Abstract: The rapid diffusion of generative artificial intelligence (AI) has intensified debate over whether productivity gains can coexist with weaker labor demand at the beginning of occupational career ladders. This study examines the mechanisms through which AI-assisted productivity may reduce entry-level hiring while leaving aggregate employment comparatively stable. The analysis synthesizes recent evidence from the United States, Europe, and Russia, with particular attention to task exposure, vacancy dynamics, age-specific employment outcomes, experience requirements, and changes in the market value of AI skills. The findings indicate that the earliest labor-market adjustment often occurs through hiring flows rather than immediate job destruction. Standardized digital tasks performed by junior workers are especially exposed to compression when incumbent employees can produce more output with AI assistance. At the same time, the evidence does not support a uniform decline in employment across AI-exposed occupations. The resulting effect is better characterized as a selective entry-level squeeze shaped by task composition, demand elasticity, firm strategy, and the complementarity between human judgment and AI tools.

Abstract: U.S. healthcare insurance organizations work with financial indicators that shape pricing, utilization management, sales governance, resource allocation, reserve review, and executive oversight. The article examines how health plans convert financial data into operational insight through cross-functional communication among finance, actuarial, operations, sales, compliance, provider network, and executive teams. The research aim is to develop a Review+ analytical model that explains how medical loss ratio, administrative expense ratio, per member per month cost, incurred but not reported reserves, commissions, and gross margin gain managerial value inside reporting routines. The study draws on recent peer-reviewed literature and selected public industry reports. Comparative analysis, source analysis, conceptual synthesis, typologization, and analytical generalization were applied. The results identify three translation mechanisms: metric-to-driver interpretation, dashboard-based sensemaking, and governance-linked reporting. The proposed model supports executive dashboards, scorecards, scenario reports, pricing discussion, resource allocation, and board-level communication in healthcare insurance organizations.

Abstract: Artificial intelligence changes product-team decision making by moving AI from an auxiliary tool into discovery, prioritization, prototyping, release review, and post-launch monitoring. The article examines how product teams shift from a linear hypothesis, build, and measure cycle to adaptive loops that connect model outputs, user signals, exception handling, and human judgment. The purpose is to clarify how teams allocate decision authority between AI-supported routine execution and human arbitration in ambiguous or high-consequence cases. The author applies source analysis, comparative interpretation, conceptual synthesis, typologization, and analytical generalization. The source base covers recent research on product management, requirements engineering, generative-AI delegation, human-AI interaction, responsible AI, and institutional governance standards. The results identify decision-boundary design, feedback quality, data instrumentation, and model-behavior monitoring as central conditions for AI-augmented product work. The findings offer a practical logic for teams that need faster execution without losing accountability, traceability, and control over product consequences.

Abstract: The relevance of the study is determined by the gap between the widespread adoption of analytical technologies and their sustainable integration into managerial decision-making and execution processes. The study aims to develop a methodological framework for integrating analytical models into digital management loops and to substantiate the organizational conditions required for their effective use. Integration is shown to emerge when data, a model, a decision rule, an action, and an observable outcome form a closed feedback loop. The study distinguishes analytical availability from loop integration and proposes dual accountability for model performance and managerial action, together with an observability criterion for the management loop. The findings can support the design, audit, and scaling of analytical solutions across functional and cross-functional organizational processes.

Abstract: The economics of retail payment acceptance has become increasingly important as European merchants face rising card-acceptance charges, unequal bargaining power, and continued dependence on international card networks. This study evaluates the merchant-side economic implications of the digital euro, with emphasis on payment costs, acquiring arrangements, market concentration, and the distribution of bargaining power between merchants and payment service providers. The analysis combines recent European Central Bank and European Commission evidence with the economics of two-sided payment markets. The results show that average net merchant service charges in the European Union increased from 0.27% in 2018 to 0.44% in 2022, while small merchants may pay three to four times more for card acceptance than large retailers. International schemes account for a majority of euro-area card transactions, limiting the credibility of switching for many merchants. The proposed digital-euro compensation model could reduce merchant costs through capped charges and the absence of private scheme and processing fees. Its realized effect, however, will depend on consumer adoption, payment-service-provider pass-through, integration costs, and competitive responses from incumbent card networks.

Abstract: This article examines approaches to innovative management in international schools operating in emerging markets under conditions of digital transformation, increasing demands for educational quality, and the necessity to adapt global educational models to local environments. The study is conducted in the form of a structured analytical review and conceptual synthesis of scientific publications devoted to digital leadership, distributed governance, teacher participation in decision-making, open innovation, and organizational resilience in educational institutions. Particular attention is paid to the tension between global educational standardization and local institutional adaptation, as well as to the limitations of directly transferring Western management models into the conditions of emerging markets in East Africa. It is established that the sustainable development of an international school is determined not by the scale of digital technology implementation, but by the ability of the management system to coordinate organizational, pedagogical, and technological changes within a unified institutional model. An original model of innovative management for international schools is proposed, based on the integration of distributed governance, digital leadership, knowledge management, the use of external knowledge sources, and local adaptation of the educational system. The obtained results make it possible to consider the institutional resilience of an international school as a function of the coherence of managerial mechanisms, the level of organizational adaptation, and the school’s ability to maintain a balance between global competitiveness and local legitimacy. The article may be of interest to researchers in educational management, digital transformation, and institutional development of educational organizations, as well as to administrators of international schools in emerging markets.

Abstract: The article examines the management of corporate AI projects during the transition from pilot implementation to a scalable business result. The main barriers to production deployment are identified, including poor data preparation, the absence of measurable business metrics, employee resistance, unrealistic expectations, and insufficient management control. A staged model is proposed that covers business problem identification, hypothesis formulation, readiness assessment, piloting, integration, and scaling. A system for assessing the technical, operational, economic, organisational, and integration readiness of an AI project is developed. The need to consider total cost of ownership, user adoption, and project risks is substantiated. The proposed approach supports decisions on scaling, repeated piloting, adjustment, or termination of an AI project.

Abstract: The renewed use of broad import tariffs in 2025-2026 has revived the question of who ultimately bears trade-policy costs along cross-border supply chains. The study examines the allocation of tariff burdens among foreign suppliers, importers, distributors, retailers, and final consumers, distinguishing border incidence from downstream price pass-through and treating margin compression as a separate adjustment channel. Evidence from the recent U.S. tariff episode and supporting empirical studies shows that foreign exporters absorbed only a small share of the initial shock: average border pass-through approached 0.95, while U.S. importers bore roughly 86-94% of tariff incidence across different periods of 2025. Consumer pass-through was slower and incomplete because inventories, contractual repricing, demand elasticity, sourcing changes, and retailer pricing strategies delayed transmission. The results indicate that tariff incidence evolves over time rather than being fixed at the border. Domestic firms may temporarily absorb costs through lower margins, reduced promotions, supplier renegotiation, and product-mix adjustments before a larger share reaches final prices. The findings support a chain-wide approach to tariff analysis based on prices, margins, quantities, and sourcing responses.

Abstract: Procurement of production services in narrow business-to-business niches involves several specialists who assess 1 supplier against criteria derived from their functional tasks. Each of them reaches the supplier website with a separate question, and the composition of those questions determines what the digital environment must contain. This review organizes existing research through the framework of theory, context, characteristics, and methodology, and it reconstructs the correspondence between the composition of roles in a purchase and the requirements placed on landing digital infrastructure. 4 roles characteristic of film production are examined: the production designer, the site manager, the technical director, and the producer. The analysis distributes their requirements across 3 stages of the purchase process, identifies points where requirements compete for the same screen space, and separates the landing logic for a catalog product from that for an infrastructure facility. A props-rental case drawn from the author's practice illustrates the reconstruction. 5 propositions formulated for later testing define a program of empirical verification. Results address owners of production service firms and specialists who design search campaigns for narrow industrial segments.

Abstract: The rapid turnover of graphics processing unit (GPU) architectures has created a mismatch between accounting depreciation schedules and the economic life of artificial intelligence (AI) computing assets. This study develops a capital-budgeting framework for GPU infrastructure under accelerated technological obsolescence and examines when sovereign cloud (SC) deployment can be economically justified in regulated industries. The analysis integrates net present value (NPV), utilization, residual-value uncertainty, architecture-driven value decay, staged procurement, switching costs, vendor concentration, compliance expenditure, and geopolitical risk. The results show that fixed useful-life assumptions can overstate the continuation value of GPU fleets when performance per watt and workload economics change faster than accounting schedules. Investment decisions are more robust when economic life is modeled by workload class and procurement is treated as a sequence of partially reversible commitments. SC is economically defensible for critical workloads when its incremental present cost is lower than the probability-weighted value of avoided regulatory, concentration, switching, and geopolitical losses. The proposed framework can support investment committees, infrastructure planning, and technology-risk governance.