Exploring Data Privacy and Protection Mechanisms in AI-Driven Organizations: Challenges and Best Practices
DOI:
https://doi.org/10.64882/ijrt.v14.iS2.1312Keywords:
Data Privacy, AI-Driven Organizations, AI Ethics, Privacy Regulations, Best Practices, Data Security Challenges, Legal Compliance, Ethical AI, Security Mechanisms, Data ProtectionAbstract
It emerged as the explosive use of artificial intelligence in all company's systems aggravated data privacy and protection problems, owing to bigdata processing at scale, autonomous learning and black-box decision-making. We review the main privacy threats, governance challenges and best practices in AI-based organizations through a SLR according to PRISMA guidelines, focused on papers published from 2020 to 2025. The results demonstrate that privacy risks in AI stem from a combination of technical vulnerabilities and human factors, such as data memorization, inference attacks, prompt injection, and the complexity of regulation. The findings imply that effective privacy could be achieved only in a stacked way, joining up technical solutions with ethical AI governance, rules and regulation compliance, as well inter-organizational awareness to ensure responsible and trusted application of AI.
References
Billiris, G., Gill, A., & Bandara, M. (2025). Privacy in the age of AI: A taxonomy of data privacy risks. In Proceedings of the Australasian Conference on Information Systems (ACIS 2025). University of the Sunshine Coast & Australasian Association for Information Systems.
Billiris, G., Gill, A., & Bandara, M. (2025). Privacy in the age of AI: A taxonomy of data privacy risks. In Proceedings of the Australasian Conference on Information Systems (ACIS 2025). University of the Sunshine Coast & Australasian Association for Information Systems.
https://blog.qasource.com/data-privacy-in-ai-testing.
https://data.folio3.com/blog/data-privacy-stats/.
https://hai.stanford.edu/ai-index/2025-ai-index-report
https://hai.stanford.edu/news/privacy-ai-era-how-do-we-protect-our-personal-information.
https://news.stanford.edu/stories/2025/10/ai-chatbot-privacy-concerns-risks-research.
https://trustarc.com/resource/midyear-momentum-data-privacy-trends-2025/
https://www.ai21.com/knowledge/ai-data-privacy/.
https://www.aidataanalytics.network/data-governance/articles/7-trends-shaping-data-privacy-in-2025.
https://www.axiomlaw.com/blog/artificial-intelligence-data-privacy-challenges
https://www.blackfog.com/5-enterprise-use-cases-ai-privacy-concerns/.
https://www.crowdstrike.com/en-us/press-releases/ransomware-report-ai-attacks-outpacing-defenses/.
https://www.dataguard.com/blog/growing-data-privacy-concerns-ai/.
https://www.ey.com/en_lu/insights/ai/data-protection-in-the-ai-driven-era
https://www.f5.com/company/blog/top-ai-and-data-privacy-concerns.
https://www.fortra.com/blog/ai-data-privacy-challenges-and-solutions.
https://www.huntress.com/blog/biggest-data-breaches.
https://www.ibm.com/reports/data-breach.
https://www.ibm.com/think/insights/ai-privacy.
https://www.ibm.com/think/insights/ai-privacy.
https://www.jacksonlewis.com/insights/year-ahead-2025-tech-talk-ai-regulations-data-privacy
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai.
https://www.netfriends.com/blog-posts/5-data-privacy-best-practices-for-ai-users.
https://www.sentinelone.com/cybersecurity-101/data-and-ai/ai-data-security/.
https://www.traverselegal.com/blog/ai-data-privacy-compliance/.
https://www.tredence.com/blog/ai-privacy.
https://www.trustcloud.ai/ai/boost-trust-with-powerful-ethical-ai-and-data-privacy-practices/
Jaiya, H. (2024). Harnessing AI for data privacy: Examining risks, opportunities and strategic future directions. International Journal of Science and Research Archive, 13(02), 2878–2892. https://doi.org/10.30574/ijsra.2024.13.2.2510.
Javed, A. (2025). Data privacy and security in AI-driven customer platforms: A cloud computing perspective. European Journal of Computer Science and Information Technology, 13(44), 84–95. https://doi.org/10.37745/ejcsit.2013/vol13n448495.
OWASP. (2025, February 13). LLM and Gen AI data security best practices. OWASP GenAI Security Project. https://genai.owasp.org/resource/llm-and-gen-ai-data-security-best-practices/.
Papagiannidis, E., Mikalef, P., & Conboy, K. (2024). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 33(1), 101885. https://doi.org/10.1016/j.jsis.2024.101885.
Tanisha, J., Pillai, A. R., Roy, G. S., Koshy, A., Kothari, S., & Ajitha, D. (2024). Privacy and data protection challenges in Industry 4.0: An AI-driven perspective. World Journal of Advanced Engineering Technology and Sciences, 12(2), 064–089. https://doi.org/10.30574/wjaets.2024.12.2.0287.
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