Модель адаптивної реконфігурації портфеля проєктів у BANI-середовищі

The contemporary business landscape has undergone fundamental changes towards the BANI paradigm (Brittle, Anxious, Non-linear, Incomprehensible), rendering traditional deterministic approaches to Project Portfolio Management (PPM) largely ineffective. Static planning methods fail to account for the stochastic nature of modern threats, leading to organizational fragility and resource misalignment. This study addresses this problem by developing a comprehensive mechanism for adaptive management based on integrating Artificial Intelligence technologies with strategic management principles to create a dynamic, self-regulating system capable of functioning in high-entropy environments. The primary result of the research is the developed Model of Adaptive Project Portfolio Reconfiguration in a BANI Environment (Intelligent Dynamic Portfolio Reconfiguration Model, IDPR-Model). The developed system consists of four interconnected models, each designed to counteract a specific BANI component. The Semantic Monitoring Model utilizes Natural Language Processing (NLP) algorithms to detect «weak signals» from unstructured external data, overcoming the challenge of «Incomprehensibility». The Predictive Model applies «Digital Twin» technology and Monte Carlo simulations to model probabilistic future scenarios, mitigating «Non-linearity» and «Brittleness». The Decision Model acts as an orchestration mechanism, using multi-objective optimization algorithms to propose reconfiguration strategies (such as freezing or accelerating assets), while retaining the human role for strategic and ethical verification. The Execution and Communication Model focuses on reducing organizational «Anxiety» through proactive communication mechanisms and Zero Trust security protocols. The proposed model provides significant methodological progress by shifting the managerial paradigm from «planning for stability» to «managing for resilience». It is substantiated that the synergy of AI-based predictive analytics with human strategic oversight will allow organizational management to minimize decision latency and dynamically optimize resource usage. The implementation of the developed model provides a reliable toolkit for enterprise managers to ensure long-term viability and competitive advantages in an unpredictable global environment.