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Original language
15.06.2025
Generative artificial intelligence as a tool for developing digital competencies of university leaders
This essay focuses on the integration of generative artificial intelligence (AI) into the training of higher education management staff. The aim is to show how the tar geted formation of digital competencies and critical thinking through AI improves the quality of management and the adaptability of higher education institutions to technological challenges.
Relevance and background
Modern higher education institutions face the dual challenge of the digital age: the need to innovate in order to stay competitive and the risk of mindless ‘automation’ when algorithms replace critical thinking. On the one hand, gener ative AI (capable of analysing data, generating content and predicting scenarios)
offers great opportunities for optimising management and educational processes. On the other hand, the introduction of complex technologies requires the training of managers who can effectively apply AI for decision-making.
In 2023, the UN highlighted that the development of digital skills in educa tional leaders is a key component of achieving SDG 4. However, according to HolonIQ, only 34% of higher education institutions implement AI training programmes for managers. This suggests the need for a more systematic approach to the formation of digital literacy in the educational sphere.
Thematic vector
The focus is on analysing the role of generative AI as means of building man agerial skills and digital competencies necessary for the sustainable development of higher education institutions. Special emphasis is placed on how managers who
have mastered AI tools create a new decision-making culture within educational organisations.
Hypothesis and methodology of the study
Hypothesis: Systematic training of managerial staff in generative AI tech niques helps improve their digital competencies, managerial performance and critical thinking, which ultimately contributes to qualitative change in higher edu cation institutions.
The study is based on a pedagogical experiment (2023–2024) involving 444 university managers. Before the start of the experiment, a survey was conducted, which showed that 1-2% of respondents actively used tools like GPT, 3-5% tried to use them, and 90% only ‘knew about the existence’ of AI.
During the training the participants:
• Learned how to make correct queries to chatbots (GPT, DeepSeek, etc.);
• Conducted SWOT analysis and developed strategies using the PDCA cycle;
• Developed higher education scenarios, including data visualization.
The comparative analysis of the results using the non-parametric Friedman criterion showed a statistically significant (p<0.05) increase (p<0.05) in the pro portion of successfully completed tasks, fr om about 50–60% at the first stage to 90–99% at the final stage. The Wilcoxon signed rank criterion (with Bonferroni correction) confirmed that the use of AI was a key factor in the improvement. Statistical tests (p<0.05) confirmed that the changes were not random but were due specifically to the use of AI in the learning process.
Key results and analytics
1. Increased digital skills: Participants learnt how to structure tasks, critically evaluate AI results and formulate clarifying queries.
2. Increased analytical flexibility: Working with different models (GPT, DeepSeek) increased opportunities for forecasting, scenario analysis and resource optimisation.
3. Spreading the impact: AI-enabled managers have launched digital transformation processes in their universities by introducing chatbots nd analytical platforms to support management and educational processes.
Economic and social effects
Economic aspect:
• Lower costs for analytics and document management by automating routine operations;
• Improving the accuracy of management decisions, which helps optimise resource allocation;
• Strengthening the competitiveness of universities in the educational services market and attracting partners/investors.
Social aspect:
• Improving the quality of the educational process: teachers get access to mas sive data sets and adaptive learning tools;
• Developing critical thinking and digital literacy: a new generation of managers capable of making informed, ethical and transparent decisions;
• Creating a cultural environment that encourages innovation and interdisci plinary collaborations.
An example is the projects implemented with the support of leaders fr om Tashkent University of Information Technologies and Renaissance University of Education, wh ere AI has become a key tool for management processes and scientific research.
General conclusions and expected results
The findings demonstrate that the purposeful introduction of generative AI into the training of university managers not only improves their digital compe tences but also stimulates critical thinking and informed decision-making. Even in the course of the experiment, the participants have already implemented new approaches to management in their organisations, which has had an impact on the quality of educational programmes and HEIs’ activities in general.
Expected long-term effects:
1. Sustained improvement in the quality of management: AI-enabled managers are more efficient in allocating resources and more flexible in responding to change.
2. Dissemination of best practices: participants’ experience serves as a basis for methodological recommendations and new educational programmes that improve the overall level of digital culture in higher education institutions. Strengthening competitiveness: systematic implementation of AI makes higher education institutions more attractive to applicants and partners, expanding opportunities for international cooperation.
4. Long-term social impact: an environment emerges wh ere technology is used responsibly and effectively, linking science, education and innovation. In this way, a learning model focused on generative AI can lay the foundation for systemic digital transformation of the entire higher education system, shaping a new generation of leaders prepared for the challenges of the digital age.
Sources
1. UNESCO report “Digital transformation in education” // [Electronic resource] – URL: https://
unesdoc.unesco.org/
2. HolonIQ report (2023): Global Survey on AI in Higher Education // [Electronic resource] –
URL: https://www.holoniq.com/
3. Tashkent University of Information Technologies // [Electronic resource] – URL: https://tuit.
uz/post/suniy-intellekt- texnologiyalaridan-foydalanish-savodxonligini-oshirish
4. Renaissance University of Education // [Electronic resource] – URL: https://renessans-edu.
uz/ru/article
Relevance and background
Modern higher education institutions face the dual challenge of the digital age: the need to innovate in order to stay competitive and the risk of mindless ‘automation’ when algorithms replace critical thinking. On the one hand, gener ative AI (capable of analysing data, generating content and predicting scenarios)
offers great opportunities for optimising management and educational processes. On the other hand, the introduction of complex technologies requires the training of managers who can effectively apply AI for decision-making.
In 2023, the UN highlighted that the development of digital skills in educa tional leaders is a key component of achieving SDG 4. However, according to HolonIQ, only 34% of higher education institutions implement AI training programmes for managers. This suggests the need for a more systematic approach to the formation of digital literacy in the educational sphere.
Thematic vector
The focus is on analysing the role of generative AI as means of building man agerial skills and digital competencies necessary for the sustainable development of higher education institutions. Special emphasis is placed on how managers who
have mastered AI tools create a new decision-making culture within educational organisations.
Hypothesis and methodology of the study
Hypothesis: Systematic training of managerial staff in generative AI tech niques helps improve their digital competencies, managerial performance and critical thinking, which ultimately contributes to qualitative change in higher edu cation institutions.
The study is based on a pedagogical experiment (2023–2024) involving 444 university managers. Before the start of the experiment, a survey was conducted, which showed that 1-2% of respondents actively used tools like GPT, 3-5% tried to use them, and 90% only ‘knew about the existence’ of AI.
During the training the participants:
• Learned how to make correct queries to chatbots (GPT, DeepSeek, etc.);
• Conducted SWOT analysis and developed strategies using the PDCA cycle;
• Developed higher education scenarios, including data visualization.
The comparative analysis of the results using the non-parametric Friedman criterion showed a statistically significant (p<0.05) increase (p<0.05) in the pro portion of successfully completed tasks, fr om about 50–60% at the first stage to 90–99% at the final stage. The Wilcoxon signed rank criterion (with Bonferroni correction) confirmed that the use of AI was a key factor in the improvement. Statistical tests (p<0.05) confirmed that the changes were not random but were due specifically to the use of AI in the learning process.
Key results and analytics
1. Increased digital skills: Participants learnt how to structure tasks, critically evaluate AI results and formulate clarifying queries.
2. Increased analytical flexibility: Working with different models (GPT, DeepSeek) increased opportunities for forecasting, scenario analysis and resource optimisation.
3. Spreading the impact: AI-enabled managers have launched digital transformation processes in their universities by introducing chatbots nd analytical platforms to support management and educational processes.
Economic and social effects
Economic aspect:
• Lower costs for analytics and document management by automating routine operations;
• Improving the accuracy of management decisions, which helps optimise resource allocation;
• Strengthening the competitiveness of universities in the educational services market and attracting partners/investors.
Social aspect:
• Improving the quality of the educational process: teachers get access to mas sive data sets and adaptive learning tools;
• Developing critical thinking and digital literacy: a new generation of managers capable of making informed, ethical and transparent decisions;
• Creating a cultural environment that encourages innovation and interdisci plinary collaborations.
An example is the projects implemented with the support of leaders fr om Tashkent University of Information Technologies and Renaissance University of Education, wh ere AI has become a key tool for management processes and scientific research.
General conclusions and expected results
The findings demonstrate that the purposeful introduction of generative AI into the training of university managers not only improves their digital compe tences but also stimulates critical thinking and informed decision-making. Even in the course of the experiment, the participants have already implemented new approaches to management in their organisations, which has had an impact on the quality of educational programmes and HEIs’ activities in general.
Expected long-term effects:
1. Sustained improvement in the quality of management: AI-enabled managers are more efficient in allocating resources and more flexible in responding to change.
2. Dissemination of best practices: participants’ experience serves as a basis for methodological recommendations and new educational programmes that improve the overall level of digital culture in higher education institutions. Strengthening competitiveness: systematic implementation of AI makes higher education institutions more attractive to applicants and partners, expanding opportunities for international cooperation.
4. Long-term social impact: an environment emerges wh ere technology is used responsibly and effectively, linking science, education and innovation. In this way, a learning model focused on generative AI can lay the foundation for systemic digital transformation of the entire higher education system, shaping a new generation of leaders prepared for the challenges of the digital age.
Sources
1. UNESCO report “Digital transformation in education” // [Electronic resource] – URL: https://
unesdoc.unesco.org/
2. HolonIQ report (2023): Global Survey on AI in Higher Education // [Electronic resource] –
URL: https://www.holoniq.com/
3. Tashkent University of Information Technologies // [Electronic resource] – URL: https://tuit.
uz/post/suniy-intellekt- texnologiyalaridan-foydalanish-savodxonligini-oshirish
4. Renaissance University of Education // [Electronic resource] – URL: https://renessans-edu.
uz/ru/article
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