Authors : Chinenye Blessing Onyekaonwu; Olaide Oluwatobi Ogundolapo; Amina Catherine Peter-Anyebe

Volume/Issue : Volume 10 - 2025, Issue 12 - December

Google Scholar : https://tinyurl.com/yhp83tbj

Scribd : https://tinyurl.com/7jde5udb

DOI : https://doi.org/10.38124/ijisrt/25dec1185

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The rapid adoption of artificial intelligence (AI) across regulated and mission-critical industries has redefined the strategic role of Technical Product Managers (TPMs) in architecting compliant, scalable, and resilient AI-powered infrastructures. This review develops a compliance-driven framework that positions TPMs at the intersection of systems engineering, AI lifecycle orchestration, and enterprise governance. The paper examines how TPMs translate high-level regulatory requirements such as GDPR, HIPAA, NDPR, SOC 2, and emerging AI safety standards into actionable product architecture decisions, spanning data ingestion pipelines, model training workflows, MLOps automation, and post- deployment monitoring. It details TPM responsibilities across the AI lifecycle, including dataset curation oversight, model risk assessment, explainability prioritization, security-by-design enforcement, and continuous compliance validation within CI/CD and ML pipeline environments. Additionally, the review analyzes the TPM’s role in cross-functional alignment, emphasizing coordination with data scientists, ML engineers, security teams, legal/compliance units, and infrastructure architects to maintain traceability, audit readiness, and technical feasibility at scale. Using evidence from high-stakes operational contexts such as healthcare AI systems, fintech anti-fraud engines, and autonomous decision-support tools the paper highlights emerging challenges and best practices for TPM leadership in managing model drift, data governance bottlenecks, adversarial risk, and lifecycle documentation. The proposed framework provides TPMs with structured guidance for designing AI-enabled infrastructures that are not only high-performance and cost-optimized, but also ethically aligned, regulation-aware, and resilient to evolving compliance and security requirements.

Keywords : AI-Powered Infrastructure, Technical Product Management, Compliance-Driven Architecture, MLOps Integration, Cross-Functional Alignment.

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