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Currently, artificial intelligence is changing the future landscape of technology and digitalization and transforming the way knowledge is generated and shared in education and science. The aim of the article is to interpret the future through interactions between education, science, and AI and to outline their potential challenges when digital transformations occur. While answering the research questions the mixed-methods approach was applied. For the study both quantitative and qualitative data was collected through descriptive and empirical survey. The empirical survey included computer-assisted web interview to assess the most relevant concepts according to the participants responses. The study involved 42 participants that were selected randomly. The selection criteria concerned educational background, previous experience, representation of diverse perspectives, theories, or approaches within the philosophy, active engagement in educational practice, and wiliness to participate. To analyse the data statistical software NVivo was applied. Approximately 70 recent scientific works were studied to present the problem through multifaceted approach. The findings show the participants’ anticipations are related to the cognitive load theory, constructivist theory, and socio-cultural theory. A number of challenges threatening innovative developments arise within the educational and scientific environments. They include ethical concerns, misinformation, digital divide, unequal infrastructure, lack of regulation, lack of digital skills, resistance to change, technology integration, and limited digital pedagogy. Ethics plays a crucial role in shaping digital transformations in education and science. The category of academic virtue is closely connected to ethical and responsible use of Ai. The paradigm of academic virtue includes ethical of knowledge, collaboration, responsibility, honesty, accuracy, adaptability, openness. AI brings automated content creation, language processing opportunities, real-time translation, and enhanced accessibility and, therefore, changes communication in the field of education and science. The research showed that the principles of effective implementation of AI in education and science include philosophical, educational, and ethical dimensions.
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