On 21 February 2026, I ran AI readiness workshops with school leaders at Cambridge International Schools Day in Accra, Ghana. Twenty-four schools completed an AI Readiness Framework, a self-assessment tool that scores schools across five dimensions of AI preparedness. Twenty-eight responses were collected in total, as several schools had more than one participant complete the assessment.
The results tell a clear story. Schools are investing in hardware and tools. They are not investing in the governance and policy structures needed to use them well.
The overall picture
The average readiness score across all responses was 47.8%, placing the typical Cambridge school in Ghana firmly in the Early Adoption tier. That number on its own is neither alarming nor surprising. It reflects a system in motion, with real effort underway but significant work still ahead.
The distribution tells you more. Eighty-two percent of schools fall in the bottom two readiness tiers:
- Foundation Building (0-40%): 10 schools (36%)
- Early Adoption (41-60%): 13 schools (46%)
- Active Implementation (61-80%): 4 schools (14%)
- Transformation (81-100%): 1 school (4%)
Only five schools have moved beyond Early Adoption. Only one, International Community School (ICS) in Accra, which hosted the event, has reached the Transformation tier at 84%. The gap between the highest and lowest scoring schools is 64 percentage points. This is not a system moving at the same speed.
Where schools are strong, and where they are not
The five dimensions of the framework reveal a consistent pattern. Schools score highest on Infrastructure and Resources (58.8%) and lowest on Policy and Ethics (35.4%). There is a 23 percentage-point gap between the two.
Here are the dimension averages, from strongest to weakest:
- Infrastructure & Resources: 58.8%
- Curriculum & Pedagogy: 52.7%
- Staff Capacity: 50.9%
- Leadership & Governance: 41.2%
- Policy & Ethics: 35.4%
The shape of the radar chart is the real finding. It is consistently lopsided. Schools have connectivity. They have devices. Many are experimenting with AI in their classrooms. But 89% of schools had either Leadership and Governance or Policy and Ethics as their weakest dimension. The tools are arriving faster than the frameworks to guide their use.
This pattern is not unique to Ghana. A 2025 RAND survey found that fewer than half of US principals reported having school or district policies on AI use, even as adoption rates climbed past 50% among both teachers and students. In England, a 2025 Sutton Trust survey found that only 9% of state school leaders had an official AI strategy in place, even as AI tool use among teachers continued to grow. The governance gap is global.
The spectrum
The range across schools is striking. ICS, the highest-scoring school, achieved 100% in Curriculum and Pedagogy, meaning AI is embedded across subjects with clear pedagogical intent. Even ICS, though, scored its lowest in Policy and Ethics at 60%, reinforcing that governance lags behind practice even in the most advanced schools.
At the other end, the lowest-scoring school recorded 20% across all five dimensions equally. That flat, low profile suggests a school that has not yet begun to engage with AI in any structured way.
The average school sits at 48% overall, with Infrastructure as its strongest dimension (59%) and Policy and Ethics as its weakest (35%).
What this means
Three things stand out from this data.
First, the investment sequence is backwards. Schools are buying devices and subscribing to platforms before establishing who is responsible for AI decisions, what ethical boundaries apply, or how student data will be protected. This is understandable. Hardware is tangible, fundable, and visible to parents. Policy work is slow, unglamorous, and requires expertise that many school leaders have not yet developed. But it creates risk. When UNESCO’s AI Competency Framework for Teachers identifies ethics and a human-centred mindset as foundational competencies, it is making a practical argument, not a philosophical one. Without governance, every AI tool a school deploys is an unmanaged experiment.
Second, the middle is crowded. Nearly half the schools cluster in the Early Adoption tier. These are schools that have started but have not yet built the institutional muscle to sustain and scale their efforts. The risk for these schools is stalling. Initial enthusiasm fades. The teacher who championed AI moves on. Without leadership structures and policy anchors, progress becomes fragile.
Third, transformation is possible but rare. ICS demonstrates that a school in Accra can reach 84% readiness. It also demonstrates how much deliberate effort that requires. The gap between ICS and the average school is not primarily about budget. It is about intent, structure, and sustained leadership commitment.
What to do about it
If you are a school leader reading this and recognising your own institution in these numbers, here is where I would start.
Start with governance, not technology. Appoint someone responsible for AI strategy. Form a small working group. You do not need a perfect policy before you begin, but you need a named person, a regular meeting, and a mandate to make decisions.
Audit what you already have. Many schools are further along on infrastructure than they realise, and further behind on policy than they assume. A structured self-assessment, like the one these 24 schools completed, makes the gaps visible. You cannot close a gap you have not measured.
Connect policy to pedagogy. The strongest schools in this dataset do not treat AI as an IT project. They treat it as a teaching and learning initiative with infrastructure requirements. The OECD’s Digital Education Outlook 2026 confirms that technology adoption without pedagogical integration produces disappointing results.
Build staff capacity with purpose. The average Staff Capacity score of 50.9% suggests that teachers are willing but undersupported. Professional development needs to go beyond tool training. Teachers need help understanding what AI changes about assessment, feedback, and the design of learning experiences.
What comes next
Twenty-four schools in one city is a snapshot, not a verdict. But it is an honest snapshot. These school leaders showed up, did the work, and now have a baseline they can build from. That matters more than any score.
The radar chart tells the story. The shape is lopsided, and the shape is fixable. Schools do not need to be perfect across all five dimensions tomorrow. They need to know where they stand today, and they need to start with the dimensions they have been avoiding.
For most schools, that means governance and policy. The unglamorous work. The work that makes everything else sustainable.