Organizations increasingly employ A.I. to enhance efficiency and decision-making processes in the modern business landscape. However, using A.I. presents numerous governance, risk management, and compliance (GRC) challenges that need meticulous attention. Within the scope of an enterprise perspective of GRC is the growing domain of A.I. GRC – the governance, risk management, and compliance over the use of artificial intelligence. The Open Compliance and Ethics Group (OCEG) defines GRC as “a capability to reliably achieve objectives, address uncertainty, and act with integrity.”

Adapting the definition of GRC to address the specifics of A.I., A.I. GRC is the capability to reliably achieve the objectives of A.I. models and their use, to address the uncertainty and risk in the use of A.I., and to act with integrity in the ethical, legal, and regulatory use of A.I. in the organization’s context. 

  • A.I. Governance. Governance in A.I. involves overseeing and guiding A.I.-related initiatives and the use of A.I. technology and models to ensure alignment with organizational objectives and values. Proper governance implies establishing clear A.I. policies, procedures, and decision-making frameworks. These frameworks should help an organization “reliably achieve objectives” of the organizations and ensure that the objectives and design of the A.I. models in their intended purpose are also achieved. Thus, the governance of A.I. involves strategic planning, stakeholder engagement, and performance and A.I. usage monitoring to ensure A.I. projects effectively meet their intended objectives and contribute positively to the broader organizational objectives.
  • A.I. Risk Management. Risk management in A.I. refers to identifying, assessing, and managing the uncertainty associated with developing, using, and maintaining A.I. technologies. These risks range from technical aspects, such as security breaches or system failure, to ethical aspects, like algorithmic bias or privacy infringement. Risk management is about addressing uncertainty. Given their potential to hamper an organization’s operations or reputation, A.I.-related risks require comprehensive risk assessments and robust risk mitigation strategies.
  • A.I. Compliance. Compliance is a critical aspect of A.I. implementation. As A.I. technology evolves, so does the regulatory landscape surrounding its use. Compliance in the A.I. context means adhering to relevant legal requirements, industry standards, and ethical norms. Compliance equates to “acting with integrity.” This involves adhering to regulations like GDPR for data privacy and adopting ethical A.I. practices to maintain transparency, fairness, and accountability in A.I. applications. In today’s era of ESG – environmental, social, and governance – the ethical use of A.I. is part of the organization’s ESG commitments. 

Incorporating core GRC principles in the responsible use of A.I. involves building a culture that values ethical A.I. use and behavior, transparency, and consistent improvement. 

The blog above is taken from GRC 20/20’s paper on: A.I. GRC: The Governance, Risk Management & Compliance of A.I.

Upcoming A.I. GRC webinars:

October 18 @ 3:00 pm – 4:00 pm EDT 

November 7 @ 12:00 pm – 1:00 pm CST 

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