A Systematic Review of Factors Influencing the Adoption of Artificial Intelligence for Training and Development in the Nigerian Banking Sector DOI: https://doi.org/10.33093/ijomfa.2026.7.2.1
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Abstract
Artificial intelligence (AI) is revolutionising human resource management through automation, data-driven decisions, personalised learning, and improved skills-gap detection. Nevertheless, AI adoption in training and development (T&D) programs in the Nigerian banking sector remains low. Therefore, this situation has become a barrier to the development of human capital and to digital transformation. This systematic literature review aims to identify the factors influencing AI adoption in T&D within Nigerian banks and then to analyse the interrelationship among the constructs. This review also examines the mediating role of T&D-AI Fit between influencing factors and AI adoption in T&D. The study uses the Task–Technology Fit (TTF) model as the theoretical framework. Using the PRISMA 2020 guidelines, 46 peer-reviewed studies published between 2018 and 2025 were identified from multiple databases and analysed using thematic synthesis. The review Key enablers include training needs assessment, training design quality, AI system attributes (usability, reliability, personalisation), and individual factors (employee attitudes and digital competency). The major barriers are inadequate infrastructure, resistance to organisational change, fears of job displacement, and regulatory uncertainty. In addition, the T&D-AI fit was shown to mediate the relationship between these factors and successful AI adoption. Achieving strong task–technology alignment (T&D–AI fit) is critical for overcoming contextual barriers and maximising AI benefits in resource-constrained banking environments. This review highlights practical implications for digital skill-building, infrastructure improvement, and ethical AI governance while extending the TTF model to emerging economies.
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Abdulquadri, A., Mogaji, E., Kieu, T. A., & Nguyen, N. P. (2021). Digital transformation in financial services provision: a Nigerian perspective to the adoption of chatbot. Journal of Enterprising Communities: People and Places in the Global Economy, 15(2), 258–281. https://doi.org/10.1108/jec-06-2020-0126
Adeniwura, O. O., Toriola, A. K., Sokunbi, G. M., & Ndubueze, D. O. (2025). Comparative analysis of the importance of artificial intelligence in addressing skill gaps in commercial banks in Nigeria and United Kingdom. Proceedings of the Faculty of Economics in East Sarajevo, (31), 113–126. https://doi.org/10.7251/ZREFIS2531113A
Adeyemo, K., & Obafemi, F. J. (2024). A survey on the role of technological innovation in nigerian deposit money bank fraud prevention. South Asian Journal of Social Studies and Economics, 21(3), 133–150. https://doi.org/10.9734/sajsse/2024/v21i3790
Al Dari, T., Jabeen, F., Hussain, M., & Al Khawaja, D. (2020). How types of organizational culture and technological capabilities contribute to organizational learning. Management Research Review, 44(3), 437–459. https://doi.org/10.1108/mrr-02-2020-0090
Alhusban, M. I., Khatatbeh, I. N., & Alshurafat, H. (2025). Exploring the influence, implications and challenges of integrating generative artificial intelligence into organizational learning and development. Competitiveness Review: An International Business Journal. https://doi.org/10.1108/cr-06-2024-0121
Amankwah-Amoah, J., & Lu, Y. (2022). Harnessing AI for business development: A review of drivers and challenges in africa. Production Planning & Control, 35(13), 1–10. https://doi.org/10.1080/09537287.2022.2069049
An, M., Lin, J., & Luo, X. R. (2024). The impact of human AI skills on organizational innovation: The moderating role of digital organizational culture. Journal of Business Research, 182, 114786. https://doi.org/10.1016/j.jbusres.2024.114786
Amankwah-Amoah, J., & Lu, Y. (2022). Harnessing AI for business development: A review of drivers and challenges in africa. Production Planning & Control, 35(13), 1–10. https://doi.org/10.1080/09537287.2022.2069049
An, M., Lin, J., & Luo, X. R. (2024). The impact of human AI skills on organizational innovation: The moderating role of digital organizational culture. Journal of Business Research, 182, 114786. https://doi.org/10.1016/j.jbusres.2024.114786
Arora, M., & Mittal, A. (2024). Employees’ change in perception when artificial intelligence integrates with human resource management: a mediating role of AI-tech trust. Benchmarking. https://doi.org/10.1108/bij-11-2023-0795
Awotunde, O. M., & Aregbeshola, A. R. (2024). Navigating the future workplace: intrapreneurship training and development for enhanced performance and organizational productivity. International Journal of Research in Business and Social Science (2147- 4478), 13(2), 127–136. https://doi.org/10.20525/ijrbs.v13i2.3016
Abed Alkarim Ayyoub, Abu Eidah, B.A., Khlaif, Z. N., EL-Shamali, M.A. & Sulaiman, M. (2023). Understanding online assessment continuance intention and individual performance by integrating task technology fit and expectancy confirmation theory. Heliyon, 9(11), e22068–e22068. https://doi.org/10.1016/j.heliyon.2023.e22068
Aziz, N., Lee, L. E. Y., Ahmed, N. K., Aziz, A., Rizwan, S. H., & Shah, S. M. H. (2025). Generative artificial intelligence and its role in shaping customer loyalty in banking: a conceptual framework. International Journal of Management, Finance and Accounting, 6(2), 375–405. https://doi.org/10.33093/ijomfa.2025.6.2.13
Balogun, F. (2026, January 9). AI could boost Africa’s economy by $1trn by 2035 - AfDB - Businessday NG. Businessday NG. https://businessday.ng/technology/article/ai-could-boost-africas-economy-by-1trn-by-2035-afdb/
Bagherifam, N., Naghdi, S., Ahmadian, V., Fazlzadeh, A., & Baghalzadeh Shishehgarkhaneh, M. (2025). Digital regulatory governance: the role of RegTech and SupTech in transforming financial oversight and administrative capacity. International Journal of Financial Studies, 13(4), 217. https://doi.org/10.3390/ijfs13040217
Bedué, P., & Fritzsche, A. (2021). Can we trust AI? an empirical investigation of trust requirements and guide to successful AI adoption. Journal of Enterprise Information Management, 35(2), 530–549. https://doi.org/10.1108/jeim-06-2020-0233
Bello, O., & Ajao, A. O. (2024, August 31). Digital Literacy and skills development in Nigeria: policies, barriers and recommendations. https://africanscholarpub.com/ajaias/article/view/262
Bhatt, P., & Muduli, A. (2022). Artificial intelligence in learning and development: a systematic literature review. European Journal of Training and Development, 47(7/8), 677–694. https://doi.org/10.1108/ejtd-09-2021-0143
Binsaeed, R. H., Yousaf, Z., Grigorescu, A., Samoila, A., Razvan Ion Chitescu, & Nassani, A. A. (2023). Knowledge sharing key issue for digital technology and artificial intelligence adoption. Systems, 11(7), 316–316. https://doi.org/10.3390/systems11070316
Boonmee, C., Mangkalakeeree, J., & Jeong, Y. (2025). Towards sustainable digital transformation: AI adoption barriers and enablers among SMEs in Northern Thailand. Sustainable Futures, 10, 101169. https://doi.org/10.1016/j.sftr.2025.101169
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022). Artificial intelligence – challenges and opportunities for international hrm: a review and research agenda. The International Journal of Human Resource Management, 33(6), 1065–1097. https://www.tandfonline.com/doi/full/10.1080/09585192.2022.2035161
Chitranshi, J., Chopra, K., & Banerjee, P. (2024). Impact of artificial intelligence in transforming and replacing traditional learning and development of employees. Foresight. https://doi.org/10.1108/fs-05-2024-0109
Choi, H.J., & Park, J. H. (2024). Research trends in learning needs assessment: a review of publications in selected journals from 1997 to 2023. Sustainability, 16(1), 382. https://doi.org/10.3390/su16010382
Cotes, J., & Ugarte, S. M. (2019). A systemic and strategic approach for training needs analysis for the International Bank. Journal of Business Research, 127. https://doi.org/10.1016/j.jbusres.2019.05.002
Davis, F. D. (1989). Perceived usefulness, Perceived Ease of use, and user acceptance of information technology. Journal of Risk and Uncertainty, 18(3), 321–325. https://doi.org/10.1023/a:1011156710779
Deep, G. (2023). Digital transformation’s impact on organizational culture. International Journal of Science and Research Archive, 10(2), 396–401. https://doi.org/10.30574/ijsra.2023.10.2.0977
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & Management, 36(1), 9–21. https://doi.org/10.1016/s0378-7206(98)00101-3
Dulloo, R. (2024). The AI revolution in hr: mapping automation, skills, and emerging roles in the evolving human resources landscape. Journal of Computational Analysis & Applications, 33(2).
Elmunsyah, H., Nafalski, A., Wibawa, A. P., & Dwiyanto, F. A. (2023). Understanding the impact of a learning management system using a novel modified delone and McLean model. Education Sciences, 13(3), 235. https://doi.org/10.3390/educsci13030235
Emily Jones, M. (2020). LibGuides: Creating a PRISMA flow diagram: PRISMA 2020. Guides.lib.unc.edu. https://guides.lib.unc.edu/prisma#s-lg-box-28341586
Faisal-E-Alam, M. (2024). Effect of training programs on trainees’ learning. Bangladesh Journal of Multidisciplinary Scientific Research, 9(1), 25-31.
Frenkenberg, A. & Hochman, G. (2025). It’s scary to use it, it’s scary to refuse it: the psychological dimensions of ai adoption—anxiety, motives, and dependency. Systems, 13(2), 82–82. https://doi.org/10.3390/systems13020082
Gkinko, L., & Elbanna, A. (2023). Designing trust: The formation of employees’ trust in conversational AI in the digital workplace. Journal of Business Research, 158, 113707. https://doi.org/10.1016/j.jbusres.2023.113707
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236. https://doi.org/10.2307/249689
Hidayat, D., Pangaribuan, C. H., Putra, O. P. B., & Irawan, I. (2021, August). Contemporary studies of task-technology fit: a review of the literature. In 2021 International Conference on Information Management and Technology (ICIMTech) (Vol. 1, pp. 309-313). IEEE.
Ismail, M. N., Jameel, S. H., Al-Zeyadi, B. K. A., Saeed, A. M., Salman, S. M., Dakov, S., & Ali, H. (2024, October). Investigating three digital transformation theories TAM, TTF, and UTAUT. In 2024 36th Conference of Open Innovations Association (FRUCT) (pp. 538-548). IEEE.
Jamal, A. F., Nemar, S. E., & Sakka, G. (2024). The relationship between job redesigning, reskilling and upskilling on organizational agility. Euromed Journal of Business. https://doi.org/10.1108/emjb-10-2023-0279
Joseph, J. P., & Ravikumar T. (2024). Relationship between digital leadership and organizational culture: role of digital literacy. International Research Journal of Multidisciplinary Scope, 05(02), 493–500. https://doi.org/10.47857/irjms.2024.v05i02.0551
Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetisensoy, O., & Demir Kaya, M. (2022). The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial intelligence. International Journal of Human–Computer Interaction, 40(2), 497–514. https://doi.org/10.1080/10447318.2022.2151730
Khan, M., Rahman, W., & Khan, S. A. (2021). Training needs assessment, trainees' work passion and training effectiveness in government training institutes of khyber pakhtunkhwa. City University Research Journal, 11(2), 267-288. https://www.proquest.com/scholarly-journals/training-needs-assessment-trainees-work-passion/docview/2579143503/se-2
Lampropoulos, G., & Sidiropoulos, A. (2024). Impact of gamification on students’ learning outcomes and academic performance: a longitudinal study comparing online, traditional, and gamified learning. Education Sciences (Basel), 14(4), 367–367. https://doi.org/10.3390/educsci14040367
López-Rodríguez, C. E., Sandoval-Escobar, M., & Maldonado, J. A. S. (2024). Resistance to technological innovation and brand equity in the banking sector. Management & Marketing, 19(1), 93-112. https://doi.org/10.2478/mmcks-2024-0006
Madanchian, M., & Taherdoost, H. (2025). Barriers and Enablers of AI Adoption in Human Resource Management: A Critical Analysis of Organizational and Technological Factors. Information, 16(1), 51–51. https://doi.org/10.3390/info16010051
Mahmud, K. T., Saira Wahid, I., Arif, I., & Belso-Martinez, J. (2019). Impact of training needs assessment on the performance of employees: Evidence from Bangladesh. Cogent Social Sciences, 5(1). tandfonline. https://doi.org/10.1080/23311886.2019.1705627
Maity, S. (2019). Identifying opportunities for artificial intelligence in the evolution of training and development practices. The Journal of Management Development, 38(8), 651–663. https://doi.org/10.1108/JMD-03-2019-0069
Marocco, S., Bellini, D., Barbieri, B., Presaghi, F., Grossi, E., & Talamo, A. (2025). Attitudes toward artificial intelligence in organizational contexts. AI, 6(11), 292. https://doi.org/10.3390/ai6110292
Melkamu, M. (2025). Artificial intelligence implementation challenges in industries: developing countries prospective. 02(01), 175–180. https://doi.org/10.61552/JAI.2025.01.004
Murire, O. T. (2024). Artificial intelligence and its role in shaping organizational work practices and culture. Administrative Sciences, 14(12), 316. https://doi.org/10.3390/admsci14120316
Nair, V. K., Jain, C., Tibrewal, P., Sudhir, L., & Prasad, M. (2025, August). Barriers to Artificial intelligence adoption among banking professionals: a total interpretive structural modelling approach. In 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS) (pp. 1-7). IEEE.
Ni, Z., Xiao, B., & Li, Y. (2025). Data-driven business process evaluation in commercial banks: multi-dimensional framework with hybrid analytical approaches. Systems, 13(4), 256. https://doi.org/10.3390/systems13040256
Nigeria Inter-Bank Settlement System Plc. (2015). Annual Report 2023. Nibss-Plc.com.ng. https://nibss-plc.com.ng/
Nor, A. I. (2025). The role of training needs analysis in training effectiveness in public sector organizations. Multidisciplinary Reviews, 9(3), 2026149. https://doi.org/10.31893/multirev.2026149
Odebode, A. A., & Ogunbayo, O. T. (2025). The potential of digital-based technology in improving organizational performance. Journal of Management Development, 44(1), 96–106. https://doi.org/10.1108/jmd-04-2024-0145
Odufisan, O. I., Abhulimen, O. V., & Ogunti, E. Olarenwaju. (2025). Harnessing artificial intelligence and machine learning for fraud detection and prevention in Nigeria. Journal of Economic Criminology, 7(1), 100127. https://doi.org/10.1016/j.jeconc.2025.100127
Ogundele, A. T., Ibitoye, O. A., Akinterinwa, O. O., Adeniran, A., Ibukun, F. O., & Apata, T. G. (2025). The role of artificial intelligence in advancing sustainable banking and service efficiency in nigerian financial institutions: An assessment of selected quoted banks. Journal of Sustainable Development Law and Policy (The), 16(1), 282-307.
Ohiani, A. S. (2020). Technology innovation in the nigerian banking system: prospects and challenges. Rajagiri Management Journal, 15(1). https://doi.org/10.1108/ramj-05-2020-0018
Okoro, G. O. (2024). Digital human resource practices and employee development in nigerian banking sector. BW Academic Journal, 16-16.
Omotayo, F. O., & Haliru, A. (2020). Perception of task-technology fit of digital library among undergraduates in selected universities in Nigeria. The Journal of Academic Librarianship, 46(1), 102097. https://doi.org/10.1016/j.acalib.2019.102097
Ononiwu, M. I., Onwuzulike, O. C., Shitu, K., & Ojo, O. O. (2024). The impact of digital transformation on banking operations in developing economies. World Journal of Advanced Research and Reviews, 23(3), 460–474. https://doi.org/10.30574/wjarr.2024.23.3.2706
Page, M., Tetzlaff, J., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Value in Health, 23(10), S312–S313. https://doi.org/10.1016/j.jval.2020.04.1154
Panda, G., Dash, M. K., Samadhiya, A., Kumar, A., & Mulat-Weldemeskel, E. (2024). Artificial intelligence as an enabler for achieving human resource resiliency: past literature, present debate and future research directions. International journal of industrial engineering and operations management, 6(4), 326-347. https://doi.org/10.1108/ijieom-05-2023-0047
Patre, S., Chakraborty, D., Kar, A. K., Singu, H. B., & Tiwari, D. A. (2023). The role of enablers and barriers in the upskilling and reskilling of users through professional skilling programs on EdTech platforms. IEEE Transactions on Engineering Management, 71, 9839-9853.
Rahman, F. H., Putranto & N. A. R. (2024). Designing effective training to enhance performance of branch managers in bank XYZ at Jakarta Region. International Journal of Current Science Research and Review, 7(8), 6277-6285.
Ramachandran, K. K., Srivastava, A., Panjwani, V., Kumar, D., Cheepurupalli, N. R., & Mohan, C. R. (2024). Developing AI-powered training programs for employee upskilling and reskilling. Journal of Informatics Education and Research, 4(2). https://doi.org/10.52783/jier.v4i2.903
Robert, N., & Mori, N. (2024). Effects of training needs assessment in enhancing employees’ skills and firm performance. Journal of Work-Applied Management, 17(1). https://doi.org/10.1108/jwam-05-2023-0046
Rulinawaty, Samboteng, L., Purwanto, A. J., Kuncoro, S., Jasrial, Tahilili, M. H., & Karyana, A. (2024). Investigating the influence of the updated DeLone and McLean information system (IS) success model on the effectiveness of learning management system (LMS) implementation. Cogent Education, 11(1), 2365611.
Sabeh, H. N., Husin, M. H., Kee, D. M. H., Baharudin, A. S., & Abdullah, R. (2021). A systematic review of the DeLone and McLean model of information systems success in an E-learning context (2010–2020). IEEE Access, 9, 81210-81235.
Shittu, R. A., Ahmadu, J., Famoti, O., Nzeako, G., Ezechi, O. N., Igwe, A. N., ... & Akokodaripon, D. (2024). Ethics in technology: Developing ethical guidelines for AI and digital transformation in Nigeria. International Journal of Multidisciplinary Research and Growth Evaluation, 6(1), 1260–71.
Simbolon, N. H., Jati, F. D., & Siahaan, S. B. (2025). Overcoming the challenges of AI adoption in banking sector: Security, regulation, and infrastructure. International Journal of Applied Finance and Business Studies, 13(1), 86–95. https://doi.org/10.35335/ijafibs.v13i1.364
Sposato, M. (2024). Leadership training and development in the age of artificial intelligence. Development and Learning in Organizations: An International Journal, 38(4), 4–7. https://doi.org/10.1108/dlo-12-2023-0256
Stofkova, J., Poliakova, A., Stofkova, K. R., Malega, P., Krejnus, M., Binasova, V., & Daneshjo, N. (2022). Digital Skills as a Significant Factor of Human Resources Development. Sustainability, 14(20), 13117. https://doi.org/10.3390/su142013117
Suhail, F., Adel, M., Mostafa Al-Emran, & Adi Ahmad AlQudah. (2024). Are students ready for robots in higher education? Examining the adoption of robots by integrating UTAUT2 and TTF using a hybrid SEM-ANN approach. Technology in Society, 77, 102524–102524. https://doi.org/10.1016/j.techsoc.2024.102524
Symasek, L., Yeazitzis, T., Weger, K., & Mesmer, B. (2025). Recent developments in individual difference research to inform the adoption of ai technology. Systems, 13(3), 156–156. https://doi.org/10.3390/systems13030156
Tomczyk, L., & Majkut, A. (2025). Integrating AI in education: An analysis of factors influencing the acceptance, concerns, attitudes, competencies and use of generative artificial intelligence among Polish teachers. Human Behavior and Emerging Technologies, 2025(1), https://doi.org/10.1155/hbe2/5599169
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC medical research methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45
Tusquellas, N., Palau, R., & Santiago, R. (2024). Analysis of the potential of artificial intelligence for professional development and talent management: A systematic literature review. International Journal of Information Management Data Insights, 4(2), 100288. https://doi.org/10.1016/j.jjimei.2024.100288
Udodiugwu, M. I., Eneremadu, K. E., Onunkwo, A. R., & Onyia, M. K. (2024). The role of artificial intelligence in enhancing the performance of banks in Nigeria. Arabian Journal of Business and Management Review (Oman Chapter), 11(2), 27-34.
Vitezic, V., & Peric, M. (2024). The role of digital skills in the acceptance of artificial intelligence. Journal of Business and Industrial Marketing, 39(7), 1546–1566. https://doi.org/10.1108/jbim-04-2023-0210
Wijayanti, P., Mohamed, I. S., & Daud, D. (2024). Computerized accounting information systems: An application of task technology fit model for microfinance. International Journal of Information Management Data Insights, 4(1), 100224. https://doi.org/10.1016/j.jjimei.2024.100224
Yaqub, Y., & Singh, A. K. (2021). Impact of training design on trainees’ motivation: An empirical study. Industrial and Commercial Training, 54(2), 220–230. https://doi.org/10.1108/ict-05-2021-0038
Yoon, S., & Kim, M. (2023). A study on the improvement direction of artificial intelligence speakers applying DeLone and McLean’s information system success model. Human Behavior and Emerging Technologies, 2023, 2683458. https://doi.org/10.1155/2023/2683458
Yuce, A., Abubakar, A. M., & Ilkan, M. (2019). Intelligent tutoring systems and learning performance. Online Information Review, 43(4), 600–616. https://doi.org/10.1108/oir-11-2017-0340
Zeng, X., Li, S., & Yousaf, Z. (2022). Artificial intelligence adoption and digital innovation: How does digital resilience act as a mediator and training protocols as a moderator? Sustainability, 14(14), 8286. https://doi.org/10.3390/su14148286