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Case Study: AI Literacy for Teachers at Schools / Academies

Delivering our tailored 1-Day AI Literacy workshop to provide teachers with training for practical, safe, and efficient AI use.
100% alignment with DfE policy.

Project Type

AI Training
& Adoption

Aligned With

DfE logo

Sector

Education

Workshop Value

5+ hours

Time Saving per
Teacher per Week

The Challenge

  • 51 hrs/week — average teacher workload in England (DfE 2024).
  • 1 in 10 teachers left the profession in 2022/23, with workload the top reason (NFER 2025).
  • 43% of teachers rated their AI confidence at only 3/10 (DfE 2025).
  • Most schools provide 0 hours of formal AI CPD (Chartered College 2025).
  • High GDPR risk if pupil data is mishandled or AI tools are used without safeguards (ICO AI guidance).

Department for Education Policy

  • The DfE’s AI in Education policy (2023, updated 2025) promotes AI for workload reduction and better teaching — but insists on safe, human-in-the-loop use (DfE policy paper).
  • The DfE has also asks schools to focus on safe and effective adoption (DfE support materials), along with compliance of GDPR and the Children’s Code.
  • Demanded clear governance, data protection, and parental transparency from schools (ICO Children’s Code).

The Solution: Our Tailored AI Literacy Workshop

Be AI-ready before it’s mandatory
A hands-on training programme designed by PGCE qualified AI specialists. In just 1 Day, we help your staff cut workload, stay compliant, and put student learning back at the centre.

Let's start the journey of equiping your school to move from informal, high-risk tool use towards embedded, safe and sustainable AI practice.

Key Elements:

1. Workflow-based AI adoption

We co-design prompt playbooks and AI-assisted workflows tailored to your teaching context — lesson planning, student feedback, differentiation, administration, and more — so teachers see exactly where AI can save time without compromising quality.

2. Compliance built in

GDPR, safeguarding, product-safety expectations, and DfE “human-in-the-loop” standards are taught, practised and embedded. Staff leave knowing what data they can use, what they must protect, and how to audit AI outputs safely.

3. Confidence in practice

Teachers practise prompt-writing, output checking, resource adaptation and “teaching with, not from” AI. We stress contextualising AI output — not trusting it blindly.

4. Resources that land

Participants leave with immediately usable materials — tailored lesson plan drafts, prompt frameworks, workflow “cheat sheets”, and a governance checklist adapted to the school’s digital strategy.

👉 One-day training. Significant time saved. Confident teachers. Safer AI use.
A school that’s truly AI-ready.

Key Outcomes & Impact

  • Time Savings:
    • 5 hrs/week saved per teacher → in a 50-staff school that’s 7,600 hrs/year (≈200 weeks of teaching time).
    • Time reinvested into small-group teaching, feedback, and personalised learning.
  • Student Impact:
    • More one-to-one support and differentiated resources for SEND/EAL learners.
    • Faster feedback cycles and personalised guidance.
  • Staff Confidence & Wellbeing:
    • Teachers gain confidence in using AI safely and effectively: prompt engineering, critical review of AI outputs, and governance practices become part of their daily workflow.
    • Improved job satisfaction and retention: less time spent on admin, more on teaching.
    • Reduced risk of “AI backlash” — staff are equipped to adapt AI tools, reject poor outputs, and maintain professional control.
  • Compliance & Risk Reduction:
    • GDPR, safeguarding, parental transparency and data-governance protocols are no longer afterthoughts but part of standard practice.
    • School leadership can demonstrate safe, policy-aligned AI deployment — reducing risk, increasing stakeholder trust, and creating a defensible position for inspection or parental scrutiny.
  • Future-proofing:
    • Staff trained in line with DfE policy and AI best practice.
    • School positions itself as forward-looking, preparing pupils for AI-driven futures.
    • By investing in model-agnostic AI literacy and governance, schools prepare staff to adapt as new tools arrive (for example, the roll-out of Oak’s Aila or future DfE-supported AI tools).

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