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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Mapping the research on artificial intelligence in corporate learning: a bibliometric analysis

Learning Organization. 2026. Vol. 33. No. 5. P. 730–752.
Asemota M. O.

Purpose – This research aims to synthesize the current literature on the application and impact of artificial
intelligence (AI) in corporate learning. It explores the historical foundations, common theories and key themes
surrounding AI’s integration into corporate learning practices across all major sectors.
Design/methodology/approach – A systematic literature review was conducted using bibliometric analysis
via VOSviewer software. A comprehensive search of the Scopus database yielded 45 peer-reviewed journal
articles, analyzed through keyword text analysis, keyword co-occurrence, bibliographic coupling and cocitation
techniques. Findings were synthesized narratively, with subgroup analyses by themes and historical evolution.
Findings – The analysis identifies AI’s strategic role in corporate learning, its increasing use in gamification,
its function as a driver of workforce transformation, growing stakeholder concerns and its ongoing
contributions to employee engagement. These trends highlight AI’s holistic transformation of organizational
learning and development.
Originality/value – To the best of the author’s knowledge, this study offers the first comprehensive
bibliometric analysis of AI in corporate learning, spanning all sectors for greater generalizability. It delivers
novel insights into research trends, influential contributors and emerging thematic clusters, advancing
understanding in this evolving field.

Research target: Education Economics and Management
Language: English
Full text
DOI
Text on another site
Keywords: corporate learningbibliometric analysisartificial intelligencesystematic literature review
Publication based on the results of:
National innovation system 2.0: involving key actors in transformation processes (2025)
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