DOI: 10.17587/prin.17.404-412
Forecasting IT Skill Demand in the East African Labor Market: A BERT-Based Analytical Framework
R. Ndungi, Student, rebeccahndungi94@gmail.com,
I. S. Blekanov, Cand. Sc. (Eng.), Associate Professor, Head of the Department, i.blekanov@spbu.ru,
St. Petersburg State University, 199034, Russian Federation
Corresponding author: Rebeccah Ndungi, Student, Faculty of Mathematics and Computer Science, St. Petersburg State University, Saint Petersburg, 199034, Russian Federation, E-mail: rebeccahndungi94@gmail.com
Received on February 20, 2026
Accepted on March 31, 2026
This research addresses the critical misalignment between IT skill supply and demand in East Africa by proposing a novel forecasting framework based on a Bidirectional Encoder Representations from Transformers (BERT) model. Existing labor market information systems often provide retrospective analyses, leaving policymakers and educators without the foresight needed to adapt curricula and training programs proactively. To bridge this gap, this research develops and validates a predictive analytics framework designed to forecast IT skill demand. The methodology applies a contextually fine-tuned BERT model to perform semantic analysis on unstructured data from regional job markets. This enables the precise extraction and categorization of IT competencies from natural language text. The framework is designed to generate predictive insights into future skill requirements. The goal is to provide timely, data-driven intelligence to directly inform education policy, curriculum development, and targeted upskilling initiatives, thereby supporting a more responsive digital workforce in the region. The forecast findings show Excel with a 0.05x multiplier growth (slow growth, though current demand is high), while Java and JavaScript have higher demand. The jobs distribution charts show web development at 43 % and Cloud/DevOps at 41 %. By generating granular, forward-looking intelligence, this framework equips educational institutions, training providers, and government bodies with the evidence base required to align skill development with the trajectory of the digital economy, fostering a more responsive and competitive workforce in the region.
Keywords: Skills Forecasting, BERT Model, Digital Workforce, Labor Market Analysis, East Africa
pp. 404—412
For citation:
Ndungi R., Blekanov I. S. Forecasting IT Skill Demand in the East African Labor Market: A BERT-Based Analytical Framework, Programmnaya Ingeneria, 2026, vol. 17, no. 7, pp. 404—412. DOI: 10.17587/prin.17.404-412.
References:
- Shariff K., Mlay D. F., Owino S. O. Generating Evidence from Life Skills Assessments to Inform Policy in East Africa, Enabling Power of Assessment, 2024, vol. 11, pp. 17—30. DOI: 10.1007/978-3-031-51490-6_2.
- Maroko A., Ndivo G. M., Maroko L. M. Youth Employabil-ity: Fostering University-Industry Links in Syllabus Design, East African Journal of Education Studies, 2021, vol. 3, no. 1, pp. 172—184. DOI: 10.37284/eajes.3.1.360.
- Atwine B., Okumu I. M., Nnyanzi J. B. What drives the dynamics of employment growth in firms? Evidence from East Africa, Journal of Innovation and Entrepreneurship, 2023, vol. 12, article 33. DOI: 10.1186/s13731-023-00295-y.
- Osumbah B. A., Wekesa P. Development in technical and vocational education and training: Synopsis and implications of education policies for right skills in Kenya, Educational Research and Reviews, 2023, vol. 18 (8), pp. 181—193. DOI: 10.5897/err2023.4328.
- Barigye D. Technical Vocational Education and Training in Uganda: Career guidance and practices, African Journal of Career Development, 2024, vol. 6, no. 1, article a100. DOI: 10.4102/ajcd.v6i1.100.
- de Jongh J. J. J., Mncayi-Makhanya P., Mdluli-Maziya P. Antecedents of youths who are not in employment, education or training: Micro-level evidence, Journal of Economic and Financial Sciences, 2024, vol. 17, no. 1, article a899. DOI: 10.4102/jef.v17i1.899.
- Khakina P. N. Solving Unemployment in Kenya by Integrating Education, Training and Market, International Journal of Research and Innovation in Social Science, 2024, no. VIII (IIIS), pp. 3331—3337. DOI: 10.47772/ijriss.2024.803239s.
- Siringi E. Putting Skills First: Analysis of Kenyan Universities' Preparedness in Shaping Graduates Skills Knowledge for Employability [Internet], SSRN Electronic Journal, 2025 Apr. 24. DOI: 10.2139/ssrn.5228458.
- Elnahrawi N. The Role of Digital Transformation in Africa's Regional Integration, SSRN Electronic Journal, 2022 Dec. 1. DOI: 10.2139/SSRN.4595317.
- Republic of Kenya. Kenya Vision 2030: A Globally Competitive and Prosperous Kenya. Nairobi: Government of the Republic of Kenya, Ministry of Planning and National Development and the National Economic and Social Council (NESC), Office of the President, 2007, 136 p.
- Bhattarai P. C., Parajuli M. N., Gautam S. et al. Education—work transition: skill gaps in the construction industry, Front Built Environ, 2025, vol. 11, article 1623609. DOI: 10.3389/fbuil.2025.1623609.
- Kinyondo A. A., Shija H., Kinyondo A. A., Shija H. Perspective Chapter: Youth Skills and Unemployment — Perceived Inadequate Soft Skills and Coping Strategies of Employers in Tanzania, Unemployment—Nature, Challenges and Policy Responses, 2023. Dec 11. DOI: 10.5772/intechopen.1003645.
- Oliver E., Oliver W., Bonvillian W. B. et al. Global Initiatives and Higher Education in the Fourth Industrial Revolution. UJ Press. 2022 Aug. 11. DOI: 10.36615/9781776405619.
- Muchiri D. G. Skilling, reskilling, and upskilling a work-force: a perspective from kenyan enterprises, Strategic Journal of Business & Change Management, 2022, vol. 9, no. 4, pp. 190—203. DOI: 10.61426/sjbcm.v9i4.2368.
- Onsomu E., Munga B., Nyabaro V. et al. Assessment of Youth Employment Policies and Their Impacts in Kenya, Youth Employment Programmes in Africa, 2025, Jan. 1, pp. 63—86. DOI: 10.4324/9781003589501-4.
- Qin C., Zhang L., Cheng Y. et al. A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics, Proceedings of the IEEE, 2025, vol. 113, no. 2, pp. 125—171. DOI: 10.1109/JPROC.2025.3572744.
- Yu R., Das S., Gurajada S. et al. A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques, Proceedings of the 1st Workshop on NLP for Positive Impact, Online: Association for Computational Linguistics, 2021, Aug., pp. 100—106. DOI: 10.18653/v1/2021.nlp4posimpact-1.11.
- Kabir M. A., Abdelfatah K., He S. et al. Forecasting Application Counts in Talent Acquisition Platforms: Harnessing Multimodal Signals using LMs, arXiv, 2024. DOI: 10.48550/arXiv.2411.15182.
- Ong X. Q., Hui Lim K. SkillRec: A Data-Driven Approach to Job Skill Recommendation for Career Insights. 2023 15th International Conference on Computer and Automation Engineering, ICCAE 2023, Sydney, Australia, 2023, pp. 40—44. DOI: 10.1109/ICCAE56788.2023.10111438.
- Nurfaizah R. J., Ahsan M., Lee M. H. A hybrid approach to hospital quality monitoring based on google maps reviews: Integrating p-control charts and bidirectional encoder representations from transformers (BERT). International Journal of Data and Network Science, 2025, vol. 9, no. 4, pp. 1081—1106. DOI: 10.5267/j.ijdns.2024.9.012.
- Lu K., Wang Z., Mardziel P., Datta A. Influence Patterns for Explaining Information Flow in BERT, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021 (NeurIPS 2021), Virtual: Curran Associates, 2021 Dec 6-14, pp. 4461-4474. DOI: 10.48550/arXiv.2011.00740.
- Uto M., Aramaki K. Linking essay-writing tests using many-facet models and neural automated essay scoring, Behavior Research Methods, 2024, vol. 56, no. 8, pp. 8450—8479. DOI: 10.3758/s13428-024-02485-2.