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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Mapping research on competency management in the age of AI: a bibliometric and systematic review

Journal of Organizational Effectiveness. 2026. P. 1–26.
Asemota M. O.

Purpose

This study maps how the rapid integration of artificial intelligence (AI) is transforming the definition, development and management of managerial and organizational competencies. It aims to reveal the intellectual structure, thematic evolution and emerging research fronts in competency management in the age of AI.

Design/methodology/approach

This study combines a systematic literature review and bibliometric analysis to map the intellectual structure, thematic evolution and emerging research fronts in competency management in the age of AI. Using the Scopus database, 958 records were initially retrieved. After filtering for peer-reviewed English-language journal articles and manually screening for relevance, a final dataset of 198 articles was analyzed. Bibliometric analyses were conducted using VOSviewer for keyword and co-occurrence mapping and Biblioshiny for publication trends and performance indicators.

Findings

Five overarching themes emerged. (1) Rise of AI-focused managerial skills, (2) AI’s role in augmenting strategic skills and routine skills, (3) dynamic managerial capabilities for AI-enabled HRM, (4) selective skill substitution, augmentation and resilience in the AI era and (5) organizational design, power and well-being implications and competencies. The findings show that competency management is increasingly shifting from static, role-based models toward more dynamic, human-centered and technology-augmented capability systems.

Practical implications

Practitioners should move beyond fixed competency catalogs and adopt flexible, development-oriented competency systems that integrate AI-related skills, augmentation strategies and resilience building. HRM and talent development functions need to design learning pathways and organizational structures that support dynamic capability development and address power, well-being and ethical considerations arising from AI adoption.

Originality/value

This study integrates systematic review and bibliometric mapping to provide an integrated overview of how competency management is being redefined under AI-enabled conditions, synthesizing fragmented literature into five clear thematic fronts and offering directions for future research.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: bibliometric analysisworkforce developmentHR analyticsArtificial IntelligenceArtificial intelligence; Generative AI; LLM; HR-automationSLR methodologyDigital TransformationCompetency Management
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