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Artificial intelligence (AI) has swiftly emerged as a core technology for securing a competitive advantage. Nonetheless, there are escalating anxieties regarding bias within AI models, given that AI developers are susceptible to introducing bias both inadvertently and intentionally. Utilizing a qualitative methodology, this study explored how AI developers can actively foster the creation of equitable AI models. The primary results indicate that the danger of bias stems predominantly from a deficiency in social and gender diversity within AI development teams, alongside pressure from AI managers to rapidly deliver highly anticipated outcomes. Furthermore, the integrity of AI developers is critical, as they possess the ability to hide biases from management and other relevant AI stakeholders. The testing phase preceding model deployment is also prone to bias because it seldom reflects the diverse social demographics that could be impacted.This research offers actionable recommendations across four core dimensions: governance, social, technical, and training and development procedures. Responsible organizations must implement deliberate measures to guarantee that their AI developers follow equitable protocols during AI creation; AI developers need to put ethical considerations first and evaluate the societal impacts of their models; collaborative partnerships ought to be formed among AI developers, AI stakeholders, and the communities likely to be affected by these models; and AI developers must emphasize transparency and explainability within their models while ensuring robust bias testing and remediation prior to deployment. Lastly, providing emotional intelligence training to AI developers is recommended to equip them for constructive dialogue with stakeholders outside the immediate development team.