Despite the rapid rise of AI tools in educational environments, many are developed without substantial involvement from educators themselves. As Zawacki-Richter et al. note in their comprehensive review, the majority of AI applications in higher education are conceived and led by computer scientists, rather than by teachers or educational specialists (Zawacki-Richter et al. 5). This disconnect often results in AI solutions that are technologically sophisticated but poorly aligned with pedagogical needs or classroom realities.
Furthermore, Emily Tate Klein discusses how many educational technology (EdTech) products suffer from a lack of teacher input during their development. This oversight can lead to ineffective or unusable tools that frustrate educators and students alike, wasting valuable resources and time (Klein). Schools and universities risk investing in AI technologies that fail to enhance learning outcomes or, worse, disrupt established educational practices.
The root of this problem is a lack of collaboration between AI developers and educators. Without teacher perspectives to inform design, critical aspects such as classroom dynamics, student diversity, and ethical considerations are often overlooked. As a result, AI risks becoming a disruptive rather than a supportive presence in education.