The RAIHR Framework
Seven dimensions defining what responsible AI governance in HR requires. Each dimension is a distinct area of judgment — a set of questions to ask, risks to recognize, and actions to take when AI is used in employment decisions.
The framework is not a checklist. It is a structured way of thinking about AI in HR that covers the full scope of where things go wrong — from biased screening tools to covert employee monitoring, from inadequate vendor contracts to organizations that have lost the human capability to govern the tools they depend on.
Fairness
Identify and challenge AI systems that produce inequitable outcomes across demographic groups in hiring, performance, and development.
Read more →Transparency
Ensure that AI-assisted decisions can be meaningfully explained to the candidates and employees they affect — and to the HR professionals who make them.
Read more →Privacy
Govern how candidate and employee data is collected, used, retained, and shared by AI vendors — and ensure individuals' rights over their own data are honored.
Read more →Security
Protect the sensitive personal data that HR AI systems process, and hold vendors accountable for the security obligations they accept.
Read more →Human Oversight
Maintain genuine human judgment in AI-assisted employment decisions — not nominal human presence, but real independent assessment with authority to override.
Read more →Accountability
Ensure that every AI-assisted employment decision has a named human owner, a documented audit trail, and a genuine mechanism for challenge and redress.
Read more →Sustainability
Manage the long-term risks of AI adoption: capability erosion, vendor dependency, model drift, and governance standards that fall behind evolving practice.
Read more →The framework is the foundation. The certification is the assessment.
RAIHR Certified Practitioner tests judgment across all seven dimensions through scenario-based examination.