More than three fifths (65%) of teachers have now had some form of training in AI, whether from formal training, an online course, informal support from colleagues, or teaching themselves how to use the technology. A third (33%) of school teachers have had no on-the-job training or support with AI, but over a quarter (27%) have taught themselves how to use it despite this. This appetite is particularly significant at schools facing challenging circumstances, such as those rated ‘Inadequate’ or ‘Requires Improvement’; teachers at these schools are more likely to have trained themselves in AI (34%) despite a lack of in-school training than those rated ‘Outstanding’ (25%), with nearly a 10-point gap standing between them.
It is worth noting, however, that teachers in schools rated ‘Outstanding’ are 12% more likely to teach themselves how to use AI – but this metric does not have the same meaning as teaching oneself AI without in-school training. There was a clear correlation between teachers receiving training and teaching themselves AI, likely because of teachers continuing their studies by exploring AI themselves. Self-teaching of your own accord, on the other hand, possibly indicates a stronger personal interest in and demand for AI. This trend could be seen across the data for affluent schools including private schools and those in wealthier regions, such as London and the South East; these schools likely have more available funding than their more disadvantaged counterparts for investing in AI, whereas the latter usually have to spend more of their resources on tackling the effects of poverty.
With many championing AI as an opportunity to tackle some of the challenges schools with lower Ofsted ratings face including helping analyse data to better understand issues like attendance, attainment, and behaviour, easing workload and financial pressures, and providing a better learning experience, this could indicate school leaders and teachers have a good awareness of the potential impact of AI, including its use cases, and are actively using it to improve school performance. This may well also suggest that there’s significant potentially untapped demand for AI in underperforming schools.
The new study also confirmed that in-school AI training is a premium. Private school teachers have more than twice as much formal AI training from a colleague or in-school session (36% vs 16%), or in an online course or structured training (6% vs 3%) than state school teachers. This suggests that there’s a cost barrier preventing AI’s widespread adoption, and with school budgets continuing to tighten, this could lead to a widening gap of AI adoption in schools in the future. This trend may also indicate private schools are readily investing in AI training as a top priority.
Another stark trend identified when comparing the top performing schools and affluent schools (private schools, schools with the least FSM-eligible students, and schools in London and the South East) was that their biggest source of training was informal support from colleagues. This possibly indicates long-term adoption of AI within these schools as teachers will have needed sufficient time to amass their own AI knowledge and become confident with the technology before supporting others. Compared to all schools in the study, informal support from colleagues is still a strong source of training, ranking third following no training or support and teaching themselves AI despite no training or support, confirming there has already been widespread AI adoption within school. But the above findings reinforce that the richest and most successful schools are well ahead with AI.
The regional disparity in training reflects this notion of AI as a premium, too. 40% of teachers in Yorkshire and the North East have had no training or support compared to just 28% of London-based teachers. This is a direct reflection of the UK Wealth Gap, indicating again that more affluent schools have much greater access to AI training than areas of deprivation.
When combined with the earlier noted trend of more teachers in underperforming schools teaching themselves AI without in-school training, we can confirm that although there is seemingly more demand for AI in richer and better performing schools (which could be caused by a number of factors including a greater awareness of AI or direction from the SLT), there is still significant demand for AI in all schools. As schools with the resources to invest in AI embrace the technology and leverage its full benefits, will this leave schools that can’t invest in AI behind?
Another point of note is the difference in AI training and support between phases: more primary school teachers have received no AI training or support (37%) compared to their secondary school colleagues (29%). The 8-point gap between these groups could be explained solely by the expected funding gap between the phases but it possibly indicates a greater demand for AI and its use cases in secondary schools.
The results also reveal that male teachers receive significantly more AI training than their female counterparts: 36% of women reported having received no AI training or support compared to just 27% of men. This supports existing research that indicates men use AI more than women. Given women dominate teaching, could this be holding back AI adoption in schools?
Our research highlighted that the more senior the role, the more AI training will be given, too. Headteachers have significantly more training than classroom teachers, with 12% having formal training from an external provider compared to just 5% of teachers. Plus, 10% more classroom teachers than headteachers have had no AI training or support.
While this is to be expected as some of the most popular and impactful use cases support school leaders, like automating report creation and analysing data, there’s still a lot of potential for AI in the classroom including streamlining processes, easing the teacher workload, and improving the learning experience for students. This may also indicate that the adoption of AI in schools is being led by school leaders who are testing its capabilities before rolling it out to all staff members.
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