Generative AI is accelerating innovation across industries but it’s also exposing a serious governance gap. As enterprises race to deploy AI tools, many are discovering their existing data governance policies weren’t built to support the scale, speed, or complexity that AI demands.

For organisations operating in regulated or risk-sensitive environments, these are immediate barriers to scale. Without strong controls over how data is sourced, structured, used and retained, AI initiatives become difficult to explain, defend or operationalise.

According to our recent report, 58% of business leaders cite AI ethics, governance and trust as one of their top challenges when implementing GenAI. To deploy AI responsibly, organisations must treat governance not as a bolt-on, but as a core capability.

What best-practice AI governance looks like

Best-practice enterprise AI governance is built on three foundational pillars:

  1. Transparency and explainability – Enterprises must be able to explain not just what an AI model decides, but how it arrived at that decision. That means full visibility into source data, enrichment steps and how information was used in inference.
  2. Traceability and data lineage – AI governance policies and procedures must include version control, usage logs and lineage tracking to maintain a record of how data evolves and how models interact with it over time.
  3. Regulatory compliance and privacy – With laws like GDPR, HIPAA and APRA CPS 234 in play, organisations must maintain control over sensitive personal information and ensure it’s governed appropriately across AI pipelines.

To deploy AI responsibly, organisations must stop treating governance as a bolt-on and as a core capability.

EncompaaS’ role in the AI governance lifecycle

This is where EncompaaS delivers its greatest impact.

EncompaaS is an AI-powered information management platform that discovers, classifies and governs enterprise data in-place without replatforming or disruption. It prepares a trusted, normalised data foundation for responsible AI, and applies policy-based governance at scale.

Here’s how EncompaaS supports best-practice AI governance across the lifecycle:

  • Curating governed datasets for training and inference

EncompaaS identifies, classifies and enriches relevant data across repositories including legacy systems, file shares and cloud platforms. It transforms unstructured and semi-structured content into structured, context-rich, AI-ready inputs.

  • Maintaining data lineage and auditability

Every change, rule and interaction is tracked, creating an immutable audit trail. EncompaaS ensures that the data behind AI decisions is explainable, compliant and defensible, supporting everything from Data Subject Access Requests (DSARs) to model audits.

  • Automating governance policies

EncompaaS enforces governance rules including classification, retention, access, and defensible deletion in real time, across the entire enterprise. It applies these policies where the data lives, supporting scalable AI adoption without compromising compliance.

Together, these capabilities turn fragmented, high-risk content into a governed data supply chain that supports trusted, traceable and explainable AI outcomes.

Real-world applications in regulated industries

The need for explainable, responsible AI is particularly urgent in sectors like:

  • Financial services – Use GenAI to surface risk patterns or summarise disclosures while maintaining retention schedules and global data privacy regulations.

  • Government – Automate citizen service queries and internal knowledge search while preserving traceability, classification and compliance with public record standards.

  • Healthcare – Prepare patient data for AI triage tools or GenAI-based knowledge assistants while enforcing PHI protection and HIPAA-aligned lifecycle controls.

In each case, EncompaaS provides the governance infrastructure needed to de-risk AI deployments and build trust with regulators, staff and stakeholders.

Enabling responsible AI at scale

The next wave of AI success stories won’t come from the boldest experiments. They’ll come from the organisations that laid the right foundation, grounded in clear data governance policies, explainable workflows, and trustworthy content.

EncompaaS transforms disparate enterprise content into a high-quality data foundation, ready for AI. By embedding governance into every stage of the AI lifecycle, it helps organisations scale with confidence without compromising trust, compliance or control.

Contact us to see how EncompaaS can help you implement best-practice AI governance and de-risk GenAI across your enterprise.