AI saves teachers time, but at what professional cost?

Blog post Part of series: Artificial Intelligence in educational research and practice

AI saves teachers time, but at what professional cost?

Dan Walker, Head of PSHCE at Rawlins Academy Ash Casey, Professor of Physical Education and Pedagogy at Loughborough University 16 Oct 2026

Artificial intelligence (AI) is having a significant impact in technology-rich environments. In teaching, a profession rife with burnout and staffing shortages (DfE, 2025), AI has been positioned as a means through which to save teachers’ time and relieve pressure (Zaman, 2024). Nevertheless, teachers are divided on AI for lesson preparation due to concerns about deskilling and depersonalising teaching (Luke, 2025). Further barriers, such as a lack of knowledge and the varying levels of support across schools, are also seen as obstacles to appropriate and pedagogically sound AI-supported practice.

Building on findings from Dan’s MSc study, this blog post explores teachers’ perspectives of AI for lesson preparation.

Context

Using a non-probability voluntary response sampling method, this study garnered views from 104 active secondary school level teachers in England through an . Following this, and using variation sampling, seven participants took part in individual semi-structured interviews. Teachers were predominantly from state-maintained and multi-academy trust schools. All participants were between the ages of 21 and 66 and taught a diverse range of subjects.

Key findings

Willingness to use AI

There was an even split in the participants’ willingness to use AI, with 48 per cent saying they did and 52 per cent saying they didn’t. Interestingly, analysis showed that 63 per cent of English, humanities and social science teachers used AI, compared to only 33 per cent of mathematics, science and computer science teachers. These results may align with current strengths of generative AI with brainstorming and summarising, useful in qualitative-based subjects, contrasting with the hallucinations seen in mathematical and quantitative outputs (Jesson et al., 2024).

Professional cost

A key concern expressed by approximately 40 per cent of participants centred on the professional cost of increased AI use. It became apparent that many teachers feared that practitioners might develop an overdependence on AI. A specific concern was that heavy reliance on AI may lead to reduced teacher competency and diminish professionalism. Participants reported that, for them, a central quality of good teaching was the presence of human qualities. These were the attributes which practitioners were most worried could be lost when using AI. In contrast, using AI as a critical friend in the learning process was seen by approximately 18 per cent of participants as a positive way to support practice and thinking.

Teacher experience comparison

Thirty-four per cent of participants felt that early career teachers (ECTs) were unlikely to have built the foundational skills and competencies needed to plan effective lessons. Consequently, they were worried that outsourcing lesson preparation to AI could result in these teachers forsaking the key learning opportunities to be gained from personally planning lessons. Interestingly, 71 per cent of teachers with 0 to 5 years of teaching experience reported using AI, compared to only 26 per cent of teachers with at least 21 years’ teaching experience. This highlights the potential need for initial teacher training (ITT) providers to include AI support as part of teacher training and early career support.

‘71 per cent of teachers with 0 to 5 years of teaching experience reported using AI, compared to only 26 per cent of teachers with at least 21 years’ teaching experience.’

Moving forward

Given the higher usage reported by ECTs in this study, there is reason to expect that AI will become increasingly embedded within routine teaching practice as this cohort progresses through the profession. AI practice in education should focus on ways that do not damage the professional identity of teachers and their ethical, educative responsibilities. Teachers in this study generally viewed AI most positively when it was used to augment professional practice rather than replace teacher effort, judgment and critical thinking. However, findings suggested that both whole-scale bans and blanket encouragement are likely to fail to prepare and upskill a workforce already short on time. Against this backdrop, it seems imperative that ITT providers, in particular, consider how best to support trainees and ECTs to use AI in pedagogically critical ways.

In conclusion, the findings in this blog post advocate for both well-informed school policies and effective training to support all teachers to use AI in ways that support both teacher workloads and learners’ journeys through education.

References

Department for Education [DfE]. (2025). Working lives of teachers and leaders: Wave 3 research report. ��

Jesson, A., Beltran-Velez, N., Chu, Q., Karlekar, S., Kossen, J., Gal, Y., … & Blei, D. (2024). Estimating the hallucination rate of generative AI. Advances in Neural Information Processing Systems, 37, 31154–31201.

Luke, A. (2025). AI and the deskilling of teachers’ work. Australian Journal of English Education, 60(1), 13.

Zaman, B. U. (2024). Transforming education through AI, benefits, risks, and ethical considerations. TechRxiv. ��

Dan Walker

Head of PSHCE at Rawlins Academy

As Head of PSHCE at a large state secondary school, Dan’s work is centred on developing thoughtful, sustainable and research-informed educational practice that supports both teachers and learners. His academic background was shaped at Loughborough University, where he completed a BSc in Sport Science, Coaching and Physical Education, a PGCE in Physical Education and an MSc in Education, achieving first class honours across all three programmes. His master’s research examined teachers’ perceptions of using artificial intelligence (AI) for lesson preparation. Through this work, Dan developed a particular interest in the implications of AI for teacher workload, decision making and teacher development. This has informed his ongoing engagement with how emerging technologies, such as AI, can be integrated responsibly into everyday practice, supporting innovation without compromising educational purpose or values.

Ash Casey, Professor

Professor of Physical Education and Pedagogy at Loughborough University

As professor of physical education and pedagogy at Loughborough University, Ash has dedicated his career to enhancing the educational landscape of physical education, underpinned by the persistent pursuit of pedagogical innovation and excellence. With nearly three decades of experience, Ash’s journey has been shaped by his passion for inclusive and adaptive teaching methodologies. At the heart of his academic endeavour lies a commitment to models-based practice in physical education and this is a cornerstone of both his research and teaching philosophy. This innovative approach has not only garnered international recognition but also had an impact on the pedagogical practices within schools globally.