2026 Guide: How to Use AI for IEP & 504 Accommodations
TL;DR
AI tools can help special education teachers draft accommodations for IEPs and 504 plans significantly faster, but every output needs human review and every input needs to be scrubbed of student identifiers. This glossary defines the key terms you’ll encounter when using AI for accommodation work, from legal frameworks like IDEA and FERPA to practical concepts like prompt libraries and anonymization. Think of AI as getting you 70-80% of the way there. You finalize the rest.
More than half of special education teachers are now using AI to help with IEP or 504 plan work. According to a 2025 CDT survey, 57% of SPED teachers used AI for IEPs or 504 plans during the 2024-25 school year, up from 39% the year before. That’s a massive shift in a single year.
But the terminology load is brutal. Between the legal acronyms (IDEA, FERPA, FAPE, LRE), the plan-specific jargon (PLAAFP, SDI, SMART goals), and the AI vocabulary (LLMs, system prompts, anonymization), teachers trying to figure out how to use AI to create accommodations for IEPs and 504 plans can feel like they need a translator before they even start.
This glossary is that translator. Every term is defined plainly, and each definition connects to how AI fits into the accommodation process. Bookmark it, share it with your team, and come back whenever you need a quick reference.
If you’re looking for tools to reduce paperwork for special education, the right starting point is understanding what these terms actually mean.
Core Plans and Documents
These are the documents at the center of the accommodation process. When educators use AI to create accommodations for IEPs and 504 plans, these are the artifacts AI helps draft.
IEP (Individualized Education Program)
A legally binding document developed to ensure a child with an identified disability receives specialized instruction and related services. IEPs are governed by the Individuals with Disabilities Education Act (IDEA) and must be reviewed at least annually by a team that includes the student’s parents, teachers, and a school representative.
Why it matters when using AI: AI can draft sections of an IEP (goals, accommodations, present levels), but IDEA requires each IEP to be unique and tailored to the individual student’s disabilities, goals, and process for achieving them. An AI draft that isn’t significantly reviewed and edited by a teacher likely won’t meet these requirements. The IEP is a legal document, not a template.
504 Plan
A plan developed under Section 504 of the Rehabilitation Act to ensure a student with a disability receives accommodations that provide equal access to the learning environment. Unlike IEPs, 504 plans do not require specially designed instruction. They are shorter, less formally structured, and cover a broader definition of disability.
Why it matters when using AI: Because 504 plans are simpler documents, AI tools can suggest accommodations more efficiently here. But “simpler” doesn’t mean “less important.” The accommodations still need to match the student’s actual needs, not just a disability label.
The IEP vs. 504 Distinction
This is the single most common point of confusion for teachers learning how to use AI to create accommodations for IEPs and 504 plans. Both plans provide accommodations. But only an IEP provides specially designed instruction (SDI). IEPs are governed by IDEA and generally end at high school graduation, while 504 protections extend through college and beyond. A student who doesn’t qualify for an IEP under IDEA’s 13 disability categories may still qualify for a 504 plan under Section 504’s broader definition.
When prompting AI, this distinction matters. An AI tool won’t know which plan type you’re working with unless you tell it, and the accommodations appropriate for each differ.
PLAAFP (Present Levels of Academic Achievement and Functional Performance)
The PLAAFP is the foundation of an IEP. It summarizes a student’s current skills, strengths, areas of need, and how their disability affects their educational performance. Everything else in the IEP, from goals to accommodations, flows from this section.
Why it matters when using AI: AI can help draft PLAAFP narratives when you feed it anonymized assessment data and classroom observations. A practitioner writing for NGLC described being able to “upload a document to get a series of suggestions in minutes” that could then be edited quickly. The key word is “edited.” The AI doesn’t know your student. You do.
SMART Goals
IEP goals should be Specific, Measurable, Attainable, Relevant, and Time-bound. Data collection is required to track progress toward each goal. Writing SMART goals that are both legally defensible and practically useful is one of the most time-consuming parts of IEP development.
Why it matters when using AI: Goal writing is one of the most common uses of AI in IEP work. In a study cited by EdWeek, experienced special educators found no statistical difference in quality between goals written by teachers and goals written with ChatGPT’s help. A separate 2024 University of North Carolina study found that teachers trained on how to use AI actually produced higher-rated goals than a control group. For more on writing effective goals, see this guide on writing measurable IEP goals.
Accommodations vs. Modifications
Getting this distinction right is critical. It affects everything from classroom practice to diploma eligibility.
Accommodation
An accommodation changes how a student accesses content or demonstrates learning, without changing the content itself or the performance expectations. The student is still working toward the same standards as their classmates, just through a different path. Examples include extended time on tests, preferential seating, or text-to-speech software.
Accommodations are typically grouped into four categories:
- Presentation: How information is delivered to the student (e.g., large print, audio recordings)
- Response: How the student demonstrates knowledge (e.g., oral responses instead of written, use of a calculator)
- Setting: Where the student learns or is assessed (e.g., small group testing, separate room)
- Timing and scheduling: When or for how long the student works (e.g., extended time, frequent breaks)
Modification
A modification changes what a student is expected to learn or the level at which they’re assessed. Modifications are typically reserved for students working significantly below grade level. Examples include simplified reading passages or reduced numbers of test questions.
The critical difference: Accommodations may appear in both IEPs and 504 plans. Modifications are generally only included in IEPs. In many states, extensive use of modifications can affect diploma eligibility, so the stakes are high. When using AI to suggest supports, always verify whether the tool is recommending an accommodation or a modification, because AI doesn’t always label them correctly.
If you need to create differentiated worksheets that implement specific accommodations, that’s the step that comes after the IEP meeting, when you’re building the actual materials.
SDI (Specially Designed Instruction)
Instruction that has been adapted in content, methodology, or delivery to address a student’s unique needs as identified in their IEP. SDI is the defining feature that separates an IEP from a 504 plan. Only IEPs include SDI.
Why it matters when using AI: When AI suggests “accommodations,” make sure it isn’t actually suggesting SDI. The two require different levels of planning, documentation, and expertise.
Supplementary Aids and Services
Under IDEA, these are “aids, services, and other supports that are provided in regular education classes to enable children with disabilities to be educated with nondisabled children to the maximum extent appropriate.” This can include everything from adapted materials to paraprofessional support.
Why it matters when using AI: AI can help brainstorm supplementary aids based on a student’s needs profile, but the IEP team decides what’s appropriate, not the algorithm.
Legal and Compliance Terms
This is where anxiety lives. Teachers know that IEPs are legal documents and that student data is protected, but the specifics can feel overwhelming. When learning how to use AI to create accommodations for IEPs and 504 plans, understanding these terms is non-negotiable.
IDEA (Individuals with Disabilities Education Act)
The federal law that requires public schools to provide a Free Appropriate Public Education (FAPE) to eligible students with disabilities. IDEA defines 13 disability categories (including specific learning disabilities, autism, emotional disturbance, speech or language impairment, and others). Students who qualify under one of these categories may receive an IEP.
Why it matters when using AI: AI can suggest accommodations organized by disability category, which is a useful starting point. But relying on category-based suggestions alone risks generic output. The 13 categories are broad, and students within the same category can have vastly different needs.
Section 504 of the Rehabilitation Act
A federal civil-rights law that prohibits discrimination against people with disabilities in any program receiving federal funding, including public schools. Its definition of disability is broader than IDEA’s. Students who don’t qualify for an IEP may still qualify for a 504 plan.
FAPE (Free Appropriate Public Education)
The guarantee that every eligible child with a disability receives education and related services at no cost, designed to meet their individual needs, in the Least Restrictive Environment. Both IDEA and Section 504 require FAPE, though they define “appropriate” somewhat differently.
LRE (Least Restrictive Environment)
The principle that students with disabilities should be educated alongside their non-disabled peers to the maximum extent appropriate. Accommodations are one of the primary tools for making LRE possible.
FERPA (Family Educational Rights and Privacy Act)
FERPA protects personally identifiable information (PII) in student education records. It governs who can access those records and limits how they can be shared.
Why it matters when using AI: This is the big one. A teacher who pastes a student’s IEP into ChatGPT to draft accommodations has created a FERPA disclosure to a third party. The risk doesn’t live in the tool. It lives in what you type into it.
Here’s the concrete example from the TCEA blog that illustrates this perfectly:
Risky prompt: “Write an IEP reading goal for Marcus Johnson, student ID 48291, who attends Riverside Elementary and has been diagnosed with dyslexia.”
Safe prompt: “Write a SMART IEP reading goal for a fourth-grade student who currently reads at a second-grade level and struggles with auditory processing.”
Same task. Completely different risk profiles. For a deeper look at keeping student data safe, read this guide on using AI without violating FERPA.
PII (Personally Identifiable Information)
Includes direct identifiers like a student’s name, ID number, or Social Security number, as well as indirect identifiers like date of birth, parent names, or any combination of details that could trace back to a specific student. Under FERPA, PII in education records cannot be disclosed without consent.
Why it matters when using AI: Anonymization (removing all PII before entering information into an AI tool) is the single most important safeguard for FERPA compliance. If you can’t identify the student from the prompt, neither can the AI vendor.
DPA (Data Processing Agreement)
A contract between a school district and a technology vendor that establishes how student data will be handled, stored, and protected. DPAs specify data retention periods, security measures, breach notification procedures, and usage restrictions.
Why it matters when using AI: District-approved AI tools with signed DPAs are the safest option for accommodation work. If your district hasn’t signed a DPA with a particular AI platform, using it for anything connected to student records is a compliance risk. Check with your technology coordinator before using any new tool.
For a full vendor evaluation framework, see this data processing agreement checklist.
AI-Specific Terms for Educators
Explore 23+ free AI tools for teachers
Browse All Tools →These definitions are for teachers who are competent professionals but not necessarily tech-native. No judgment here. The goal is clarity.
Generative AI / LLM (Large Language Model)
Generative AI refers to artificial intelligence systems that create new content (text, images, code) based on patterns learned from training data. An LLM is a specific type of generative AI trained on massive amounts of text. ChatGPT, Claude, and Gemini are all LLMs.
A critical caveat: LLMs are trained on literature that doesn’t adequately reflect the experiences of people with disabilities, which creates the risk of bias in their outputs. This is why human review is essential, not optional. For more on how AI works in education tools, see how TeachTools handles AI.
Prompt
The instruction or question you give an AI tool. The quality of your prompt directly determines the quality of the output. In accommodation work, a well-written prompt includes the grade level, the disability-related need (without PII), the type of accommodation you’re looking for, and any constraints (e.g., “must be implementable in a general education setting”).
System Prompt / Persona Prompt
A set of instructions pasted into the “Custom Instructions” or first message of an AI chat so the tool follows specific rules automatically. For IEP and 504 work, a system prompt might instruct the AI to never ask for student names, to always format goals in SMART format, and to flag when a suggestion is a modification rather than an accommodation.
Practitioners on Reddit and educator forums share these system prompts freely. Some educators have created dedicated IEP tools within ChatGPT that walk users through each section of the document while enforcing privacy guardrails.
Prompt Library
A simple document (often a shared Google Doc or spreadsheet) containing ready-to-paste prompts for specific IEP tasks: PLAAFP narratives, SMART goals, accommodation suggestions, behavior plan language, and progress monitoring notes. Building a prompt library with your SPED team means everyone starts from a tested, anonymized template instead of writing from scratch each time.
Anonymization
The process of stripping all personally identifiable information from data before entering it into an AI tool. This is the most important FERPA safeguard when using AI for IEP and 504 plan work. Replace student names with generic descriptors (“a third-grade student”), remove school names, and never include ID numbers, birthdates, or parent information.
Some clients of dedicated IEP AI platforms report reducing writing time from 3-4 hours to approximately 20 minutes per IEP. But that speed only matters if the data going in is clean. Privacy first, efficiency second.
Emerging Concept: AI as Assistive Technology in the IEP
One development worth watching: some school districts have begun listing large language models as an assistive technology accommodation within the IEP itself. Rather than using AI to write the IEP, the student uses AI as a support tool in the classroom, similar to how text-to-speech or graphic organizers are listed as accommodations.
This is still emerging and controversial, but it represents a fundamentally different relationship between AI and the IEP. Instead of AI being the drafter, it becomes the accommodation.
How AI Fits the Accommodation Workflow
Understanding these terms is useful. Connecting them into a workflow is what makes them actionable. Here’s how the pieces fit together when using AI to create accommodations for IEPs and 504 plans:
- Review the PLAAFP. Understand the student’s current performance, strengths, and needs.
- Anonymize. Strip all PII from any data you plan to enter into an AI tool.
- Prompt the AI. Use a tested prompt from your prompt library to request accommodation suggestions. Specify the grade level, disability-related need, accommodation category (presentation, response, setting, or timing), and plan type (IEP or 504).
- Review critically. Check whether the AI’s suggestions are accommodations or modifications. Verify they’re specific to the student’s actual needs, not just generic outputs based on a disability label.
- Discuss with the team. Bring the AI-drafted suggestions to the IEP or 504 meeting as a starting point, not a finished product.
- Finalize the document. The human team makes the final decisions. AI assisted. You decided.
- Create the materials. After the meeting, build the worksheets, assessments, and lesson plans that implement the accommodations.
That last step is where tools built for classroom materials come in. You can generate differentiated worksheets matched to a student’s accommodations, or create quizzes with adjusted formatting. The IEP meeting decides what the student needs. The classroom materials make it real.
One practitioner writing for NGLC captured the right mindset: “It’s not a one-click solution and requires some layered approaches and mindful consideration, but I would argue that it’s still worth integrating into your practice. What I want from LLM is not to replace teachers’ thinking and expertise, but to assist us in tasks.”
And from the other side, one Reddit user in r/Teachers offered a grounding reminder: “I am one of the few not in favor of AI… it’s one thing to use it as a guideline to teach, but IEPs are legal documents affecting human lives.” Both perspectives matter. The AI gets you 70-80% of the way there. Your expertise, your knowledge of the student, and your professional judgment are the other 20-30%.
Frequently Asked Questions
Can AI write an entire IEP or 504 plan?
Technically, yes. About 15% of SPED teachers reported using AI to write IEPs or 504 plans in full during 2024-25. But IDEA requires each IEP to be individually tailored. An AI-generated plan that hasn’t been substantially reviewed and edited by the IEP team is unlikely to meet legal requirements. Use AI to draft sections, not to replace the process.
Is it a FERPA violation to paste student information into ChatGPT?
It can be. Entering personally identifiable information into a consumer AI tool without a data processing agreement constitutes a disclosure to a third party under FERPA. The safest approach is to anonymize all data before entering it and to use district-approved tools that have signed DPAs.
What’s the difference between an accommodation and a modification when using AI to create IEP supports?
An accommodation changes how a student accesses the same content (extended time, audio versions of texts). A modification changes what the student is expected to learn (simplified content, reduced assignments). AI tools don’t always label their suggestions correctly, so always verify. Modifications can affect diploma eligibility in many states.
How much time can AI actually save on IEP paperwork?
Estimates vary. CDT research suggests weekly AI users may save up to six weeks over a school year. Some platforms report reducing per-IEP writing time from 3-4 hours to about 20 minutes. The real savings depend on how well you’ve built your prompt library and how much review the outputs need.
Are AI-generated IEP goals as good as human-written ones?
Research suggests they can be. A study of experienced special educators found no statistical difference between teacher-written goals and AI-assisted goals on key quality measures. A University of North Carolina study found that teachers trained on how to use AI for IEP goals actually produced higher-rated results than those who didn’t use AI.
What AI tools are safe to use for IEP and 504 accommodation work?
The safest options are district-approved platforms with signed data processing agreements, FERPA-supportive policies, and clear data retention limits. Consumer tools like the free version of ChatGPT lack these protections. Always check with your district’s technology coordinator before using any AI tool for student-related work. You can review a privacy checklist for AI tools to evaluate options.
Can AI suggest accommodations based on a student’s disability category?
Yes, and it’s one of the more common use cases. IDEA defines 13 disability categories, and AI can generate accommodation suggestions organized by category. But category-based suggestions are starting points, not finished recommendations. Two students with the same disability label can need very different supports. Always match AI suggestions against the individual student’s PLAAFP.
Is there a risk of bias in AI-generated accommodations?
Yes. Large language models are trained on text that doesn’t adequately represent the experiences of people with disabilities. This can lead to stereotypical or incomplete accommodation suggestions. A board-certified SPED advocate writing on Substack warned that over-reliance on AI risks “generic accommodations instead of truly individualized supports.” Human review is the primary safeguard against bias.
Understanding how to use AI to create accommodations for IEPs and 504 plans starts with knowing the language. This glossary gives you the vocabulary. The next step is putting it into practice with a single, anonymized prompt and seeing what comes back. Then edit, refine, and bring your expertise to the table.
Ready to build the classroom materials that bring those accommodations to life? See how TeachTools supports teachers with 23 purpose-built tools for worksheets, quizzes, lesson plans, and more.