Part of AI Readiness for Schools: A Practical Framework for African and Global South Contexts. This post covers the first dimension, leadership and governance.
When school leaders ask me where to start with AI, they almost always ask about technology. Which tools should we use? Should we pay for ChatGPT or Gemini? Which platform is best for our learners?
These are fair questions, but they are the wrong first questions. The schools making the best decisions about AI did not start by choosing tools. They started by deciding who is responsible, what the rules are and how decisions get made. They started with governance. This post sets out what that means in practice, why it comes first, and three things any school can put in place within a week, at no cost.
The tool trap
The tool-first approach usually looks like this. A school buys a licence for an AI writing assistant. A few teachers try it. Some love it, some ignore it, some are sceptical. Learners are already using ChatGPT on their phones anyway. A parent complains about AI-written homework, a head of department asks what the school’s position is, and nobody has an answer, because nobody was asked to develop one.
This is happening in schools everywhere. In a 2023 UNESCO survey of more than 450 schools and universities, fewer than 10% had formal guidance on generative AI. Meanwhile College Board research found that 84% of high school students were using generative AI for schoolwork by mid-2025. In England, a 2025 Sutton Trust survey found that only 9% of state school leaders had an official AI strategy.
That gap is not a technology gap. It is a governance gap.
What the Ghana results showed
I have since seen the same pattern in data of my own. At Cambridge International Schools Day in Accra in February 2026, I asked a room of about 200 school leaders how many had a written AI policy. A handful of hands went up. In the workshops that followed, 24 schools completed the AI readiness self-assessment, giving 28 responses.
- Infrastructure and Resources was the strongest dimension, at 58.8%.
- Leadership and Governance averaged 41.2%, and Policy and Ethics 35.4%, the two weakest.
- 89% of schools had one of those two as their weakest dimension.
- Even the highest-scoring school, at 84% overall, scored lowest on Policy and Ethics.
Schools had connectivity, devices and teachers experimenting. What they lacked was someone in charge and a set of rules. The full analysis is in What 28 AI readiness assessments reveal about schools in Ghana.
What governance means here
I am not talking about bureaucracy. You do not need a committee that meets once a term and produces a 40-page policy. School leaders are too busy for that, and the technology moves too fast for it. Governance, at school level, means three things.
1. Someone is responsible
Who in your school is accountable for AI decisions? Not “interested in AI” or “good with technology”. Accountable. If a parent emails tomorrow asking what your position is on learners using AI for coursework, who replies?
In most schools the honest answer is that nobody has been asked. That is the first gap to close. Name an AI lead. It can be a part-time responsibility for a deputy principal, a curriculum coordinator or a confident head of department. The title matters less than the clarity: this person owns the question.
2. AI is on the agenda
Make AI a standing item at leadership meetings, not a one-off discussion. Five minutes is enough. What tools are staff using? What are parents asking? What are learners doing? What needs deciding?
This sounds small. It is not. A recurring agenda item signals that the issue matters, and it gives the conversation a place to happen before a crisis forces it.
3. There is a process for decisions
When someone wants to use a new AI tool, what happens? Who looks at it, against what criteria, and who says yes? In most schools individual teachers make these choices one tool at a time with no coordination. That is how learner data ends up in six different AI platforms, none of which has been checked for privacy.
A one-page process fixes this. A teacher proposes a tool, the AI lead reviews it, and the answer is approved, approved with conditions, or not approved. The review can be five questions:
- What problem does it solve for teachers or learners?
- What data does it collect, where is that data stored, and does that meet your country’s data protection law (POPIA in South Africa, the Data Protection Act in Ghana or Kenya, for example)?
- Is there an age limit in the tool’s own terms, and do your learners meet it?
- Does it work on the devices and connectivity you actually have, including phones and patchy data?
- What does it cost now, and what will it cost when the free tier ends?
Why this comes before technology
These three moves cost nothing. No licences, no hardware, no consultants. A school can do all three within a week, and they improve every AI decision that follows. You stop reacting and start leading.
I have seen schools with limited infrastructure make excellent AI decisions, and well-resourced schools with a device for every learner struggle because nobody had clarified who was responsible. Infrastructure matters, but it is rarely the main constraint. Clarity usually is. This matters especially in African schools, where budgets are tight and a tool bought without a plan is money that cannot be spent twice.
Governance builds teacher confidence
There is a second, less obvious reason to start here. Governance builds confidence. A 2025 Gallup and Walton Family Foundation survey found that 68% of US teachers had received no training on AI tools, and the gap is likely wider in many of the schools I work with. A compulsory training day does not close that gap on its own. It closes when teachers feel supported: when they know who to ask, and when clear boundaries make trying things feel safe rather than risky.
“Try this tool, within these guidelines, and talk to the AI lead if you are unsure” is a very different message from “AI exists and we have not decided what to do about it yet”. Confident teachers make better decisions about AI than compliant ones. For how to build that capacity once the ground rules exist, see How to Design AI Professional Development That Changes Practice.
From governance to policy
Governance is the first dimension of the readiness framework, and policy and ethics is the second. Once someone owns AI and there is a decision process, that person’s first job is to write the rules down: a short acceptable use statement for staff and learners, guidance on academic integrity, and a position on learner data. Assessment comes soon after, because the first real test of a policy is usually a piece of AI-assisted coursework. Assessment in the AI Era covers that step.
The same logic applies above the school. For a school group, district or ministry, governance means deciding who owns AI policy across the system, how tools are procured, and where learner data is hosted. Sovereign AI for Education Systems looks at those choices for ministries.
What to do this week
Before your next leadership meeting, answer three questions.
- Who is your AI lead? Put a name to it, and tell them.
- When will AI next be on the leadership agenda? Put a date on it.
- What happens when a teacher wants to use a new AI tool? Write down the process, even if it is three steps.
You do not need a full AI strategy, a chosen platform or a budget to begin. You need someone responsible, a regular conversation and a way to make decisions. The rest follows.
To see where your school stands across all five dimensions, take the five-minute AI readiness assessment or read the full framework. I run readiness workshops and leadership sessions for schools, school groups and education organisations; see Speaking or get in touch.
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