As organisations accelerate their GenAI ambitions, a critical challenge is becoming clear: AI is only as powerful as the data behind it. Yet for most organisations, that data is neither fully visible nor fully governed.

Industry estimates show that 70–90% of enterprise data is unstructured, housed in emails, documents, call transcripts, PDFs, collaboration platforms and other scattered sources. Despite this, the majority of information management investments to date have focused on structured systems like databases and ERP platforms.

For organisations aiming to operationalise generative AI applications and other enterprise AI tools, traditional enterprise information management (EIM) systems are simply not equipped to manage the complexity of today’s information landscape.

Information management solutions must evolve to meet the scale, complexity and governance demands of the AI era.

Why unstructured data is the real AI frontier

Structured data represents only a small fraction of an enterprise’s information landscape. The greater value, and the greater risk, reside within unstructured and semi-structured content. However, only 18% of organisations effectively leverage unstructured data.

Without effective unstructured data management, GenAI models operate with an incomplete or distorted view of the enterprise. Critical insights are missed, bias is inadvertently introduced, and the risk of non-compliance escalates.

To drive meaningful, trustworthy AI outcomes, enterprises must invest in information management solutions that can:

  • Discover and classify unstructured data at scale
  • Enrich content with meaningful metadata
  • Apply governance, security and compliance policies directly at the source
  • Enable in-place management across hybrid, cloud and on-prem environments

Only with this solid data foundation can organisations confidently move from analysing unstructured data to transforming it into strategic insight.

Where generic data preparation tools fall short

While many enterprise AI tools and data preparation platforms offer basic ingestion and transformation capabilities, few address the complex, enterprise-grade requirements essential for safe, scalable AI adoption.

Generic platforms typically:

  • Focus primarily on structured and semi-structured datasets, overlooking the vast volumes of unstructured enterprise content. As a result, critical information stored in emails, documents, collaboration platforms and other unstructured formats remains undiscovered. This creates incomplete datasets that undermine the quality and reliability of AI-driven insights.
  • Lack automated, policy-based governance and lifecycle enforcement for sensitive or high-risk information. Without automated governance controls, organisations are forced to rely on manual processes that increase compliance risk, operational inefficiency and human error.
  • Require costly, disruptive “lift and shift” migrations, increasing operational and security risks. Moving sensitive data into new environments exposes enterprises to unnecessary migration risks, operational downtime and additional security vulnerabilities.
  • Fail to maintain chain of custody, auditability and defensible compliance. Enterprises operating in regulated industries risk falling short of legal and evidentiary requirements when full audit trails and content provenance are not preserved.
  • Overlook evolving regulatory requirements, such as GDPR, HIPAA, APRA CPS 234, and emerging AI governance standards. Generic tools are not built to keep pace with shifting compliance landscapes, leaving enterprises vulnerable to non-compliance, fines and reputational damage.

For enterprises operating in regulated, complex environments, these shortcomings create operational, legal and reputational risks.

Why EncompaaS is purpose-built for enterprise AI

As AI adoption accelerates, enterprises are grappling with increasingly complex information environments.

The EncompaaS platform addresses these modern challenges by using AI to discover, understand, organise and de-risk enterprise data without lifting, shifting or rebuilding existing infrastructure.

It enables enterprises to:

  • Discover and classify information across all repositories, ensuring complete visibility of both structured and unstructured data
  • Enrich content with intelligent metadata, improving searchability, compliance and context for AI-driven initiatives
  • Apply policy-based governance in place, supporting compliance requirements such as GDPR, HIPAA and APRA CPS 234 without disrupting business operations
  • Normalise and organise data into a high-quality foundation, making unstructured information AI-ready and analytics-friendly
  • Protect sensitive content through encryption, access controls and auditability, ensuring trust, transparency and security across the data lifecycle

By creating a normalised, governed, high-quality data foundation, EncompaaS helps enterprises overcome the data challenges that limit AI effectiveness, supporting trustworthy, scalable AI deployment across the organisation.

Choosing the right information management solution is one of the most important decisions organisations will make as they prepare for an AI-driven future.

Download our solution comparison guide to see why EncompaaS delivers the compliance, scalability and AI readiness that today’s enterprises require.

You can also contact us to learn how EncompaaS can help unlock the full potential of your information and power your GenAI initiatives responsibly.