The fundamental term of this research is didactic possibilities of artificial intelligence — understood as the pedagogical potential, instructional capabilities, and educational affordances that AI-powered technologies provide for optimizing teaching and learning processes, including personalization of instruction, automation of assessment, adaptive content delivery, and enhancement of student engagement [1].

The relevance of investigating AI applications in education has reached unprecedented significance in the contemporary educational landscape. Global investment in artificial intelligence development has surpassed one trillion dollars, with projected contributions to the world economy reaching seven trillion dollars within the coming decade [2]. Educational institutions worldwide are actively seeking ways to harness these technologies to address persistent challenges including teacher shortages, growing student populations, and the demand for individualized instruction.

The Republic of Kazakhstan has demonstrated remarkable commitment to educational digitalization and AI integration. President Kassym-Jomart Tokayev's 2025 State of the Nation Address, titled «Kazakhstan in the Era of Artificial Intelligence: Current Challenges and Solutions through Digital Transformation», established the strategic direction for national development [3]. The Address declared that building a digital state represents a strategic choice determining Kazakhstan's future, with complete transition to digital governance targeted within three years. The AI-Sana program was launched to involve up to 100,000 students in high-tech projects, emphasizing that AI competency development must begin at the school level.

On November 17, 2025, President Tokayev signed Law No. 230-VIII «On Artificial Intelligence», establishing the first comprehensive legal framework for AI development, use, and regulation in Kazakhstan [4]. This landmark legislation introduces mandatory labeling requirements for synthetic content, clarifies copyright provisions for AI-generated works, prohibits manipulative AI practices, and establishes risk-based classification systems. The law entered into force on January 18, 2026, positioning Kazakhstan among early global adopters of dedicated AI legislation.

The Ministry of Education and Ministry of Digital Development jointly approved the Conceptual Foundations for AI Implementation in Secondary, Technical, Vocational, and Post-Secondary Education for 2025–2029, establishing unified national standards covering ethics, legal regulation, personal data protection, and academic integrity [5]. Elements of artificial intelligence have been integrated into Digital Literacy and Informatics subjects beginning with the 2025–2026 academic year.

Internationally, the European Union's Artificial Intelligence Act, adopted in 2024 and becoming progressively applicable from February 2025, classifies educational AI systems as high-risk, requiring stringent compliance measures including transparency, human oversight, and bias mitigation [6]. The Act prohibits emotion inference systems in educational institutions and mandates AI literacy for all personnel interacting with AI systems. UNESCO's guidance documents on generative AI in education provide frameworks for human-centered implementation that protects learner rights while enabling innovation [7].

Kazakhstani scholars have contributed significantly to understanding educational technology integration. Kuanbayeva B., Mukhtarkyzy K., and colleagues investigated augmented reality applications supporting collaborative learning in science education, demonstrating positive outcomes for student engagement [8]. Zhukabayeva T. K. and research partners examined digital transformation for sustainable development of higher education, identifying key success factors for technology adoption [9]. Seitova V. analyzed innovative technology implementation in Kazakhstan's educational context, highlighting both achievements and persistent challenges [10].

Russian pedagogical science provides foundational frameworks through the works of Polat E. S., whose research on new pedagogical and information technologies established principles for integrating digital tools into instruction [11], and Selevko G. K., whose comprehensive encyclopedia of educational technologies systematized approaches to technology-enhanced learning [12].

International researchers including Holmes W. and Luckin R. have extensively examined AI in education, emphasizing the need for ethical frameworks, transparency, and human-centered design [13]. Their collaborative work established foundational concepts for understanding how intelligent tutoring systems, adaptive learning platforms, and AI-powered assessment tools can enhance educational outcomes while requiring careful attention to potential biases and limitations.

Theoretical Framework for AI-Enhanced Didactics

The didactic possibilities of artificial intelligence in education encompass multiple interconnected dimensions that transform traditional pedagogical approaches. Contemporary research identifies several key capabilities: personalized learning pathways, intelligent tutoring systems, automated assessment and feedback, content generation and adaptation, learning analytics, and administrative automation.

Personalized learning represents perhaps the most significant didactic opportunity offered by AI technologies. Machine learning algorithms analyze individual student performance data, learning preferences, and engagement patterns to generate customized instructional sequences. Research demonstrates that AI-driven personalization can accommodate diverse learning styles, pace instruction appropriately, and identify knowledge gaps requiring targeted intervention.

Intelligent tutoring systems (ITS) provide adaptive, one-on-one instruction that responds dynamically to student inputs. These systems maintain detailed student models tracking mastery levels across knowledge domains and adjust problem difficulty, hints, and explanations accordingly. Studies indicate that well-designed ITS can approach the effectiveness of human tutoring while offering unlimited availability and consistent quality.

Fig. 1. Model of AI Integration in Educational Process (The model was developed by the author based on artificial intelligence)

Figure 1 presents a comprehensive model illustrating the integration of AI tools across didactic functions (see the interactive diagram below).

Practical Implementation and Challenges

The integration of AI into Kazakhstan's educational system reflects broader global trends while addressing national priorities. The government's investment of 650 billion tenge in research initiatives includes AI literacy courses across universities, establishment of AI specializations at 17 institutions, and partnerships with international organizations including UNICEF and UNESCO.

However, significant challenges accompany these opportunities. Research identifies concerns regarding the digital divide, with disparities in access to technology and internet connectivity particularly affecting rural and socio-economically disadvantaged communities. Teacher preparedness represents another critical factor, as effective AI integration requires pedagogical knowledge combined with technical competency. Studies indicate that positive teacher attitudes toward AI significantly influence adoption success, yet many educators report insufficient training and support.

Ethical considerations demand particular attention. The EU AI Act's classification of educational AI as high-risk reflects legitimate concerns about algorithmic bias, data privacy, and potential negative impacts on student autonomy and critical thinking development. Kazakhstan's AI legislation similarly emphasizes transparency, accountability, and protection of fundamental rights, prohibiting manipulative AI practices and requiring clear disclosure of AI-generated content.

Research reveals concerning patterns regarding AI dependency. Studies demonstrate inverse relationships between increased AI literacy and traditional cognitive skills including problem-solving, critical thinking, and creative abilities. These findings underscore the importance of balanced implementation approaches that leverage AI capabilities while preserving essential human competencies.

In conclusion, the didactic possibilities of artificial intelligence in education present transformative opportunities alongside significant responsibilities. This analysis demonstrates that AI-powered tools offer substantial potential for personalizing instruction, automating assessment, enhancing student engagement, and improving administrative efficiency. Kazakhstan's comprehensive legislative and policy framework, including the 2025 Law on Artificial Intelligence and national standards for AI in education, establishes a foundation for responsible innovation aligned with international best practices.

Successful realization of AI's didactic potential requires attention to multiple factors: adequate infrastructure and equitable access, comprehensive teacher preparation programs, ethical guidelines protecting student rights, and pedagogical approaches that complement rather than replace human instruction. The goal must be developing students who can confidently work with future technologies while preserving critical thinking, creativity, and other essentially human capabilities.

Future research should examine long-term outcomes of AI integration in Kazakhstani educational contexts, investigate effective models for teacher professional development, and explore culturally responsive approaches to AI implementation that honor national values while embracing technological advancement. The era of artificial intelligence in education has arrived; the challenge lies in harnessing its possibilities wisely for the benefit of all learners.

References:

1. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.
2. Tokayev, K.-J. (2025, October 2). Speech at the Digital Bridge 2025 International Forum. Official website of the President of the Republic of Kazakhstan. https://www.akorda.kz/en/speech-by-president-kassym-jomart-tokayev-at-the-digital-bridge-2025-international-forum-29941
3. Tokayev, K.-J. (2025, September). State of the Nation Address «Kazakhstan in the Era of Artificial Intelligence: Current Challenges and Solutions through Digital Transformation». Official website of the President of the Republic of Kazakhstan. https://www.akorda.kz
4. Law of the Republic of Kazakhstan No. 230-VIII «On Artificial Intelligence» (November 17, 2025). https://online.zakon.kz/Document/?doc_id=34207749
5. The Astana Times. (2025, September 18). Kazakhstan Establishes National Standards for Artificial Intelligence in Education. https://astanatimes.com/2025/09/kazakhstan-establishes-national-standards-for-artificial-intelligence-in-education/
6. European Parliament. (2024). EU AI Act: First Regulation on Artificial Intelligence. https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence
7. UNESCO. (2023). Guidance for Generative AI in Education and Research. Paris: UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
8. Kuanbayeva, B., Shazhdekeyeva, N., Zhusupkalieva, G., Mukhtarkyzy, K., & Abildinova, G. (2024). Investigating the role of augmented reality in supporting collaborative learning in science education: A case study. International Journal of Engineering Pedagogy, 14, 149–161. https://doi.org/10.3991/ijep.v14i1.42391
9. Zhukabayeva, T.K., Baumuratova, D.B., Zholshiyeva, L., Karabay, A., & Abdrakhmanov, K.A. (2025). Digital transformation for sustainable development of higher education. Bulletin of Shakarim University. Technical Sciences. https://tech.vestnik.shakarim.kz/jour/article/view/2155
10. Seitova, V. (2024). Innovative technologies in education: A case study of implementation in Kazakhstan. Eurasian Science Review, 2(3), 187–200. https://doi.org/10.63034/esr-77
11. Polat, E.S., Bukharkina, M.Yu., Moiseeva, M.V., & Petrov, A.E. (2008). New Pedagogical and Information Technologies in Education System. 3rd ed. Moscow: Academia. ISBN 978–5–7695–4788–1
12. Selevko, G.K. (2006). Encyclopedia of Educational Technologies. Vol. 1–2. Moscow: NII School Technologies. ISBN 5–87953–227–5
13. Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century. London: IOE Press. ISBN 978–1782772095