Artificial Intelligence Governance Practices and Entrepreneurial Trust Outcomes

ABSTRACT: The rapid adoption of artificial intelligence (AI) in entrepreneurial ventures has raised critical questions regarding trust, transparency, and ethical responsibility. Although AI has the potential to innovate and enhance the efficiency of the operations, the stakeholders tend to develop hesitancy due to the fear of making unethical decisions, misusing data, and accountability. This study investigates the influence of AI governance practices on entrepreneurial trust outcomes, with the overarching objective of understanding how ethical guidelines, data privacy and protection policies, algorithmic transparency, regulatory compliance, and accountability systems collectively shape stakeholder confidence in AI-driven ventures. The study is based on a qualitative and conceptual approach that uses the secondary sources of data, such as academic journals, books, and historical evaluations and industry reports to generalize theoretical and empirical knowledge. The analysis points to the fact that the integrated governance mechanisms play a crucial role in the promotion of trust due to the ethical practice, data protecting, the straightforward decision-making procedure, and accountability. Key recommendations include the adoption of comprehensive AI governance frameworks by managers and entrepreneurs, development of regulatory guidelines by policymakers, and continuous stakeholder engagement to reinforce credibility and legitimacy. The study concludes that AI governance is both a strategic and ethical imperative for sustainable entrepreneurial success. Limitations Limitations Reliance on secondary data might be limiting since it might fail to provide a contextual difference between industries and geographies.

KEYWORDS: Artificial intelligence, AI governance, ethical guidelines, data privacy, algorithmic transparency, regulatory compliance, entrepreneurial trust.