This is part 7 in a 12-part series on How Primary and Secondary Schools Use AI. The goal is to provide educators with a roadmap for planning AI usage in their schools.
Special education is one of the most demanding and high-stakes areas in education. Teachers juggle instruction, accommodations, IEP meetings, documentation, collaboration, and communication with families while supporting students with diverse learning needs. The strain is real, and research shows it contributes to high burnout and turnover.
AI is beginning to ease parts of that load. When used responsibly, it can help draft IEP elements, adapt materials, translate communication, and make learning more accessible. It gives teachers more time with students. It gives students more ways to participate in meaningful learning.
Let’s explore how districts are using AI to strengthen special education systems, reduce workload, and expand inclusive learning opportunities.
A – What It Is
AI for special education and accessibility refers to tools that help educators create accommodations, modifications, differentiated materials, and accessible versions of curriculum quickly and effectively. These tools also support teachers with documentation and compliance tasks that previously took hours. AI systems support special education in four key ways:
1. IEP Drafting & Documentation Support
AI can assist teachers in generating draft goal statements, progress note summaries, and plain-language explanations for families. Early studies with novice special educators suggest that using AI to draft IEP goals can lead to higher-quality, more comprehensive goals and make the drafting process more efficient, while teachers still review and revise every word.
2. Accessible Versions of Content
AI tools can quickly level text, simplify dense language, add vocabulary supports, translate instructions, convert text into audio, or generate visual scaffolds. These features are especially helpful for students with reading disabilities, language processing needs, ADHD, autism, and multilingual learners. Research on AI-based adaptive reading and learning supports shows improved comprehension and participation, along with reduced teacher preparation time.
3. Supports for Inclusive Classroom Instruction
In inclusive settings, AI helps general and special educators create differentiated materials. AI tools automate creation of modified assignments, scaffolded writing frames, step-by-step math explanations, and multimodal task breakdowns. Early adopter districts report that these supports reduce the need for separate materials and make inclusion more seamless, with students accessing the same lesson at varying levels of complexity.
4. Behavior, Social-Emotional & Family Communication Supports
AI can assist teachers in organizing behavior data, drafting baseline summaries, and generating language for Functional Behavior Assessments or Behavior Intervention Plans. It can also help translate or simplify IEP language so families better understand services and progress. These tools support communication and planning, but teachers make all interpretive decisions to ensure accuracy and appropriateness.
B – Why It’s Important
Special educators carry extraordinary responsibility. The stakes are high and the workload is burdensome. AI has emerged as one of the most meaningful supports they have had.
1. Reduce Paperwork and Administrative Overload
Special educators spend hours each week on documentation. AI can help special educators draft emails, progress notes, IEP components, and adapted materials, reducing the time they spend on repetitive writing tasks. When AI handles the first draft, teachers can devote more of their energy to interpretation, instruction, and collaboration.
2. Faster and More Flexible Accommodations
Creating multiple versions of assignments or readings can take hours. AI allows teachers to produce leveled texts, visual supports, guided notes, and translations instantly. This helps students access grade-level content without waiting for materials to be manually adapted each time.
3. Stronger Inclusive Practices
Inclusion works best when general education teachers have tools to adjust instruction on their own, without relying on a specialist for every accommodation. Early adopter districts show AI helping teachers create differentiated versions of the same task, making it easier for students with disabilities to participate in whole-class lessons.
4. Clearer Family Communication
Families often find IEPs and evaluations dense or overwhelming. AI can help draft clear, accessible explanations and translate communication into families’ home languages. This supports stronger partnerships while preserving teacher oversight and judgment.
5. Support Teacher Retention
Special education turnover is strongly linked to workload and working conditions. While AI cannot solve systemic issues on its own, .tools that meaningfully reduce documentation burdens and streamline tasks could play a key role in supporting retention.
C – How It’s Being Used
Case Study #1: El Segundo Unified School District (CA) – Using AI to Scale Differentiation and Special Education Supports
Focus: AI-assisted differentiation and accommodations
Heroes: Dr. Fong Yuzhou, general and special education teachers
What They Did
In El Segundo USD teachers used AI tools to level texts, generate sentence starters, support IEP drafting, and outline behavior plans. These uses were part of districtwide efforts to support differentiation in both general and special education classrooms.
How It Worked
Teachers uploaded core instructional materials and used AI to create scaffolded versions for diverse learners. The district emphasized clear guardrails: AI serves as a teacher assistant, and all instructional and legal decisions remain with educators.
What the Results Showed
Board documents indicated strong teacher adoption and noted that the tools made inclusion more feasible by scaling materials to individual student needs. Leaders highlighted improved access for students with disabilities in general education settings.
Case Study #2: Novice Special Educators – Improving IEP Goal Quality with AI-Assisted Drafting
Focus: Improving IEP goal quality and efficiency
Heroes: Novice SPED teachers participating in research trials
What They Did
In a research trial led by Salih Rakap at the University of North Carolina Greensboro, novice special-education teachers working with preschool children with autism were randomly assigned to use the AI tool (ChatGPT) or a control condition. Teachers in the AI group were instructed to use ChatGPT to draft IEP goals (including student strengths, needs, and measurable outcomes) before reviewing and revising them themselves. PubMed+2SAGE Journals+2
How It Worked
Participants used a validated instrument (the Revised IEP/IFSP Goals and Objectives Rating Instrument, R-GORI) to compare the quality of AI-supported versus traditional drafting. Teachers refined the AI drafts to align with local district expectations and individual student needs. SAGE Journals+1
What the Results Showed
Teachers in the AI-supported group produced higher-quality goals than those in the control group (in terms of clarity, measurability, and alignment) though the study authors note the sample was small and exploratory.
Case Study #3: Special Education Teachers – Reducing Documentation Workload Through AI-Generated Drafting
Focus: Streamlining non-teaching tasks
Heroes: Special education teachers and researchers
What They Did
The Journal of Special Education Technology documented examples of teachers using AI to draft collaboration emails, adapt texts for multiple reading levels, and create progress monitoring templates aligned to IEP goals.
How It Worked
Teachers entered key details such as student strengths, goal areas, or progress data. They used AI to generate first drafts. Then they reviewed and edited these drafts to ensure accuracy, compliance, and student-centered language.
What the Results Showed
Researchers found AI can reduce time spent on repetitive writing and documentation, which are major sources of workload stress. They argue that such tools could meaningfully support teacher well-being if integrated responsibly.
Case Study #4: CIDDL – Increasing Accessibility and Participation Through AI-Supported Classroom Tools
Focus: Real-time accessibility and inclusive instruction
Heroes: CIDDL researchers, assistive technology specialists, classroom teachers
What They Did
The Center for Innovation, Design, and Digital Learning (CIDDL) highlighted AI tools that provide captioning, text leveling, translation, vocabulary supports, and audio descriptions, along with AI systems that guide students through multi-step academic tasks.
How It Worked
Teachers used AI to adapt texts on demand, provide live transcription, support math problem solving, and break down complex directions. These features made it easier for students with disabilities to participate in everyday lessons.
What the Results Showed
CIDDL summarized a meta-analysis showing moderate positive effects of AI-based interventions on academic and social-emotional outcomes for students with disabilities. They conclude that AI can help shift accessibility from reactive accommodations to proactive design.
D – Pro Tips
1. Use AI as a drafting partner while keeping teachers in full control.
The IEP goal-writing studies demonstrated this clearly: novice special educators improved clarity and completeness when they let AI generate early drafts, but final decisions always came from the teacher.
2. Start with low-stakes before moving into high-stakes tasks.
In the documentation workload case study, teachers reported that AI was easiest to adopt when they began with routine drafting tasks, like emails, summaries, and leveled materials. Then they expanded into IEP-related writing as comfort grew.
3. Use AI to make inclusion more realistic in everyday instruction.
El Segundo USD showed how AI-generated leveled texts, scaffolded materials, and sentence starters allowed more students with disabilities to participate meaningfully in shared classroom activities.
4. Lean on universal accessibility features that support many learners at once.
CIDDL’s accessibility work highlighted how captioning, text simplification, and translation help students with disabilities, multilingual learners, and struggling readers simultaneously, reducing the need for multiple sets of materials.
5. Aim AI at the heaviest documentation pain points to maximize impact.
Special educators in the Journal of Special Education Technology case study found the biggest time savings when AI supported progress notes, collaboration messages, and adapted texts. These are the very tasks that typically consume much of educators’ planning time.
6. Put strong guardrails in place for privacy and responsible use.
Across studies and district examples, educators emphasized avoiding identifiable student data in public tools and relying on secure, district-approved systems when working with special education information.
7. Pair AI tools with ongoing professional learning and collaboration.
Both the IEP goal-writing research and CIDDL’s implementation examples showed stronger outcomes when teachers received coaching, shared effective prompts, and learned together how to use AI responsibly.
References
Billingsley, Bonnie, and Elizabeth Bettini. “Special Education Teacher Attrition and Retention: A Review of the Literature.”
https://journals.sagepub.com/doi/10.3102/0034654319862495
Citizen Portal. “District Shows Classroom Uses for Magic School AI, Highlights Supports for Special Education and Differentiation.”
https://citizenportal.ai/articles/6334452/California/District-shows-classroom-uses-for-Magic-School-AI-highlights-supports-for-special-education-and-differentiation
CIDDL (Center for Innovation, Design, and Digital Learning). “The Future of Accessible Classrooms: How AI Is Opening Doors in Special Education.”
https://ciddl.org/the-future-of-accessible-classrooms-how-ai-is-opening-doors-in-special-education/
CIDDL (Center for Innovation, Design, and Digital Learning). “Special Education Teachers’ Use of Generative AI.”
https://ciddl.org/special-education-teachers-use-of-generative-ai/
Goldman, Samantha R., Juli Taylor, Adam Carreon, and Sean J. Smith. “Using AI to Support Special Education Teacher Workload.” Journal of Special Education Technology.
https://eric.ed.gov/?id=EJ1434118
Marino, Matthew T. “Artificial Intelligence and Special Education: Potential and Considerations.” Journal of Special Education Technology.
https://eric.ed.gov/?id=EJ1457498
OECD. “Artificial Intelligence and the Future of Teaching and Learning for Students with Special Educational Needs.”
https://www.oecd.org/education/artificial-intelligence-and-special-educational-needs
Rakap, Salih. “Chatting with GPT: Enhancing Individualized Education Program Goal Development for Novice Special Education Teachers.”
https://journals.sagepub.com/doi/10.1177/01626434231211295
Rakap, Salih, and Serife Balikci. “Enhancing IEP Goal Development for Preschoolers with Autism: A Preliminary Study on ChatGPT Integration.”
https://pubmed.ncbi.nlm.nih.gov/38625490/
Zhang, Dongbo, et al. “Artificial Intelligence–Based Interventions for Students with Disabilities: A Systematic Review and Meta-Analysis.”
(Discussed in CIDDL’s summary “The Future of Accessible Classrooms: How AI Is Opening Doors in Special Education.”)
https://doi.org/10.1007/s40692-024-00387-9
