Evaluating AI-Assisted Psychoeducational Report Writing: A Framework for Utility, Equity, and Defensibility

Abstract

Psychoeducational reports translate assessment data into decisions about eligibility, services, and instruction, yet research documents persistent problems with their clarity, data-linkage, and usefulness to families and educators (Hale & Brown-Chidsey, 2023; Hite, 2026). Generative artificial intelligence (AI) has entered report writing, and early studies describe its adoption and effects on report quality (Farmer, Lockwood, Floyd, & Sisco, 2025; Lockwood, Farmer et al., 2025). School psychology lacks a structured way to determine when AI assistance is useful, equitable, and defensible and when it introduces risk. This conceptual article proposes a framework organized around three domains: utility, equity, and legal and ethical defensibility. Utility concerns whether reports help intended users understand and act on findings. Equity concerns whether reports improve access while avoiding bias, deficit framing, and unsupported cultural assumptions. Legal and ethical defensibility concerns whether reports preserve practitioner judgment, protect student information, and remain consistent with special education law and professional ethics. The framework considers both where AI is used in a report and the specific task it performs. It supports distinguishing lower-risk from higher-risk uses and informs a proposed risk-stratification system and decision pathway. Implications for practice, training, governance, and research across school psychology are discussed.