Bridging the AI governance gap: Evaluating the effectiveness of transparency tools and ethics boards in multinational firms

Generative artificial intelligence (AI) is transforming innovation and competitiveness in multinational corporations, yet its rapid adoption has outpaced the development of effective governance mechanisms. This study investigates the “Generative AI Governance Paradox”, the tension between fostering innovation and ensuring transparency, accountability, and regulatory compliance. Using a mixed-methods approach, the research evaluates the effectiveness of transparency tools (e.g., explainable AI, third-party audits, model documentation) and ethical oversight structures (e.g., AI ethics boards) in mitigating governance risks. Qualitative interviews with 30 governance experts and a quantitative survey of 150 multinational firms reveal that organizations combining explainable AI with empowered ethics boards experience significantly fewer governance failures. Specifically, these firms report 48% fewer instances of bias and regulatory violations, and 35% fewer regulatory investigations when third-party audits are employed. However, ethics boards with only advisory roles showed limited impact. The study emphasizes that real effectiveness stems from the integration of these tools into core decision-making processes, supported by leadership commitment and an ethical culture. The findings underscore the need for robust governance practices, executive authority in oversight structures, and the institutionalization of ethics in AI deployment. Future research should explore sector-specific governance models and emerging technologies for enhancing AI accountability at scale.