For years, educational innovation with technology has been narrated from the future: devices that would arrive in classrooms, platforms expected to transform teaching, methodologies presented as turning points. That narrative framework is beginning to fall short. In compulsory education, technology is already part of everyday school life and has ceased to be an exceptional element, becoming instead a structural condition of the education system.
The expansion of artificial intelligence, the widespread adoption of digital learning environments and the experience accumulated after the pandemic have accelerated this shift. Educational discussion is thus moving towards more concrete questions: how these technologies are used in the classroom, what impact they have on basic learning, and how they alter teaching work and school organisation. The focus moves away from the device and closer to the pedagogical decisions that accompany it.
Looking towards 2026 means paying attention to changes that are already under way, even if they are not occurring in the same way in every school. Concrete debates are emerging in classrooms: how to adapt teaching without generating inequalities, how far to rely on automated systems, or how to use available information without losing sight of students.
Building on this observation, this article proposes to organise some of the debates that currently run through educational innovation with technology and that are likely to shape educational conversations in the coming years.
How these trends were identified
The trends presented in this article are based on a systematic reading of processes that are already under way and that are beginning to acquire structural weight in compulsory education.
The analysis draws on the intersection of three dimensions. First, recent educational research, especially work focused on learning, assessment, digital competence and school organisation. Second, public policy orientations, curricular frameworks and strategic documents which, at different speeds, are incorporating technology as a stable component of the education system. Third, the everyday practice of schools and teachers, where these orientations are translated (or diluted) under real classroom conditions.
A trend is considered relevant when it appears repeatedly across these three domains and when it generates visible frictions. Trends are most clearly detected where the education system is forced to make decisions. For this reason, the analysis focuses on persistent tensions that run through current educational debate: the balance between automation and pedagogical support; personalisation of learning versus equity; the use of educational data and its implications for student care; and the gap between innovation discourse and the material conditions of schools.
Finally, a specific filter has been applied for K–12 education. Only dynamics with a direct impact on basic learning, classroom organisation and the school experience of children and adolescents have been included. Approaches specific to higher education or corporate training that cannot be transferred to compulsory education are therefore excluded.
In 2026, educational discussion is moving towards more concrete questions: how these technologies are used in the classroom, what impact they have on basic learning, and how they alter teaching work and school organisation. The focus moves away from the device and closer to the pedagogical decisions that accompany it.
The normalisation of AI within educational infrastructure
In recent years, artificial intelligence has entered educational discussion through specific tools and high-intensity debates. However, as it becomes embedded in education systems, its role is beginning to change. Rather than introducing visible novelties, AI tends to integrate into existing processes, becoming a support layer that shapes the everyday functioning of schools.
In K–12 education, this integration occurs mainly in tasks that do not always take centre stage: support for lesson planning, adaptation of materials to different learning paces, early detection of difficulties, or management of information on student progress. AI does not redefine educational practice on its own, but it does continuously modify the context in which pedagogical decisions are made.
The trend therefore does not point towards replacing teachers or abruptly transforming the classroom, but towards the normalisation of automated systems as part of educational infrastructure. Their impact accumulates over time and depends less on specific tools than on the criteria used to integrate them into school organisation and teaching work.
Looking ahead to 2026, the debate will shift away from the adoption of artificial intelligence towards its sustained use. Which functions are delegated to automated systems, how pedagogical judgement is preserved, and how spaces for human intervention are defined will be key questions. The relevance of AI in schools will lie not in its visibility, but in its capacity to quietly reconfigure the conditions of educational work.
The educational limits of learning personalisation
Learning personalisation has become one of the central arguments of educational innovation with technology. In K–12 education, it translates into increasingly widespread practices of adapting pace, content and support within the classroom.
The trend emerging towards 2026 points to a more systematic use of digital tools to adjust teaching to student diversity. Platforms that propose differentiated activities, systems that suggest specific reinforcement, or resources that allow the same content to be addressed at different levels of complexity are already part of the school landscape in many contexts.
This movement introduces clear improvements in attention to students with difficulties or different learning rhythms, but it also raises deeper questions. As personalisation relies more heavily on data and algorithms, the capacity to segment students increases, along with the early classification of learners and the fixing of expectations of progress that are not always visible or pedagogically discussed.
In compulsory education, where schools fulfil a function of cohesion and compensation, this tension carries particular weight. Adjusting teaching to individual needs without fragmenting the shared school experience becomes a delicate balance. Technology expands the possibilities for adaptation, but it also makes it easier for differences to become entrenched and normalised.
By 2026, the conversation around personalisation will no longer revolve around technical feasibility, but around its educational limits. How far to adjust, according to which criteria, and under what pedagogical supervision will be central questions in a context where personalisation has ceased to be an abstract promise and has become everyday practice.
Assessment and data: understanding better without controlling more
The use of digital platforms, activity logs and tracking systems for assessment has increased the amount of information available about what happens in the classroom and how students learn.
The trend consolidating towards 2026 is not the replacement of traditional assessment by automatic systems, but a shift in focus: from punctual measurement of outcomes to a more continuous understanding of learning processes. Digital tools make it possible to collect intermediate evidence, identify patterns of difficulty and provide useful information to adjust teaching while learning is still under way.
This shift opens up significant possibilities for formative assessment and more tailored student support, especially at key stages such as early literacy or mathematics learning. At the same time, it raises familiar dilemmas in a new context. The greater the capacity for data collection, the greater the risk of reducing learning to quantifiable indicators or transferring logics of control into educational spaces.
In compulsory education, where assessment has a pedagogical function rather than a purely certifying one, these tensions take on particular significance. The availability of data does not, in itself, guarantee better educational decisions. Everything depends on how data are interpreted, who has access to them and for what purpose they are used.
Looking towards 2026, the debate will no longer focus on whether it is possible to assess with technology, but on how to do so without impoverishing the educational experience. Finding a balance between useful information, pedagogical judgement and care for students will be one of the central issues in discussions on educational innovation.
Digital competence redefined as civic competence
For years, digital competence in schools has been associated mainly with tool use: knowing how to search for information, use applications or navigate digital environments. That approach is increasingly limited. In K–12 education, the constant presence of digital technologies and, more recently, artificial intelligence systems has shifted the debate onto broader ground.
The trend consolidating towards 2026 points to a redefinition of digital competence as a set of civic capacities. It is no longer just about knowing how to use technology, but about understanding how it works, how it shapes circulating information, and how it influences individual and collective decisions. Media literacy, the ability to evaluate sources, recognition of content generated by automated systems, and basic understanding of data-related risks take on a central role.
In compulsory education, this shift has clear curricular implications. Digital competence ceases to be an instrumental skill or a standalone subject and becomes a transversal element across different areas, from science to the humanities. The classroom thus becomes a space not only for using technologies, but also for critically analysing their effects.
This shift also responds to a social context marked by disinformation, automated content and the growing opacity of digital systems. Schools face the challenge of providing tools to navigate this environment without placing on students a responsibility that is, to a large extent, collective.
By 2026, the conversation around digital competence will no longer focus on levels of technical proficiency, but on the type of relationship that education fosters between children, adolescents and technology. The underlying question will be what role schools play in shaping citizens capable of understanding and questioning the digital systems that permeate their everyday lives.
Innovating with technology in unequal contexts
As technology becomes more firmly embedded in education systems, an issue that has long remained in the background gains prominence: the material conditions under which this innovation takes place. In K–12 education, where differences between schools and territories are significant, the introduction of technology does not start from a position of equality.
The trend emerging towards 2026 points to a change in focus. In contrast to innovation models designed for highly connected, resource-rich environments, increasing attention is being paid to solutions that function under non-ideal conditions. Technologies capable of operating with limited connectivity, shared devices or precarious infrastructure are no longer seen as exceptions, but as central to educational discussion.
This shift is not only technical, but pedagogical. In unequal contexts, innovation with technology is increasingly assessed by its impact on basic learning — reading, writing and mathematics — and by its ability to support teachers in highly diverse classrooms. The question is not which technology is most advanced, but which is viable, sustainable and useful in everyday school life.
At the same time, this trend forces a reassessment of certain dominant narratives around digital transformation. The uncritical adoption of tools can widen existing gaps if real conditions of use are not taken into account. Innovating with technology, in these contexts, means making conscious decisions about what to introduce, what to adapt and what to discard.
By 2026, the debate on educational innovation with technology will be shaped by this material dimension. The central question will be whether educational technologies help to reduce inequalities or, on the contrary, reinforce differences that already exist between schools and education systems.
A shift in focus
For years, educational innovation with technology has been told as a succession of advances. Looking towards 2026 requires changing the narrative and reading it in terms of trends rather than milestones. The tools are already in schools, and not all of them produce the same effects. Some expand possibilities; others introduce new tensions. What will matter is not distinguishing between “good” or “bad” technologies, but understanding which dynamics are becoming established, which generate friction, and what educational decisions they trigger in specific contexts.
In this terrain, trends help us identify where educational innovation is heading once it ceases to be a promise of the future and starts to be measured by its real effects on the school experience. It is in this transition that what we currently understand by educational innovation is being defined.
