What Can (and Can't) Be Automated with AI in Education?

TL;DR Summary

• AI in Education: Offers time-saving and support benefits but isn't a universal fix.
• What Works Well: Text generation, admin tasks, and quiz creation - if reviewed by humans.
• Use With Caution: Grading, student writing help, and lesson planning may raise ethical or pedagogical concerns.
• Still Experimental: Personalised learning, predictive analytics, and classroom monitoring come with major risks.
• Rule of Thumb: Use AI for drafting and admin-not judgement, emotion, or surveillance.
• Bottom Line: AI should support - not replace - human educators and meaningful learning.

Why This Article Matters

In schools and colleges, AI promises to save time, personalise learning, and ease the administrative burden on staff. However, automation is not a one-size-fits-all solution. Some tasks are ideal candidates for AI support-others demand human judgement, contextual awareness, or ethical sensitivity that machines cannot replicate.

Tasks Already Being Automated

These uses are practical, widely adopted, and helpful when paired with human oversight.

✅ Text Generation & Summarisation

Used to draft:

• Lesson summaries
• Report card comments
• School announcements
• Rubrics or assessment criteria

Useful? Yes, with human review.
Key barriers: Inaccuracies (AI hallucinations), generic tone, and time required to fact-check outputs.

✅ Administrative Support

AI tools assist with:

• Scheduling
• Drafting e-mails
• Generating standard letters
• Summarising meeting notes

Key barriers:

• Data privacy concerns
• Poor nuance in sensitive communications
• Integration gaps with school information systems

✅ Quiz & Assignment Generation

Common uses include:

• Multiple-choice questions
• Grammar or vocabulary tasks
• Prompt creation for creative or academic writing

Key barriers:

• Weak alignment with curricula
• Shallow or biased question content
• Necessity of teacher review and adaptation

Tasks AI Can Support-with Caution

These uses are emerging, but not without pedagogical, ethical, or reliability challenges.

⚠️ Grading & Feedback

AI can:

• Draft feedback on essays
• Score structured responses

Barriers:

• Lack of personal insight
• Inconsistent logic in grading
• Ethical/legal issues (especially in high-stakes contexts)
• Resistance from teachers and learners

⚠️ Student Writing Support

AI writing assistants help refine grammar, structure, or clarity.

Barriers:

• Plagiarism and ghostwriting risks
• Diminished student voice
• Blurred line between support and outsourcing

⚠️ Lesson Planning & Design

AI can assist teachers in:

• Generating lesson ideas
• Matching content to learning goals

Barriers:

• No awareness of class dynamics or cultural context
• Potential for generic or unsuitable lesson flows
• Risk of eroding intentional pedagogy

What's Emerging - but Still Experimental

Innovative uses exist, but often raise equity, transparency, or trust concerns.

Personalised Learning Paths

AI systems adapt content to individual learner levels.

Barriers:

• Opaque algorithms (black box)
• Risk of widening achievement gaps
• Reduced teacher control over curricula

Predictive Analytics

Used to forecast:

• Dropout risks
• Learning difficulties

Barriers:

• Biased datasets
• Risk of labelling or stereotyping learners
• Lack of interpretability

Classroom Monitoring (High Risk)

Includes:

• Behaviour analysis via cameras or software
• Attention tracking or live activity scanning

Barriers:

• Serious privacy implications
• Cultural and legal resistance (especially in Europe)
• Student and staff discomfort

So, What Can You Trust AI With?

Here's a simple rule of thumb:

The Human-AI Balance

Every AI application in education raises a deeper question:
Who stays in control-humans or systems?

AI should support teacher judgement, not replace it.
It should amplify student learning, not reduce it to patterns.
Above all, it should respect the trust and context that define great teaching.

Read More

This article is the first in a 3-part series:

1. Understand the limits and benefits of automation (this article).
2. Beyond Automation - Explore creative, reflective, and ethical uses of AI.
3. From Tasks to Thinking - Learn how to integrate AI across the learning spectrum.