Storage Management Services category, according to the Gartner® Hype Cycle™ for Data Security Technologies, include “business agreement on data classification, categorization and related retention policies is critical for successful deployments, but is often difficult to obtain.”

That can be a significant challenge if there’s no consensus. Some systems may also limit classification definitions.

Another obstacle mentioned for Digital Communications Governance and Archiving in the Gartner Hype Cycle is “executive sponsorship and stakeholder buy-in to data classification and related retention policies may be difficult to obtain.”

It’s difficult to apply classification universally without this kind of support. It may occur because those in charge don’t realize its overall value.

If these gaps sound familiar, you should reconsider how you’re using classification, why it may be ineffective, and how to find agreement across your organization.

Ideally, data classification solutions should support data security, privacy, and governance. The Gartner Hype Report named PKWARE as a Sample Vendor for “Format-Preserving Encryption” and “Data Classification.”

Encryption That’s Too Complex

Not all data encryption platforms are the same. Traditional options impact productivity, depend on certificates, and have high overhead. Modern encryption is certificate-free and persistent.

Persistent encryption means it stays with the data, whether at rest or in transit. It’s a complete lifecycle solution, since it doesn’t require certificates or slow down operations. Finally, centralized policies dictate it, so there’s no user dependence.

Format-Preserving Encryption

Another aspect of encryption and why it doesn’t fit all needs is whether it preserves the format. This means the encryption stays with the data even when accessed via applications. The Gartner Hype Cycle calls this important because format-preserving encryption (FPE) can “protect data at the point of ingestion, storage in a database, or access through data pipelines.”

The Gartner Hype Cycle recognizes PKWARE in this category.

Classification and encryption are pillars of integrated data security programs. Others within this same ecosystem include controls related to AI, breach response, privacy, and multi-cloud platforms with multi-functional data security.

Data Security Controls for AI

AI has become a pillar for every industry, supporting data analysis and actionable insights. However, AI models introduce risk in terms of data privacy. The best approach to take to harness the power of AI is through de-identification that doesn’t lose context.

Deterministic data masking provides this capability. Masking copies of production data for use in AI models enables predictive analytics. The key is replicating it in the same format and appearance as the actual data.

You can also use automated discovery to find sensitive elements that shouldn’t be included in AI models. You can then apply protection and governance rules to restrict data usage in these environments.

Breach Response Controls

Data breaches are an everyday occurrence. While you cannot eliminate all risk, you can reduce your attack surface and mitigate the fallout.

Proactive data breach resiliency can pave this path. It involves:

• Visibility of sensitive elements across your enterprise
• Preemptive protection so that if there’s a breach, data remains inaccessible
• Policy-driven protections for PII, PCI, and PHI

Moving beyond access control and perimeter security is a hallmark of the new age of breach resilience. With the right platform, you have a full inventory of your most valuable assets, and they retain protection.

Data Privacy Controls

The Gartner Hype Cycle noted that “technical innovations help balance data confidentiality with data utility, providing encryption and privacy controls for sensitive data.” Privacy-enhanced technologies and cryptographic controls support this balance, which are most commonly encryption, redaction, or masking.

With any of these remediation activities, you can use and share data securely and compliantly. Modernizing how you do this avoids broken workflows. These remediations utilize a central policy for application, which eliminates manual work.

Fiserv exemplifies this by encrypting over 1 million files a day without interrupting workflows. Secure data exchange occurs continuously, keeping the company compliant and workers able to do their jobs.

Multi-Cloud Platform Controls

The Gartner Hype Cycle also highlights multi-cloud platforms with multi-functional data security features. Organizations have begun to use cloud services from two or more public cloud providers. It offers flexibility and a way to optimize performance.

With its pros, there’s also new risk if you don’t have consistent security controls across environments. Regardless of which cloud environment contains sensitive information, you can define policies centrally for discovery and remediation. Doing so within one data security platform offers simplicity and consistency.

The Gartner Hype Cycle for Data Security Technologies offers an expansive overview of the industry. It also defines the serious gaps that remain in mature systems. Modern data protection platforms can close these, providing a way to future-proof systems. You don’t have to compromise compliance or security.

We believe this Gartner recognition of PK Protect as a Sample Vendor demonstrates our commitment to delivering what organizations need today and tomorrow.

Read the entire report for more insights today.

Gartner, Hype Cycle for Data Security Technologies, Andrew Bales, 10 July 2025 

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