AI-Driven Systems in MTSS: Potential Opportunities and Challenges

Multi-tiered systems and support (MTSS) offers a framework for schools to provide equitable learning opportunities. However, implementing MTSS with fidelity can be challenging due to limited resources that many schools experience. As a result, more educators are turning to artificial intelligence (AI) tools as a solution to resource limitations. This article examines how AI tools can strengthen MTSS, specifically, improvement to inclusive practices, data analysis, intervention implementation, progress monitoring, personalized learning, student engagement, and teacher efficiency. The article also examines potential risks related to using AI tools within MTSS such as ethical considerations, date security, data quality, bias potential, financial limitations, and professional development needs. Additionally, practice implications are provided to guide school psychologists in leading responsible AI implementation within MTSS frameworks.

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Publication Details

Journal
Journal of Applied School Psychology
Published
2026-01-02
DOI
https://doi.org/10.1080/15377903.2026.2629399
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Driven Systems in MTSS: Potential Opportunities and Challenges

Hank Bohanon, Kaitlin Reichart, Adam B. Lockwood
Journal of Applied School Psychology
Intelligent Tutoring Systems and Adaptive Learning
article

AI-Driven Systems in MTSS: Potential Opportunities and Challenges

Hank Bohanon, Kaitlin Reichart, Adam B. Lockwood
article en

Abstract

Multi-tiered systems and support (MTSS) offers a framework for schools to provide equitable learning opportunities. However, implementing MTSS with fidelity can be challenging due to limited resources that many schools experience. As a result, more educators are turning to artificial intelligence (AI) tools as a solution to resource limitations. This article examines how AI tools can strengthen MTSS, specifically, improvement to inclusive practices, data analysis, intervention implementation, progress monitoring, personalized learning, student engagement, and teacher efficiency. The article also examines potential risks related to using AI tools within MTSS such as ethical considerations, date security, data quality, bias potential, financial limitations, and professional development needs. Additionally, practice implications are provided to guide school psychologists in leading responsible AI implementation within MTSS frameworks.

Journal of Applied School PsychologyVol. 42(1)
Loyola University Chicago (US), Lifespan (US)
Openalex Percentile: Top 37%
Intelligent Tutoring Systems and Adaptive Learning
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AI-Driven Systems in MTSS: Potential Opportunities and Challenges — Hank Bohanon, Kaitlin Reichart, et al. · Journal of Applied School Psychology (2026) | TGRS Research Map | TGRS