Industry Case Studies on Building and Governing Trustworthy AI Platforms

As artificial intelligence systems proliferate across critical industry sectors, the imperative to build platforms that are simultaneously capable and trustworthy has grown urgent. This chapter examines five cross-sector case studies—spanning financial services, healthcare, manufacturing, public administration, and retail—to surface the governance architectures, transparency mechanisms, and accountability structures that distinguish trustworthy AI deployments from opaque, high-risk alternatives. Drawing on responsible AI governance frameworks, the Digital Trust Ecosystem Framework (DTEF), NIST AI RMF, and the EU AI Act, the chapter synthesises recurring patterns: layered data governance, explainability-by-design, fairness auditing pipelines, and human oversight protocols.

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