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<p>Artificial intelligence (AI) is transforming organizations by driving efficiency and innovation. However, its rapid adoption also brings ethical, regulatory, and governance challenges. This paper presents the AI-C2C (conscious to conscience) governance framework—a practical, phased model designed to help organizations navigate ethical AI integration. The framework consists of three stages: AI-conscious adoption, AI + human intelligence (HI) collaboration, and AI-conscience governance. It evolves with AI maturity, focusing on transparency, accountability, and role-based oversight. The framework is built on insights from expert interviews, sector case studies (IBM, AstraZeneca, Mastercard), and a thorough literature review. It outlines key roles, including the Chief AI Officer, the creation of AI ethics committees, and the use of Explainable AI (XAI). Additionally, the framework proposes seven key performance indicators to assess ethical compliance, transparency, workforce readiness, and regulatory alignment. This paper provides a clear roadmap for organizations to adopt AI responsibly, foster stakeholder trust, and create long-term value through ethical innovation.</p>

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AI-C2C (conscious to conscience): a governance framework for ethical AI integration

  • 期刊论文

  • 发表日期：

    2025年4月22日

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  • Thamburaj Anthuvan,
  • Kajal Maheshwari

摘要

Artificial intelligence (AI) is transforming organizations by driving efficiency and innovation. However, its rapid adoption also brings ethical, regulatory, and governance challenges. This paper presents the AI-C2C (conscious to conscience) governance framework—a practical, phased model designed to help organizations navigate ethical AI integration. The framework consists of three stages: AI-conscious adoption, AI + human intelligence (HI) collaboration, and AI-conscience governance. It evolves with AI maturity, focusing on transparency, accountability, and role-based oversight. The framework is built on insights from expert interviews, sector case studies (IBM, AstraZeneca, Mastercard), and a thorough literature review. It outlines key roles, including the Chief AI Officer, the creation of AI ethics committees, and the use of Explainable AI (XAI). Additionally, the framework proposes seven key performance indicators to assess ethical compliance, transparency, workforce readiness, and regulatory alignment. This paper provides a clear roadmap for organizations to adopt AI responsibly, foster stakeholder trust, and create long-term value through ethical innovation.