Ministry of Education AI Challenge Resource Pack: Practical Tools for Running AI Pilots

Understanding AI: what different types of AI are, how they work, and where they fall short. A shared working understanding helps your team build a common language, make informed decisions, and communicate effectively with technology vendors.

→ Refer to Fab AI’s introduction to AI, which walks you through the main definitions, main techniques, and the history of how we got where we are today. It’s as non-technical as possible in this field, but an important read for all of us who will build or use AI tools in the future.

Your country’s AI readiness with a picture of the legal and regulatory, social and cultural, economic, scientific, and technological landscape for AI in your country. This helps you identify the rules and norms you need to work within, and where you may need to help establish them through your work.

→ Refer to the UNESCO AI Readiness Assessment Methodology—a thorough, clearly structured framework for mapping your country’s context. It’s free to use and designed to be applied by ministry teams without external support.

Knowing what others have already tried helps spark ideas and gives you real starting points to build on.

→ Refer to AI Use Cases for Education Ministries—ten real examples of ministries using AI for system-level transformation and to support educators, drawn from the Ministries Challenge and beyond.

→ Also refer to How Is AI Being Used by Education Ministries to Improve Service Delivery in Low- and Middle-Income Countries?, an EdTech Hub Learning Brief that takes a case-based look at how ministries are using AI for systems-level applications: from automating administrative processes and improving Education Management Information Systems, to supporting data-driven decision-making and resource allocation. This is a useful complement if you want to go deeper on the evidence base.

A practical guide to help ministries and public agencies navigate AI procurement and engage with vendors and technical teams with confidence. This Cheat Sheet explains key terms, outlines common decision paths (including build vs. buy) and highlights the questions to ask to protect citizens, budgets, and data. It is focused specifically on contracting a vendor to build, adapt, or provide an already-developed AI-enabled product or prototype.

→ Refer to the Introduction and Section A: Procuring AI Solutions: A Checklist for Ministries (p. 3-11) in A Ministry’s Cheat Sheet for AI Integration into Government

Use this if you are building a solution in-house rather than procuring one. This Cheat Sheet is designed to help you become your own most rigorous critic. Work through the checklist, adapted from the AI development lifecycle, to ensure your Proof of Concept is robust, responsibly developed, and ready for future scaling.

→ Refer to Section B: Developing Internal Solutions (p. 12-16) in A Ministry’s Cheat Sheet for AI Integration into Government

When ministries deploy AI tools in education, critical questions arise about who owns the content AI creates, who owns the data that trains AI systems, and what rights remain with teachers, students, and the ministry itself. This Cheat Sheet helps you make informed decisions on mitigating risks, leveraging best-practice approaches, and managing the trade-off between institutional control and the pace of innovation.

→ Refer to Cheat Sheet: Intellectual Property and AI in Education

→ You can use the accompanying presentation to shape a workshop for your team.

Introduces “algorithmic safeguarding”: protecting against threats that are non-human, scalable, and often invisible until harm has already occurred. This Cheat Sheet helps educational institutions meet their duty of care to protect students not only from bad actors, but from flawed systems. It covers threat matrices, safeguarding frameworks, and a concrete implementation checklist.

→ Refer to Cheat Sheet: Safeguarding

→ You can use the accompanying presentation to shape a workshop for your team.

This covers the principle that data is subject to the laws and governance of the nation where it is collected. This is a foundational issue: the choice of where data lives is effectively a choice about who controls national records and the developmental data of future citizens. This Cheat Sheet includes definitions, a comparative overview of global approaches, and a checklist for making informed assessments.

→ Refer to Cheat Sheet: Data Sovereignty

→ You can use the accompanying presentation to shape a workshop for your team.

A practical workbook providing best-practice tools and templates, with guidance on how and when to use each one. It covers systems mapping, problem definition, hypothesis formulation, identifying critical assumptions, and planning experiments to validate that your prototype works for real users and has genuine potential to address challenges in education service delivery.

→ Refer to The Ministries of Education AI Challenge Workbook

A practical overview of Low-Code/No-Code (LCNC) tools for building rapid prototypes to test ideas and concepts early, before committing to further build costs. This Cheat Sheet is useful for teams exploring options before entering a formal procurement process.

→ Refer to Section C: AI Tooling Reference (LCNC) (p. 17-20) in A Ministry’s Cheat Sheet for AI Integration into Government

Focuses on the transition from a “Research Mindset” (which prioritises model accuracy) to a “Production Mindset” (which prioritises cost-predictability, offline resilience, and data sovereignty). It treats pilot-to-scale as a systems transition in which governance, architecture, operations, procurement, safeguarding, and equity all need to mature together. This Cheat Sheet includes checklists for scale-ready scenarios, and clear guidance on what to do when more testing or pivoting is needed first.

→ Refer to Cheat Sheet: Pilot to Scale