DfE puts England's EdTech market at £5.9bn and calls for clearer usage data

The new report finds assessment technology is growing fastest, AI -led personalized learning is attracting investment ahead of current revenue, and schools lack consistent evidence to guide procurement. A new Department for Education assessment values England's EdTech market at £5.93 billion and calls for clearer evidence on how schools buy and use technology. The Department for Education has published a new assessment of the education technology market in England, estimating that 1,092 EdTech companies generate £5.93 billion in annual turnover and attract £776 million in investment. Commissioned by the Department for Education (DfE) and conducted by PUBLIC, the June 2026 report examines how the market has changed since the department's previous assessment in 2022. It covers the size of the supplier base, how schools use digital products, barriers to adoption, and possible government action. Although the report focuses on England, its main market analysis is presented at UK level because company, employment, and investment data are generally reported nationally. Across the UK, the study identifies 1,123 EdTech companies, annual turnover of approximately £6.5 billion, investment of £782 million, and between 29,660 and 39,100 employees. The research combines company data from The Data City with interviews involving 20 schools and trusts, 24 EdTech suppliers, and 14 sector experts. It also uses 276,890 individual records supplied by EdTech Impact to examine the use of digital products across schools in one large multi-academy trust between February 2025 and February 2026. That school dataset identifies differences between products that have been purchased and those used regularly. The report recommends improved access to procurement and usage information, alongside a national EdTech roadmap, clearer evidence standards, and further research into the long-term impact of AI-led personalized learning. Assessment technology grows fastest as investment targets AI Foundational learning and EdTech hardware remain the largest parts of the supplier market. The report identifies 446 foundational learning companies, generating £2.62 billion in annual turnover, and 390 EdTech hardware companies with turnover of £2.48 billion. Management and administrative technology accounts for a further £1.39 billion. Assessment technology is smaller but records the highest annual growth rate at 18.1 percent. The category includes 71 companies, employs 2,705 people, and generates £470 million in turnover. Despite that growth, assessment technology attracted £24.3 million in annual investment. The report links its expansion to immediate school demand for products supporting automated marking, analytics, testing, and teacher workload reduction. Investment is distributed differently in personalized learning. The category generated £77 million in turnover but attracted £187 million in investment, the third-highest investment total across the seven market categories. The DfE assessment suggests investors are positioning for future demand for AI systems that adapt content, pace, and feedback to individual students. However, personalized learning recorded annual growth of 3.1 percent, the lowest rate among the categories analyzed. Assistive and inclusive learning shows the reverse pattern. Its 80 companies generated £96 million in turnover but received £8.6 million in investment, the lowest total in the dataset. The report recommends targeted action to encourage investment in assistive and inclusive technology, including stronger links between suppliers, investors, schools, Innovate UK, and existing DfE initiatives. Companies can appear in more than one category where their products serve multiple functions, so the vertical totals should not be added together to calculate the number of businesses in the market. The report also identifies a leadership diversity gap. Its company analysis finds that 13.4 percent of EdTech businesses were founded or co-founded by women, 10.5 percent were led by women, and women held 19.8 percent of registered director positions. One MAT's data shows contracts do not guarantee regular use The school-usage analysis distinguishes between active contracts and recorded engagement. An active contract confirms that a school has paid for and authorized a product. Usage records capture activity such as logins, session duration, and time spent using a platform. The report says a school can hold an active contract for a product that receives limited use. Without detailed engagement data, leaders may not know whether subscriptions are embedded in teaching and operations or accessed only occasionally. A technology leader at one multi-academy trust tells researchers: "The usage data has been really useful because... You assume teachers are using it, and actually, when you look at the usage, they're not. And yet you're paying for something that's quite expensive." Management and administrative products recorded the most consistent activity across the sample, reflecting their role in registration, behavior tracking, recruitment, finance, and account management. SalamanderSoft had 46 active contracts in the dataset, followed by Exampro with 44. Arbor MIS, MyNewTerm, IMP Software, Iplicit Finance System, and SAMpeople each had 39. Foundational learning products generated the highest volume of student engagement. The report identifies Kerboodle, Twinkl, White Rose Education, and Accelerated Reader among the curriculum and content products used across the sampled schools. Different categories also produced different patterns of activity. Gamified products were commonly used in short sessions, often for retrieval practice, while curriculum and instructional platforms recorded longer periods of engagement. Assessment products showed peaks around testing periods, rather than consistent use throughout the year. Personalized learning tools were frequently accessed later in the day, including during independent study outside scheduled lessons. The ten most-used products accounted for more than half of all recorded activity in the sample, despite the wider market containing more than 1,000 suppliers. General-purpose artificial intelligence products also appear in the data and school interviews. The report names ChatGPT, Claude, Perplexity, Gemini, and Microsoft Copilot among the tools being used for lesson planning, resource creation, administration, and some student activities. The DfE cautions that the results do not measure product effectiveness, educational value, or safety. The usage data comes from one multi-academy trust, excludes activity on personal devices and outside school systems, and should not be treated as representative of all schools in England. The report also states that naming a product does not amount to an endorsement by the DfE or PUBLIC. National roadmap and common evidence standards recommended The research identifies eight stages in the school EdTech process, from defining a need and researching products to procurement, staff training, and evaluating long-term impact. Schools reported barriers at every stage. These included limited digital planning, insufficient staff time, complex procurement requirements, weak infrastructure, difficulties assessing supplier claims, and a lack of consistent information about whether products improve learning or reduce workload. Drawing on the DfE's Technology in Schools Survey 2024-25, the report notes that one fifth of primary schools and 7 percent of secondary schools lack a digital strategy. It also says 29 percent of teachers had received training on generative AI. The report recommends that the DfE develop a national EdTech roadmap setting out priority technologies, intended uses, and indicative adoption timelines. Existing support is currently spread across separate programs and guidance, making it difficult for schools and suppliers to plan around a single national direction. It also proposes more consistent evidence expectations based on the EdTech Evidence Board's criteria. These cover educational need, theory of change, evidence of impact, implementation and usability, data protection and safeguarding, and value for money. To improve visibility of school purchasing and engagement, the report recommends collaboration between the DfE, schools, multi-academy trusts, procurement organizations, suppliers, and data platforms such as EdTech Impact. The proposed work could test ways to aggregate procurement and usage information without creating additional administrative work for schools. Current financial reporting categories are described as too broad to show clearly which products schools buy or how intensively they use them. The report also calls for longitudinal research into AI and personalized learning products, comparing their effect over time with general-purpose AI systems and other teaching approaches. Other recommendations include connecting DfE-funded pilots with staff training and scaling plans, expanding lending models for assistive and emerging hardware, supporting regional groups of schools to evaluate products together, and creating non-commercial spaces where educators and suppliers can discuss implementation. The assessment does not attach new funding or a delivery timetable to these recommendations. It places the next stage with the DfE and its partners, including schools, trusts, suppliers, investors, and research organizations, alongside existing work through the EdTech Testbed Programme and EdTech Evidence Board. Subscribe to the ETIH newsletter Sign up with your email address to receive news and updates. First Name Last Name Email Address Sign Up We respect your privacy and will not pass your email address on to third parties. However, we will occasionally send you promotional messages on behalf of our advertisers. Thank you!