eISSN: 2791-173X editor@grpublishing.org
All Journals
Submit your article

Global Multidisciplinary Journal

Open Access Peer Review International
Open Access

Strategic Data Governance for Secure AI Adoption and Organizational Resilience: Addressing Challenges in SMEs and Large Enterprises

DOI
pdf
Dr. Pranav R. Kulshreshtha 1 ,
4 Independent Researcher, Data Governance & AI Security Frameworks, Bengaluru, India

Abstract

Background: In an era defined by the proliferation of Artificial Intelligence (AI) and big data, the 
governance of information assets has transitioned from a back-office compliance function to a critical 
strategic imperative. As organizations seek to leverage AI for competitive advantage, the quality, 
security, and ethical management of underlying data have become paramount.  
Methods: This study employs an integrative review of contemporary literature, industry frameworks 
(such as DAMA-DMBOK), and empirical studies to analyze the evolving landscape of data governance. 
The research specifically examines the distinct challenges faced by Small and Medium-sized Enterprises 
(SMEs) compared to large corporations, alongside the critical role of governance in enabling secure AI 
adoption.  
Results: The analysis reveals that while foundational principles of governance remain consistent, 
implementation strategies must be highly adaptive. Large enterprises often struggle with siloed data 
and bureaucratic inertia, whereas SMEs face significant resource constraints that make comprehensive 
frameworks difficult to operationalize. Furthermore, the integration of AI introduces complex ethical 
variables, particularly regarding data privacy in sectors like healthcare and wearables. 
Conclusion: Effective data governance requires a hybrid approach that balances rigid compliance with 
agile decision-making. For AI to be secure and reliable, organizations must adopt metric-driven 
governance models that prioritize data quality and ethical stewardship. The study suggests that future 
frameworks must incorporate decentralized technologies, such as blockchain, to enhance trust and 
transparency in multi-stakeholder environments. 

Keywords

Data Governance, Artificial Intelligence, SMEs, Data Ethics

References

📄 Rajgopal, P. R., & Yadav, S. D. (2025). The role of data governance in enabling secure AI adoption. International Journal of Sustainability and Innovation in Engineering, 3, 1–25.
📄 Sargiotis, D. (2024). Overcoming Challenges in Data Governance: Strategies for success. SpringerLink, 339–363.
📄 Chu, D. (2024). How do data governance metrics enhance decision-making? Secoda.
📄 Levstek, A., Pucihar, A., & Hovelja, T. (2022). Towards an Adaptive Strategic IT Governance Model for SMEs. J. Theor. Appl. Electron. Commerce Res., 17(1), 230–252.
📄 West, C. (2023). SMEs and data governance: an approachable guide. Vaxa Analytics.
📄 Prieto-Avalos, G., Cruz-Ramos, N.A., Alor-Hernández, G., Sánchez-Cervantes, J.L., Rodríguez-Mazahua, L., & Guarneros-Nolasco, L.R. (2022). Wearable Devices for Physical Monitoring of Heart: A Review. Biosensors, 12, 292.
📄 Mangaroska, K., Martinez-Maldonado, R., Vesin, B., & Gaševi´c, D. (2021). Challenges and opportunities of multimodal data in human learning: The computer science students’ perspective. J. Comput. Assist. Learn., 37, 1030–1047.
📄 Choudhury, S., Fishman, J.R., McGowan, M.L., & Juengst, E.T. (2014). Big data, open science and the brain: Lessons learned from genomics. Front. Hum. Neurosci., 8, 239.
📄 DAMA International. (2024). DAMA-DMBOK Revised Edition, 2nd ed. Technics Publications: Denville, NJ, USA, 100–121.
📄 Khatri, V., & Brown, C.V. (2010). Designing data governance. Commun. ACM, 53, 148–152.
📄 McMurry, J.A., Juty, N., Blomberg, N., et al. (2017). Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data. PLoS Biol., 15, e2001414.
📄 Ferretti, A., Ienca, M., Sheehan, M., et al. (2021). Ethics review of big data research: What should stay and what should be reformed? BMC Med. Ethics, 22, 51.
📄 The DGI Data Governance Framework. (2020). The Data Governance Institute.
📄 Feth, D., & Rauch, B. (2024). Datentreuhänder in der praxis. Datenschutz Und Datensicherheit - DuD, 48(2), 103–109.
📄 Garcia, R.D., Ramachandran, G.S., Jurdak, R., & Ueyama, J. (2022). Blockchain-Aided and Privacy- Preserving data governance in Multi-Stakeholder applications. IEEE Trans Netw Serv Manage, 19(4), 3781–3793.
📄 Georgiou, A., Magrabi, F., Hypponen, H., et al. (2018). The safe and effective use of shared data underpinned by stakeholder engagement and evaluation practice. Yearb Med Inform, 27(1), 25–28.
📄 Goel, K., Emamjome, F., & Ter Hofstede, A.H.M. (2021). Data Governance for Managing Data Quality in Process Mining.
📄 Hanapiah, N.M., Iahad, N.A., & Bahari, M. (2021). Identifying Principles and Ownership of Data Governance Framework for Higher Education Institution. Int. Conf. Res. Innov. Inf. Syst.
📄 Hassani, H., & MacFeely, S. (2023). Driving excellence in official statistics: unleashing the potential of comprehensive digital data governance. Big Data Cogn Comput, 7(3), 134.
📄 He, Q., Liu, Y., Jiang, L., Zhang, Z., Wu, M., & Zhao, M. (2023). Data sharing mechanism and strategy for Multi-Service integration for smart grid. Energies, 16(14), 5294.
📄 Hildebrandt, K., Panse, F., Wilcke, N., & Ritter, N. (2020). Large-Scale Data Pollution with Apache Spark. IEEE Transactions on Big Data, 6(2), 396–411.
📄 Huff, E., & Lee, J. (2020). Data as a Strategic Asset: Improving Results Through a Systematic Data Governance Framework. SPELACP.
📄 Jang, K.-A., & Kim, W.-J. (2021). Development of data governance components using DEMATEL and content analysis. J Supercomputing, 77(4), 3695–3709.
📄 Jayasinghe, U., Otebolaku, A., Um, T-W, & Lee, G.M. (2017). Data centric trust evaluation and prediction framework for IOT. 2017 ITU Kaleidoscope: Challenges for a Data-Driven Society.
📄 CTG. (n.d.). Overcoming Common Data Governance Challenges. CTG Blog.

How to Cite

Dr. Pranav R. Kulshreshtha. (2025). Strategic Data Governance for Secure AI Adoption and Organizational Resilience: Addressing Challenges in SMEs and Large Enterprises . Global Multidisciplinary Journal, 4(11), 17-26. https://www.grpublishing.org/journals/index.php/gmj/article/view/197

Most read articles by the same author(s)

<< < 1 2 3 4 5 6 7 8 9 10 > >> 

Similar Articles

1-10 of 90

You may also start an advanced similarity search for this article.