About this Event
AI initiatives rarely fail at the model. They often fail because the data underneath isn't ready.
Before an organisation can integrate AI effectively, it needs a clear understanding of its data: what exists, where it comes from, who can access it, how reliable it is, and whether it is suitable for the workflow being considered.
Data Readiness for AI Integration is a one-day working session for operations, data, and IT leads who are responsible for building the data foundations needed for AI.
Rather than working on a broad, multi-year data clean-up, you'll focus on one nominated workflow or dataset context and build a practical foundation around it. You will work with descriptions, structures, and fictional exercise datasets — not production data.
What You'll Work On
- Trace the Decision Back to the Data: Start with a business decision and identify the datasets and information it depends on.
- Build Data Inventory and Lineage: Map what data you have, where it comes from, and how it flows through the workflow.
- Test Data Quality, Bias and Representativeness: Work through structured tests and identify how similar checks could be applied to your own data.
- Review Access, Retention and Security: Develop an access-control approach based on how information is actually used, rather than simply following the organisational chart.
- Define the Minimum Viable Data Foundation: Identify the smallest practical data foundation needed to support one AI workflow.
- Build a Two-Week Remediation Plan: Turn your findings into a focused plan with actions, ownership, and clear next steps.
What You'll Leave With
By the end of the session, you'll have practical working artefacts including:
- A data inventory and lineage diagram
- A data quality and bias test report
- An access-control matrix
- A two-week remediation sprint plan
Who Is This For?
This working session is designed for:
- Operations leads
- Data and analytics professionals
- IT leads
- Professionals responsible for organisational data foundations
- Teams preparing data for AI integration
Bring knowledge of a nominated workflow or dataset context to work on during the session. Do not bring production data.
Prerequisites
FND-101 is recommended.
This session is designed as professional development. It is not a data audit, security assessment, or assessment of your production systems.
Your Facilitator: Dr Eunice Sari
Dr Eunice Sari is a humanity-centred AI and inclusive design leader with 25+ years of experience across AI integration, digital transformation, data-informed decision-making, and organisational capability. As Co-Founder of the Western Australian AI Hub, she helps organisations build practical foundations for responsible and effective AI integration.
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Refund, Cancellation and Transfer Policy
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Event venue & nearby stays
The Platform, 256 Adelaide Terrace, Perth, Australia
Concerts, fests, parties, meetups — all the happenings, one place.