AI Readiness Isn’t a Tech Strategy. It’s a Trust Strategy
The AI conversation is heating up fast, and HR is suddenly at the center of it. But most teams are being asked to move quickly without a clear definition of what ‘readiness’ even means. The truth? Flashy dashboards and off-the-shelf tools won’t get you there. If your data isn’t trusted—by HR, by leadership, or by employees—it won’t drive action. And it definitely won’t drive strategy. In this session, we’ll talk about the role people analytics plays in making AI readiness real—not theoretical. We’ll share new insights from CHROs, show where trust in people data is breaking down, and walk through a practical framework to help you rebuild it. Whether you sit in PA, HRIT, or strategy, this is about putting explainable, defensible data at the center of how your org moves forward.
- A working definition of AI readiness for HR – why trust precedes tools.
- Where trust breaks in people data – lineage, quality, access, bias and security.
- A practical trust-building framework – explainable metrics, transparent logic, governance and audit trails.
- Fresh CHRO research – priority gaps and how PA/HRIT can respond.
- Operating cadence – stakeholder mapping, adoption measures and decision architecture.
- A sharper, simpler definition of what ‘AI readiness’ actually looks like in HR.
- Why trust—not tools—is the real unlock for faster decisions and better alignment.
- How explainable metrics and transparent logic build credibility with execs and end users.
- New research on what CHROs are struggling with—and how PA teams can help.
- 3 specific ways you can strengthen data trust and set HR up to lead this shift.
Why this is on the agenda
Boards want AI productivity, regulators demand governance, and employees expect fairness. Without trust in people data – lineage, quality, access and bias controls – HR cannot make explainable decisions or secure CHRO/CFO backing. AI readiness therefore hinges on credible metrics, transparent logic and auditability, not new tools.