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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66878
Volume:
10 |
8 |
Aug 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
College of Law
Koneru Lakshmaiah Educational Foundation, University, Vijayawada,Andhra Pradesh, India.
The rapid diffusion of artificial intelligence (AI) systems across commerce, government, and daily life has intensified long-standing tensions between technological innovation and the right to privacy. AI systems depend on the large-scale collection, aggregation, and inferential processing of personal data, often in ways that strain the foundational principles of data protection law, including purpose limitation, data minimisation, consent, and transparency. This paper examines the legal challenges that artificial intelligence poses to the protection of personal data, drawing on comparative analysis of the European Union's General Data Protection Regulation and Artificial Intelligence Act, the sectoral and state-based framework of the United States, and emerging approaches in other jurisdictions. It identifies recurring points of friction, including the opacity of algorithmic decision-making, the difficulty of applying consent-based models to machine learning training, the phenomenon of inference of sensitive attributes from ostensibly non-sensitive data, the tension between data minimisation and data-hungry model development, and the practical impossibility of full erasure once personal data has been absorbed into a trained model. The paper further considers enforcement fragmentation between data protection authorities and AI-specific regulators, cross-border data transfer complications, and the growing use of biometric and profiling technologies. Through analysis of statutory text, regulatory guidance, and enforcement trends current as of mid-2026, the paper argues that existing privacy frameworks, though adaptable in principle, require targeted reform, technical standard-setting, and closer institutional coordination to remain effective against AI-driven risks to personal data. The paper concludes with policy recommendations aimed at reconciling innovation incentives with the enduring legal and normative value of privacy as a fundamental right.
KEYWORDS
Artificial intelligence does not render existing privacy and data protection law obsolete, but it exposes structural assumptions — a linear data lifecycle, a stable line between collected and inferred data, and an assumption that deletion is straightforward — that no longer hold reliably in an AI-driven data ecosystem. The EU's layered GDPR–AI Act architecture is the most developed response to date, while the United States' sectoral, state-driven approach shows both the flexibility and the fragmentation that result from relying on general consumer-protection enforcement absent comprehensive federal legislation. Across jurisdictions, the recurring challenges identified here — consent, automated decision-making, inference, data minimisation, erasure, cross-border transfer, biometric identification, and enforcement fragmentation — point to a common conclusion: protecting personal data in the age of AI requires not only vigorous application of existing legal principles but targeted statutory reform, technical standard-setting, and sustained institutional coordination, which together will determine whether privacy retains practical meaning as AI becomes further embedded in everyday data processing.
[1]GDPR, Art. 22. [1]Case C-634/21, OQ v. Land Hessen (CJEU, 7 December 2023) (SCHUFA). [1]Secure Privacy, 'GDPR Compliance in 2026: The Complete Guide' (2026). [1]European Data Protection Board, 2026 Coordinated Enforcement Framework Action on Transparency, as reported in Inside Privacy, 'What to Watch in 2026' (28 January 2026). [1]Case T-553/23 (EU General Court, 3 September 2025), on appeal as Case C-703/25 P (CJEU, filed 31 October 2025). [1]AI Act, Art. 5(1)(h); Nixon Peabody, 'Data Privacy, Cybersecurity, AI developments shaping 2026' (9 February 2026). [1]TechGDPR, 'Data protection digest 1 Aug 2026', reporting EDPB discussion of rising complaint volumes attributable to AI.
Publication Date
8/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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