RAG Grounding Checklist: What Must Be True Before You Trust an Answer

Why Read This Research

Retrieval-augmented generation (RAG) can improve AI answers by grounding them in institutional documents, but it does not make those answers safe to use by default. This infographic gives higher education leaders a practical nine-check governance standard for validating sources, citations, version control, access permissions, conflicts, and campus-specific risk before AI guidance is forwarded, reused, or operationalized. Use it to separate helpful self-service from cases that require human review.

Key Questions Answered

• How can higher education teams confirm whether a RAG-generated answer is grounded enough to use?
• What governance checks should apply before staff forward, reuse, or repeat AI-generated guidance?
• When is RAG appropriate for self-service, and when is human review required?
• How can institutions reduce risk from stale documents, unsupported citations, conflicting policies, or unauthorized data access?

Features

• Software Category in Focus: AI/ML Platforms
• Future Campus Impacts: Retain, Operations, Governance, Risk, Innovate
• Author: Alpha Hamadou Ibrahim, PhD, Vice President of Data, Analytics, and AI, Tambellini Group
• Research Availability: June 2026