Free eBook for IBM i Leaders
Your IBM i Data Is Ready for AI. Is Your Data Estate?
Your IBM i already holds years of operational and transactional data. This eBook shows you how to make it connected, trusted, and ready for analytics and AI.
Get the IBM i Leader’s Roadmap to
AI-Ready Analytics
What You'll Get From This Guide
A clearer view of your data
See where your IBM i data is easy to access, where it gets stuck, and where gaps still exist.
A roadmap for getting AI-ready
Understand the steps involved in making IBM i data easier to trust, access, and use for reporting, analytics, and AI.
A readiness scorecard
Spot gaps and set priorities across data access, data trust, analytics capability, and AI readiness.
What's Inside
This guide is built for IT, Finance, Operations, and business leaders who know they could be getting more from their IBM i data but need a clearer picture of where they stand first.
Common Barriers to Data Access & Trust
Where IBM i data gets stuck, why reporting stays manual, and what makes the numbers harder to trust.
The Assess, Connect, and Transform Framework
Follow a three-step model for moving from siloed data to a more connected foundation for analytics and AI.
Examples Across Key Roles
See how IT, Finance, Operations, and business leaders can use better access to IBM i data to support faster decision-making and action.
A Scored Self-Assessment
Measure the current state of your data environment and identify the most important areas to address first.
Frequently asked questions
Do I need to replace my IBM i to use this roadmap?
No. The roadmap builds on the system you already run. Your IBM i stays in place while your data becomes more accessible and ready for modern analytics.
Is this guide technical or strategic?
Both, with the right balance. It explains the path in clear business terms while giving IT the detail needed to understand how each step works.
How long does the readiness assessment take
A few minutes. The scorecard has sixteen short statements across four areas, and you score each one honestly to see exactly where your gaps are.
Who should read this?
IT, Finance, and Operations leaders running IBM i who want more from the data they already have, plus anyone exploring analytics or AI as a next step.