What Is AI Governance?

AI Governance: Definition and Purpose

AI governance refers to the imposition of frameworks, rules, standards, legal requirements, policies, and best practices that govern, manage, and monitor the use of artificial intelligence (AI). It involves directing, managing, and monitoring AI activities to meet legal and ethical requirements. On the ethical front, businesses are focused on ensuring a high level of transparency, safety, and security in their AI models to build and maintain customer trust. On the legal front, enterprises must conform to legal requirements and satisfy regulators—or risk substantial financial penalties and damaged brand reputation.

Hardly a day passes without news of a new technological or legal development in generative AI appearing in the media—and they all have implications for the way companies do business. This frenzy is justified, as McKinsey research estimates that generative AI could contribute between $2.6 trillion and $4.4 trillion in annual value going forward. However, to realize this potential, organizations must implement AI in a way that is transparent, secure, and trustworthy. In fact, Gartner suggests that organizations that successfully operationalize secure and trustworthy AI could see a 50% increase in their AI adoption and attainment of business goals.

The key drivers of AI governance in enterprises include innovation, efficiency, compliance, and trust—all crucial elements for successfully integrating AI into business operations.

• Innovation: AI governance provides a structured, yet flexible, framework that encourages responsible innovation. It allows for the development of advanced AI solutions within ethical boundaries, driving business growth and competitive advantage.
• Efficiency: By standardizing and optimizing AI development and deployment processes, AI governance enables enterprises to bring AI products to market faster while reducing costs.
• Compliance: AI governance aligns AI solutions and decision-making with industry regulations and global legal standards. This ensures that AI practices meet legal requirements, reducing legal risks for the business and furthering its regulatory compliance.
• Trust: AI governance focuses on building trustworthy and transparent AI systems—a practice that is crucial for maintaining customer rights and satisfaction while also protecting the organization’s brand value. Trustworthy AI enhances customer confidence and loyalty while reducing the risk of regulatory action.