Abstract
Political rhetoric plays a crucial role in shaping national strategies and communicating state priorities. This study leverages advanced analytics and Natural Language Processing (NLP) tools to analyze the thematic content and frequency of key phrases in Kazakhstan's presidential messages from 1997 to 2024. Using methods such as topic modeling, lexical density analysis, and frequency distribution, we assess how rhetoric aligns with progress in key indicators. Additionally, we compare elements of political rhetoric with selected healthcare indicators, attempting to identify correlations.However, it is important to emphasize that our goal was not to establish causal links, as we are limited by data availability. Instead, we aim to demonstrate that text analysis tools, including those used in AI-driven research, can be applied to assess political rhetoric. Our findings illustrate the potential of such methods in evaluating discourse trends and their alignment with national development priorities.