Watch the second session of our four-part webinar series on Data & AI Governance at Pace, organised by Hitachi Solutions, Trusenta, and DataWyse.
Picture the board meeting. The chair turns to your data leader and asks a simple question: “Show me the governance on the data feeding our AI model, the classification, lineage, and quality record.”
In most organisations, that question can’t be answered. It’s not due to poor decisions, but because the governance layer behind the AI was never built.
Between 73% and 80% of enterprise data has never been classified, catalogued, or assigned an owner, and much of it is already feeding AI systems. AI doesn’t fix this; it amplifies the problem by producing automated outputs from unverified data.
This session is the practical answer: helping you find your dark data, build lineage as a new audit trail, govern quality as a measurable discipline, and meet the regulatory obligations now taking shape.
Key Takeaways:
- Where your dark data is hiding, and how to prioritise what to classify first
- Why lineage has become the audit trail boards and regulators ask for (demonstrated step by step in Microsoft Purview)
- How to govern data quality as a measurable discipline, not a technical afterthought
This session is designed for leaders responsible for:
- Driving AI and data strategy on Microsoft platforms
CIOs/CDOs leading Copilot, Dynamics 365, and enterprise AI adoption - Ensuring secure, compliant and governed AI data usage
CISOs and privacy leaders managing access, risk and compliance - Building trusted data foundations and analytics
Data leaders improving quality, stewardship, and using Purview & Fabric - Scaling AI adoption and business transformation
Transformation leaders enabling AI use and confidence
Three experts. One integrated outcome.
- Hitachi Solutions – Microsoft transformation and implementation
- Trusenta – Governance and operating model design
- DataWyse – Data products, readiness, and platform execution
Watch the session on-demand and start building the data foundation your AI initiatives require to scale with confidence.
For enquiries, drop us a message at [email protected].
What’s Coming Next?
Session 1 and 2 set the foundation and initial execution, the next step involves governing data flows when embedded AI switches on.
Session 3, The Data Inside the Machine, addresses the technical and architectural shift required as AI agents become the dominant users of your data—showing how to properly govern multi-model and multi-agent environments.
Step into what comes next. Register for Session 3 here