This informal CPD article, ‘The Role of AI in Building Outstanding Individual Education Plans (IEPs)’, was provided by Dr. Catherine O’Farrell of Incluzun HR Consultancy, who provide Quality Learning Support Assistants around The United Arab Emirates.
Across the UK, schools are working harder than ever to provide meaningful, personalised support for pupils with Special Educational Needs and Disabilities (SEND). Individual Education Plans (IEPs) or SEND Support Plans remain one of the most important tools for translating assessment information into practical classroom action. Yet, despite their importance, IEPs are often time-consuming to produce, inconsistent in quality, and sometimes disconnected from daily teaching practice.
A 2019 report outlines how AI can analyse learner data to generate personalised recommendations and adaptive goals. It emphasises that AI enhances rather than replaces professional judgement by improving precision and consistency in educational planning. (1)
Artificial Intelligence (AI) is now emerging as a powerful support tool in this space. When used ethically and professionally, AI can help schools design clearer, more targeted, and more responsive IEPs — not by replacing professional judgement, but by strengthening it.
Moving from Paperwork to Personalisation
One of the longstanding challenges with IEPs in UK schools is that they can become compliance documents rather than living plans. Teachers and SENCOs may spend hours writing targets, yet classroom staff may still feel unsure about what this means in practice on Monday morning.
AI can help bridge this gap by:
- Analysing assessment data to highlight patterns in learning needs
- Translating diagnostic or professional reports into classroom-friendly strategies
- Suggesting evidence-informed interventions aligned with specific barriers to learning
Instead of generic targets such as “Improve sitting tolerance”, AI-supported systems can help staff refine targets into something more actionable, for example:
“Will remain seated and attentive for 3-5 minutes using a structured prompt scaffold in 4 out of 5 sessions.”
The key shift is from broad aspiration to precision and clarity, which supports both teaching and accountability.
Improving Target Quality and Measurability
Outstanding IEPs include SMART targets — specific, measurable, achievable, relevant, and time-bound. However, writing high-quality targets requires expertise and time, both of which are stretched in many schools.
D. Mitchell developed an AI tool to support this. Mitchell’s meta-analytic synthesis identifies evidence-based classroom strategies such as scaffolding, explicit instruction, and structured feedback as central to effective SEND provision. His work supports the importance of translating assessment findings into practical, classroom-level strategies, a process AI can help systematise. (2)
AI tools can assist SENCOs and teachers by:
- Reformatting broad concerns into measurable learning outcomes
- Suggesting appropriate review timelines
- Linking targets to developmental milestones or curriculum expectations
For example, if a teacher inputs: “Struggles to stay focused during independent tasks”, AI can propose structured targets such as:
- “Will remain engaged in an independent task for 10 minutes using a visual timer and checklist, increasing to 15 minutes over 8 weeks.”
This does not replace professional review — but it raises the baseline quality of target setting across a school.
Strengthening the Link Between Assessment and Provision
A common weakness in IEPs is the disconnect between assessment findings and classroom strategies. Educational psychologist reports, speech and language therapy recommendations, and occupational therapy advice can be lengthy and highly technical.
AI can support by:
- Summarising professional reports into key classroom implications
- Highlighting strategies that align with identified needs
- Organising recommendations under areas such as communication, cognition, sensory processing, and social interaction
This makes multi-agency advice more accessible to busy teachers and teaching assistants, ensuring that provision is consistent, not fragmented.
Supporting Inclusive Classroom Strategies
Studies demonstrate that structured accommodations significantly impact measurable outcomes for students with learning needs. The findings reinforce the value of clearly defined, measurable targets and provision mapping within IEP frameworks. (3)
Outstanding IEPs do not simply list interventions; they describe how everyday teaching will be adapted. AI can help generate inclusive strategies aligned with the graduated approach (Assess, Plan, Do, Review) by suggesting:
- Differentiation methods
- Scaffolding techniques
- Visual supports
- Executive function aids
- Sensory regulation strategies
For example, for a pupil with working memory difficulties, AI might suggest:
- Chunking instructions
- Use of visual checklists
- Repetition and rehearsal routines
- Reduced copying from the board
This supports universal inclusive practice rather than over-reliance on withdrawal interventions.
AI can help reduce administrative load
Enhancing Review and Progress Monitoring
IEPs should be dynamic documents that evolve with the pupil’s progress. However, tracking small steps of improvement can be difficult.
AI tools can:
- Analyse assessment data over time
- Flag when progress is slower or faster than expected
- Suggest when targets may need adjusting
- Generate visual summaries for review meetings
This can be particularly valuable during termly SEND reviews, enabling clearer discussions with parents and carers about what is working and what needs refining.
Reducing Administrative Burden
SENCO workload is a national concern. Drafting, updating, and reviewing IEPs for large numbers of pupils can take significant time. AI can help reduce administrative load by:
- Generating first-draft plans based on existing data
- Auto-formatting documents into school templates
- Summarising review notes into updated targets
This allows professionals to spend more time on direct support, staff coaching, and pupil interaction, which is where impact is greatest.
Strengthening Parent and Pupil Voice
High-quality IEPs reflect the views of the child and their family. AI tools can help structure this by:
- Turning parent meeting notes into clear priority areas
- Suggesting child-friendly target wording
- Producing visual versions of plans suitable for pupil discussion
This supports co-production, a key principle within the SEND Code of Practice.
Ethical Use and Professional Responsibility
AI must be used carefully in SEND contexts. It should never replace professional assessment, nor should it make diagnostic assumptions. Schools must ensure:
- Data protection and GDPR compliance
- Secure handling of sensitive pupil information
- Professional oversight of all AI-generated content
- Clear understanding that AI provides suggestions, not decisions
The role of the SENCO, teacher, and specialist professionals remains central. AI is a tool for support, not substitution.
Building Consistency Across a School
One of AI’s greatest strengths is improving consistency. In many schools, IEP quality varies depending on who writes them. AI-supported frameworks can help standardise:
- Target-writing language
- Structure of provision plans
- Types of strategies suggested
- Review processes
This leads to a more coherent whole-school approach to SEND, aligning with Ofsted’s emphasis on inclusive practice and high expectations for all learners.
Looking Ahead
AI is not a quick fix, and it is not a replacement for skilled educators. However, when integrated thoughtfully, it can help schools move towards more precise, more inclusive, and more responsive IEPs.
Ultimately, outstanding IEPs are those that:
- Are clearly understood by staff
- Translate into daily classroom practice
- Are reviewed regularly
- Reflect the child’s voice
- Lead to meaningful progress
AI can help schools spend less time on formatting and more time on thinking deeply about the child behind the plan — and that is where true inclusion begins.
We hope this article was helpful. For more information from Incluzun HR Consultancy, please visit their CPD Member Directory page. Alternatively, you can go to the CPD Industry Hubs for more articles, courses and events relevant to your Continuing Professional Development requirements.
References:
- Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
- Mitchell, D. (2014). What Really Works in Special and Inclusive Education. Routledge.
- Elliott, S. N., & Marquart, A. M. (2004). Extended time as a testing accommodation: Its effects and perceived consequences. Exceptional Children, 70(3), 349–367.
