Artificial intelligence (AI) is being rapidly adopted in education, including the evaluation of
student performance and the assessment of teacher professional capabilities. The following presents a discussion
of AI’s potential applications in each stage of Kazakhstan’s national educational assessments, from test item
development to piloting, adaptive administration, automated scoring, and results interpretation. Methodology
and Methods: A literature review of academic reports and practical applications reveals that AI has significant
potential to enhance the efficiency, objectivity, and analytical depth of assessments. Results: These AI solutions
enable the development of multi-modal tasks, the identification and addressing of anomalies in piloting, intelligent
proctoring during administration, transparent scoring of open-ended responses, and deep learning analytics.
At the same time, challenges related to algorithmic bias, data privacy, ethical responsibility, and algorithmic
reliability must be addressed to deploy AI successfully. Scientific Novelty: This study presents one of the first
systematic analyses regarding how AI can be integrated into all stages of Kazakhstan’s national assessment cycle
and offers a unified conceptual model linking multimodal task development with adaptive delivery, automated
scoring, and deep-learning-based diagnostic analytics. Practical Significance: It also recognizes the need to
upgrade infrastructure, create regulations, train workers, and introduce robust quality assurance systems. When
used systematically and progressively, AI can help make assessments more transparent, equitable, and efficient.
This would turn extensive evaluation into a flexible instrument for enhancing instruction and learning.