This case study examines the International Information Technology University in Almaty, Kazakhstan, using the AI-Augmented Sustainable Development University conceptual framework. It explores how International Information Technology University systematically integrates artificial intelligence not only as a tool for operational optimization, but as a strategic driver for advancing the three core pillars of sustainability Environmental, Social, and Economic (Governance) across institutional governance, academic programs, campus infrastructure, and community engagement. The study highlights a set of pioneering initiatives, including AIoptimized energy management systems, data-driven sustainable infrastructure planning, intelligent resource monitoring, and adaptive curriculum design aligned with Sustainable Development Goals and future workforce competencies. At the same time, the analysis critically addresses emerging tensions and risks associated with AIenabled sustainability, such as the environmental footprint of computational resources, the implications of algorithmic decision-making in governance and sustainability reporting, data transparency, and challenges related to equitable access to AI-enhanced education. By situating IITU's experience within a broader global context, the case study provides a transferable and evidence-based blueprint for universities seeking to harness artificial intelligence to accelerate sustainable development while responsibly managing technological, ethical, and social trade-offs.

The rapid integration of artificial intelligence into strategic decision-making and organisational governance is heralding a new era of AI-driven leadership. While promises of enhanced efficiency, predictive accuracy, and data-driven optimisation dominate discourse, this transformation introduces profound dualities that remain insufficiently examined. This paper provides a comprehensive conceptual analysis of the inherent tensions between operational efficiency and systemic risk in algorithmic leadership. Through a systematic review of interdisciplinary literature, we identify and categorize key challenges and threats across three domains - the ethical domain, encompassing algorithmic bias, opacity, and the erosion of moral accountability; the operational domain, involving data dependency, strategic fragility, and cybersecurity vulnerabilities; and the human-social domain, focusing on the dehumanization of workplace relations, erosion of trust, and the potential atrophy of essential human leadership competencies such as empathy and creative judgment. We argue that the core peril lies not in automation per se, but in a passive over-reliance that may precipitate a shift from human-centric to metric-centric organisational paradigms. In response, the paper proposes a framework for Human-Centric AI-driven Leadership, grounded in the principles of hybrid intelligence, algorithmic transparency, and leader-led governance. This model advocates for AI as a tool for strategic augmentation rather than replacement, emphasising the irreplaceable role of human judgment in navigating complex, value-laden decisions. Our conclusions highlight an urgent need for robust ethical frameworks, new leader competencies in AI literacy and oversight, and organisational structures designed to harness efficiency while deliberately mitigating risk. This study contributes to both scholarly and practical understanding by mapping the contested terrain of AI-driven leadership and charting a path for its responsible evolution.

Modern universities, as socio-economic systems, face challenges from globalisation, technological shifts, and sustainable development demands. Transforming a traditional university into an IT institution focused on sustainability requires new management methods. This article argues that combining adaptive leadership with Artificial Intelligence (AI) is critical for this transformation. Traditional hierarchical models are insufficient in the face of uncertainty. The authors propose a conceptual model in which adaptive leadership—at both institutional and distributed levels—uses AI to support informed decision-making, proactive adaptation, and personalised university activities. AI supports, not replaces, leadership by enhancing system analysis and scenario modelling. The core argument is that human adaptability and AI's analytic power together build a resilient, competitive IT university.

This paper critically examines how the integration of Edge Artificial Intelligence (Edge AI) and Cloud-Native Artificial Intelligence (Cloud-Native AI) can enhance agility, scalability, and governance in modern project management. Drawing on literature published between 2019 and 2025, the study applies the Technology-Organization-Environment (TOE) and Diffusion of Innovations (DOI) frameworks to explore the technical, organizational, and environmental factors enabling hybrid Edge-Cloud adoption. Using a structured narrative review, the research synthesizes evidence on how distributed intelligence architectures reshape project agility, responsiveness, and lifecycle automation. Beyond synthesis, the paper introduces a novel Dual-Loop Edge-Cloud Governance Framework. This domain-specific conceptual model formalizes two complementary governance cycles: an Operational Loop at the edge, supporting real-time, autonomous project execution and local decision-making; and a Strategic Loop in the cloud, driving organizational learning, policy refinement, and global consistency. This framework provides essential theoretical and practical guidance for project leaders seeking to manage the inherent complexity and conflicting demands of hybrid AI systems, ensuring both rapid project responsiveness and long-term organizational alignment and accountability.

The development of artificial intelligence (AI) is revolutionizing various industries, including IT project management. Augmented Competency Principles stands as a new approach that uses AI to strengthen and empower IT project teams. The essence of this principle lies in the complementary interaction of AI and the competence of project teams. Rather than replacing project managers, AI complements their competencies (knowledge, skills, and experience). AI automates routine tasks, analyzes large volumes of data, and provides recommendations and predictions, freeing up time for team members to focus on more complex and creative tasks. The benefits of using the principle of augmented competence are related to the automation of tasks and the provision of new knowledge that will significantly improve the efficiency and productivity of the team, recommendations and predictions based on data, enabling teams to make more informed and effective decisions. Access to new knowledge and insights drives innovation and leads to new ideas and solutions. AI helps identify and mitigate potential risks, which can lead to more successful projects. Applying this principle to IT project management managements will automate software testing with AI that replaces testers so they can focus on more complex types of testing, such as exploratory testing, performs customer data analysis with AI, and enables companies to better understand their customers and their needs, which can lead to improved marketing campaigns and products. It is important to note that this principle does not involve replacing project managers with AI. Instead, AI is used as a tool to empower human teams and help them achieve better results. As AI technologies continue to evolve, Augmented Competency Principles will likely play an even more important role in IT project management. AI can help teams overcome complex challenges, make better decisions, and succeed in a more dynamic and competitive environment.

The advent of AI technologies in educational institutions has reshaped the way universities innovate and address challenges. This paper explores a novel framework for managing the creative capacity of AI-powered SMART universities using the Theory of Inventive Problem Solving (TRIZ). By leveraging TRIZ principles, the study identifies methods for fostering creativity, resolving systemic contradictions, and optimizing resources within academic environments. The proposed approach integrates AI capabilities with TRIZ to enhance decision-making, improve resource allocation, and stimulate innovation in educational ecosystems.

The object of the research is a novel development methodology for innovation projects that leverages the power of the synergy principle of the Theory of Inventive Problem Solving (TRIZ). It integrates artificial intelligence (AI) technology. The problem addressed in this research is the inefficiency and limitations of traditional methods for development innovation projects, which often fail to comprehensively evaluate their potential, risks, and alignment with future technological trends. The research results in the synergistic application of TRIZ principles and AI technology for conducting comprehensive audits of innovation projects. By integrating the structured problem-solving framework of TRIZ with the analytical power of AI, a novel approach is proposed to enhance the evaluation and optimization of innovation initiatives. The paper explores how artificial intelligence algorithms can be used to analyze project data and identify potential obstacles and opportunities based on the principles of TEDx. As well as to create alternative solutions and predict possible outcomes, help identify synergies between different project elements and external factors. And to constantly monitor and adapt the innovation process based on real-time data and AI-driven insights. The difference in the research is the integration of TRIZ principles into auditing innovative projects using AI systems. The presented case showed the effectiveness of the proposed conceptual, mathematical and process models of auditing innovative projects. The master's program in artificial intelligence implemented at the Kyiv National University of Construction and Architecture (Ukraine) was chosen as an example for the case study. The study demonstrates the potential of this audit-integrated approach to improve the success rate of innovation projects by providing more accurate assessments, identifying hidden opportunities, and facilitating proactive decision-making. This research contributes to more effective and successful innovation projects by providing a data-driven and intelligent approach to project development and improvement. Within the framework of the considered case, an assessment of the acceleration of analysis and decision-making processes was carried out using the example of the innovative development program for training masters in artificial intelligence. It was found that the analysis and decision-making processes are implemented 2.68 times faster without loss of decision quality.

This paper investigates the reasoning mechanisms of multimodal AI models through the lens of TRIZ (Theory of Inventive Problem Solving) principles. Multimodal AI, which integrates and processes information from multiple data types such as text, images, and audio, has seen significant advancements. However, its reasoning capabilities remain a challenging frontier, particularly in harmonizing diverse modalities to achieve coherent outputs. By applying TRIZ, a systematic methodology widely used in engineering and innovation, we explore how these models address conflicts inherent in multimodal data fusion and reasoning. We identify key TRIZ principles such as Contradiction Resolution, the System of Systems approach, and the Concept of Ideality. We map these to the challenges and mechanisms of current multimodal AI systems. Our analysis highlights how models employ inventive principles to resolve contradictions, such as balancing accuracy across modalities or reconciling disparate representations. We also propose a novel framework inspired by TRIZ for enhancing reasoning in multimodal AI, emphasizing adaptability, scalability, and resource efficiency. This study contributes to a deeper understanding of multimodal reasoning and offers actionable insights for designing more robust and efficient AI systems. By leveraging TRIZ principles, we aim to foster innovative approaches to complex problem-solving in AI, bridging the gap between theoretical understanding and practical application.

Recent advancements in multimodal artificial intelligence (AI) have enabled models to process and integrate diverse data types, such as text, images, and audio. However, the underlying thinking mechanisms of these models remain largely heuristic and lack structured problem-solving capabilities. This paper explores the potential of applying TRIZ (Theory of Inventive Problem Solving) principles to enhance the reasoning processes of multimodal AI models. By leveraging TRIZ methodologies— such as contradiction resolution, inventive principles, and the system evolution framework—we propose a structured approach for AI-driven innovation and decision-making. The study investigates how TRIZ can optimize the learning strategies of multimodal models, improve creative problem-solving, and enhance their adaptability to complex, real-world challenges. Experimental validation is conducted on diverse AI tasks, demonstrating that integrating TRIZ-based mechanisms leads to more efficient, systematic, and explainable decision-making in multimodal AI systems. The findings highlight the synergy between TRIZ and AI, offering new pathways for developing intelligent systems capable of higher-order reasoning.

This study proposes a conceptual framework for applying artificial intelligence (AI) to sustainable development projects, emphasizing its role in mitigating risks, enhancing flexibility, and fostering resilience. A case study analysis demonstrates the practical application of AI tools in optimizing project outcomes while aligning with global sustainability goals. The findings underscore the transformative potential of AI in enabling sustainable practices and achieving long-term success in the BANI (brittle, anxious, nonlinear, incomprehensible) environment. This research contributes to the growing discourse on digital transformation and sustainability by presenting actionable strategies for project managers and stakeholders. To highlight this study’s quantitative findings, key numerical estimates derived from the case study and model validation have been incorporated into the abstract, showcasing AI’s measurable impact on project resilience, efficiency, and stakeholder confidence.

The integration of Artificial Intelligence (AI) into society, termed AI socialization, necessitates a deliberate and systematic strategy to ensure that AI technologies are embedded effectively while addressing ethical, cultural, and societal implications. This paper introduces a project management roadmap for AI socialization, rooted in a competency-based approach that aligns project activities with the requisite skills and expertise. Designed to tackle the intricate challenges of AI adoption, this roadmap employs a skills-focused strategy to guarantee that appropriate knowledge, capabilities, and proficiencies are utilized at every project phase. By blending project management methodologies with perspectives from social sciences, ethics, and public policy, the proposed framework seeks to promote a responsible and impactful assimilation of AI into society. This comprehensive method enhances the acceptance and application of AI technologies while ensuring their deployment reflects societal values and serves the collective benefit. The roadmap provides a clear and organized framework for managing projects aimed at successfully incorporating AI into societal contexts. Beyond mere technical deployment, AI socialisation involves fostering public comprehension, upholding ethical standards, and facilitating seamless human-AI collaboration. Drawing on proven project management principles, the roadmap is tailored to address the distinctive elements of AI integration. It underscores the importance of aligning project tasks with essential competencies, emphasising the pivotal role of expertise and skills in overcoming the complexities of AI adoption. This ensures that projects are carried out with both efficiency and accountability, paving the way for a socially beneficial integration of AI.

The article is devoted to the formulation of the method of maximizing the F-synergistic value of IT development projects of a project-oriented organization, which was developed within the syncretic methodology of project management. The application of the proposed method is considered in the field of IT development projects of organizations involved in infrastructure restoration projects of Ukraine. The directions of scientific research in the field of value-oriented project management are analyzed. The previously unsolved part of the scientific problem is highlighted. Objects of value analysis in a project-oriented organization carrying out IT development were identified, among which stellarator projects were highlighted. A model for determining the value of a separate component of the system is presented. The concept of F-synergistic value is defined. Such a value is proposed to be calculated through the aggregate value of three clusters that create synergistic effects both within themselves (first-order value) and among themselves (second-order value). The clusters included: "IT + people" cluster, "projects + operational activity" cluster, "methodology + environment" cluster. Models for determining the value of a separate cluster and the aggregate F-synergistic value are proposed. Variations in the selection of weighting factors for evaluating value criteria are considered. Within the syncretic methodology, a method of maximizing the F-synergistic value of IT development of a project-oriented company is proposed. The model of 27 scenarios of the dynamics of the change of the multipliers of synergy of three clusters is presented. In the corresponding tables for each scenario, a hypothesis is put forward regarding the reasons for such dynamics for each scenario, as well as a model of further IT development of a project-oriented company in response to such reasons. According to the results of the development of the method of maximizing the F-synergistic value of IT development projects of a project-oriented organization guided by syncretic methodology, directions for improving the activities of such organizations were determined. An extended SWOT analysis of the proposed method was conducted. Conclusions based on the research are formulated, prospects for further research in the chosen direction are outlined.

The rapid advancement of artificial intelligence (AI) systems has had a profound impact on various aspects of business and technology. One area greatly influenced by AI is innovation project management, which plays a critical role in driving organizational growth and success. The purpose of the paper examines the erosion of competencies in innovation project management as a consequence of the increasing reliance on AI systems. The object is innovation project management relying on the expertise, experience, and decision-making capabilities of human managers. However, the introduction of AI systems in project management processes has brought about significant changes. AI-powered tools and algorithms can automate tasks, analyse vast amounts of data, and provide valuable insights and recommendations. While this presents numerous benefits, it also raises concerns about the diminishing role of human competencies in managing innovation projects. AI systems require vast amounts of training data to operate effectively. In the process, they might overlook or undervalue the tacit knowledge and domain expertise possessed by human project managers. The results emphasize the need for project managers to develop new competencies, such as understanding AI capabilities, interpreting AI-generated insights, and effectively integrating AI systems into project workflows. To mitigate the erosion of competencies, organizations should invest in training programs that equip project managers with the necessary skills to work alongside AI systems. Recognizing these challenges and proactively addressing them through training, collaboration, and a balanced approach to human-AI interaction is crucial for organizations seeking to leverage AI while maintaining a high level of project management expertise.

In the context of the BANI (Brittle, Anxious, Non-linear, and Incomprehensible) environment, managing innovation projects demands a transformative approach to understanding and leveraging value chains. The object of the research focuses on modelling the value chain's creative level to enhance the management of innovation projects in a BANI environment. This paper proposes a novel model for assessing and enhancing the creative level of value chains within organizations to foster resilience and adaptability in a volatile ecosystem. The research problem is the increase of the creative level of the value chain to be effectively modelled and managed to enhance the success of innovation projects in a BANI environment characterized by instability, anxiety, non-linearity, and incomprehensibility. The main scientific results introduce a framework that integrates creativity metrics, systemic thinking, and real-time adaptability as core components of value chain management. Key elements of the model include – identifying creativity hotspots along the value chain, evaluating the interplay between creative potential and organizational capacity for innovation and incorporating tools for dynamic scenario planning and risk mitigation tailored to the BANI context. The research methodology combines qualitative and quantitative approaches, utilizing case studies from diverse industries to validate the proposed model. The area of practical use of the research highlights the critical role of creative value chains in enhancing organizational agility, mitigating risks, and unlocking sustainable growth in complex and unpredictable environments. This paper contributes to the literature by bridging the gap between innovation project management and adaptive systems thinking, offering actionable insights for practitioners and policymakers aiming to thrive in the challenges of the BANI world. An innovative technological product in the context of the research addresses the challenges of managing creativity and innovation within the value chain, particularly in a BANI environment. An innovative technological product in the context of the research addresses the challenges of managing creativity and innovation within the value chain, particularly in a BANI environment. Scope of the innovative technological product: Management of innovative projects.

This article examines the concept of syncretic innovation project management and its importance in today's business environment. Syncretic management is defined as an approach that combines different methods, tools and knowledge to achieve success in innovative projects. The article examines key aspects of syncretic management, such as knowledge integration, the use of different methodologies, the formation of cross-functional teams, the involvement of external resources, and many others. The influence of syncretic management on the effectiveness of innovative projects is studied and its role in promoting the sustainable development of organizations is emphasized. The article also provides examples of successful implement ation of syncretic management in various areas of business and emphasizes the relevance of this approach in the modern world of innovation. Creating value in project management is a fundamental goal for organizations seeking to achieve their strategic goals and meet stakeholder expectations. This article examines the concept of value creation through the lens of consistent project management, also known as the waterfall approach. Sequential project management is a structured methodology that divides projects into distinct phases, emphasizing careful planning, risk mitigation, quality assurance, and clear documentation. Creating value through consistent project management involves achieving a balance between structured planning and adaptability. The choice of project management methodology depends on the nature of the project and the readiness of the organization for a structured, consistent approach. Ultimately, the pursuit of value through project management is a continuous journey led by project professionals and organizations committed to delivering successful projects that meet strategic goals and stakeholder expectations.

Among the contemporary concepts fostering active innovation and the development of information support for management systems at the level of individual cities, the Smart City stands prominent. For port operations management at the port level, the notion of Smart Port is instrumental. Additionally, the fusion of these two aforementioned concepts in cities where the port assumes the role of a city-forming enterprise gives rise to the concept of Smart Port-City. This article aims to ascertain the role of the Smart Port-City concept as foundational for initiating projects that facilitate the balanced development of transportation networks and the corresponding infrastructure of both the city and the port, employing modern methodologies and technologies. Principal outcomes. The system of joint city and port development objectives has been examined. The structure of functional domains within the Smart Port-City concept has been proposed, amalgamating the two foundational components. The sequence of processes for realizing Smart Port-City objectives through relevant projects has been delineated. Conclusions. The system of joint city and port development objectives within the transportation domain serves as the cornerstone for launching transportation-centric projects benefitting both the city and the port.

The development of artificial intelligence (AI) is revolutionizing various industries, including IT project management. The object of research is the principle of augmented competence, which is a new approach that uses AI to strengthen and expand the capabilities of IT project teams. The essence of this principle lies in the complementary interaction of AI and the competence of project teams. Instead of replacing project managers, AI complements their competencies (knowledge, skills and experience). One of the hot spots is the application of AI in the process of automating routine tasks, analyzing large volumes of data and providing recommendations and predictions, freeing up time for team members to focus on more complex and creative tasks. The possibility of automating tasks and providing new knowledge, which will significantly improve the efficiency and productivity of the team, has been obtained through the use of the principle of augmented competence. As a result, data-driven recommendations and predictions enable teams to make more informed and effective decisions. Access to new knowledge and insights stimulates innovation and leads to new ideas and solutions, helps identify and mitigate potential risks, which can lead to more successful projects. Applying this principle to IT project management audits will automate software testing with AI, which replaces testers so they can focus on more complex types of testing such as exploratory testing, performs customer data analysis with AI, and enables companies to better understand your customers and their needs, which can lead to better marketing campaigns and products. It is important to note that this principle does not involve replacing project managers with AI. Instead, AI is used as a tool to empower human teams and help them achieve better results. As AI technologies continue to evolve, the principle of augmented competence is likely to play an even more important role in IT project management. AI can help teams overcome complex challenges, make better decisions, and succeed in a more dynamic and competitive environment.

The integration of artificial intelligence (AI) into the field of education has brought about transformative changes, shaping the way students learn and educators teach. This abstract explores the current trends of education technology within the context of an AI environment as of 2022. The study delves into key developments such as personalized learning platforms, adaptive learning systems, and AI-enhanced teaching tools that leverage machine learning algorithms to tailor educational experiences to individual student needs. Additionally, gamification and immersive learning, along with the integration of blockchain for secure academic credentialing, are discussed as emerging trends in the education technology landscape. The accelerated adoption of remote and blended learning platforms, fueled by the COVID-19 pandemic, is also acknowledged, emphasizing the crucial role AI plays in optimizing online education. The paper addresses the ethical considerations associated with the increasing prevalence of AI in education, focusing on concerns such as data privacy, algorithmic bias, and the responsible and inclusive use of AI systems. The study concludes by emphasizing the dynamic nature of the education technology landscape, suggesting the need for ongoing research and adaptation to ensure that AI continues to enhance the educational experience for students and educators alike.

Global trends and sources of formation of clip thinking in the field of digitalization of educational systems are studied. The key influences are the transition to a new model of the global environment and the expansion of the use of artificial intelligence in educational systems. The topicality of the issue is due to the need for teachers’ prompt response to the growth of the content of educational information, challenges associated with the phenomenon of «clip» thinking, which are a certain obstacle in the competence training of future professionals. It has been established that these and other factors force teachers to change the style, forms, methods and methods of obtaining, accumulating, processing and presenting educational information and to build effective educational practices on this basis. It was found out that information technologies, on the one hand, allow productive management of educational and cognitive activities, but also require appropriate information and technological support. The main characteristics of clip thinking are defined: imagery, increased emotional component of educational and cognitive activity, high speed of perception and superficial processing of information, deficit of attention and its concentration, fragmentation and mosaicism of the picture of the world, loss of desire for knowledge, reduced need and ability for productive activity, etc. the main features of its carriers are highlighted. The results of an empirical study conducted among students of higher education at the Kyiv National University of Construction and Architecture showed that some of them prefer clip-based thinking. The analysis of the literature on the problem of innovative approaches in the training of future professionals made it possible to identify the range of information technology tools in the context of the transformation of "clipping" of thinking. It was concluded that overcoming the cognitive deficit, the dominance of the sphere of abstract and logical thinking is possible under the condition of the appropriate construction of the training organization in the direction of the logical presentation of the educational material, its compliance with practical goals, the introduction of technologies aimed at educational interaction (the use of electronic discussions (forums), electronic mail, conferences, etc.), ensuring an individual approach to the organization of educational and cognitive activities, taking into account the motives, needs and opportunities of higher education seekers, the variability of the selection of IT learning technologies and their combination.

The article is devoted to the formulation of the method of spiral development of values in the implementation of digitalization projects of self-managed organizations, which was developed within the syncretic methodology of project management. The application of the proposed method is considered in the field of infrastructure restoration projects of Ukraine. A scientific problem regarding the availability of a project management methodology that meets modern challenges has been formulated. The gap between the practical needs of project-oriented organizations in a new unique methodology and the availability of established standards for solving typical project management tasks is revealed. A review of literary sources was carried out, modern project management trends were highlighted, including: increasing complexity of modern corporate project management methodologies, application of value-oriented management approaches, models of self-managed teams. The principles of value-oriented management for infrastructure restoration projects implemented by self-managed organizations within the syncretic methodology have been formulated. The method of values spiral development of a project-oriented organization, which uses models of self-management, through the implementation of digitalization projects within the syncretic methodology, is proposed. Within the scope of the method: a value model for digitalization projects of self-managed organizations is proposed; the concept of "stellarator project" is introduced, the definition of such a project is given. The results of the approbation of the method in a project-oriented organization working in the field of infrastructure restoration of Ukraine are presented and analyzed. Areas of improvement of the project-oriented activities of the specified organization have been determined. A SWOT analysis of the proposed method was carried out. Conclusions based on the research are formulated, prospects for further research in the chosen direction are outlined.