Artificial intelligence and advanced analytics are transforming the way organisations operate. From automating routine tasks to uncovering new insights, the opportunities are huge. But here’s the catch: AI is only as good as the data that feeds it.
That’s why I’ve developed the Data Readiness Checklist for Future Technologies – a simple, practical tool to help organisations reflect on how prepared their data really is.
Why I created the checklist
Over the past few years, I’ve seen many teams in higher education and beyond get excited about AI, dashboards, and predictive models — only to hit a wall when the underlying data wasn’t ready. Issues like inconsistent definitions, gaps in security, or limited skills can quickly derail even the most promising projects.
The checklist brings these issues into focus. It gives leaders, data professionals, and teams a common language to talk about data maturity, without needing technical jargon.
What the checklist covers
The tool highlights four key areas that underpin future success with AI and data-driven technologies:
- Data Quality – ensuring accuracy, consistency, and trust in your information.
- Data Security & Compliance – safeguarding sensitive data and meeting obligations like GDPR.
- Data Skills & Culture – building the knowledge and behaviours that enable innovation.
- Data Governance & Strategy – creating the structures and alignment needed for sustainable success.
Each area is broken down into a Bronze–Silver–Gold maturity model, so you can quickly see where your organisation sits today and what steps will help you progress.
Who it’s for
This resource is designed to be sector-agnostic, but it draws on lessons from higher education and other industries. It’s especially useful for:
- Leaders planning system or digital transformation projects.
- Data professionals reviewing policies, practices, or compliance.
- Teams who want a simple way to start conversations about AI readiness.
How to use it
You don’t need to complete it all in one go. Use the checklist to:
- Spark team discussions.
- Highlight areas where quick wins are possible.
- Identify longer-term priorities for investment.
Reviewing it annually – or whenever a major data or technology project begins – can help keep your organisation future-ready.
Get the checklist
The Data Readiness Checklist is free to download and share. It’s a starting point for reflection, and I hope it helps you and your teams take confident steps toward using AI and advanced analytics effectively.