AI for Humanity

<p>This thesis examines how Responsible AI (RAI) governance models influence the adoption of AI-powered IoT devices considering critical factors such as transparency fairness accountability privacy and security. As AI systems increasingly interact with human users in data-driven environments concerns over algorithmic governance explainability and regulatory compliance shape public trust and business decision-making. This study explores the intersection of RAI governance industry implementation and user perception using qualitative thematic analysis to draw insights from professional businesses and end-users. The findings reveal that trust in AI-powered IoT is contingent upon multiple RAI principles including explainability data security fairness and ethical oversight rather than transparency alone. Furthermore the study highlights the trade-offs between AI innovation regulatory compliance and ethical deployment providing recommendations for businesses to foster RAI-driven AI adoption while ensuring alignment with evolving governance frameworks. It offers practical recommendations for ethical design regulatory compliance and user-centric transparency helping organizations enhance AI adoption and trust while maintaining a competitive edge in the evolving IoT market.</p>