Olga Akimova, Associate Professor at the Lomonosov MSU Business School, has co-authored the chapter “Generative AI Literacy of University Faculty Members in Russia,” included in the international academic monograph “Data-Driven Monetization Strategies for Economic Insights”, published by IGI Global. The publication is indexed in the Scopus international database.
The study was conducted in collaboration with colleagues from St. Petersburg State University and St. Petersburg State University of Industrial Technologies and Design.
The proposed methodology is based on three complementary approaches. The TPACK (Technological Pedagogical Content Knowledge) framework examines the integration of technology through three components: subject expertise, pedagogical knowledge, and proficiency in generative AI tools. The Theory of Planned Behavior (TPB) adds a motivational dimension to technical skills — attitudes toward AI, social norms, and self-reliance, which are critical for the real-world adoption of technology. Finally, the Jobs to Be Done (JTBD) approach shifts the focus from abstract competencies to specific professional tasks: rather than asking whether a university instructor or lecturer ‘knows how to use AI,’ it considers ‘which tasks they accomplish using AI’ — from lecture preparation to peer review.
Based on the analysis of individual faculty development plans at leading Russian universities and job postings on hh.ru, leading online recruitment platform in Russia, the researchers identified 24 key tasks, grouped into six areas of professional activity: teaching, research, organizational and methodological work, curriculum development, consulting and expert services.
For each task, the authors introduce a structured scale for assessing digital literacy, enabling a systematic evaluation of faculty members’ actual proficiency in generative AI.
According to the author’s estimates, improving AI literacy among faculty could increase labor productivity by 29.92%. For the Russian higher education system (approximately 211,000 faculty members), this would translate into annual savings of around 9 billion rubles.
“AI literacy among faculty is not just a technical skill, but a strategic asset. By freeing educators from routine tasks, generative AI allows them to focus on personalized student support, mentorship, and the development of innovative educational solutions. This also creates a multiplier effect for the economy: graduates taught by faculty proficient in generative AI tools are themselves better equipped to implement innovations without fear of new technologies,” notes Olga Akimova.
We congratulate Olga Akimova on this significant academic achievement and wish her continued success in both research and teaching.
The full study is available on the publisher’s website:
