It cannot be overstated – A strong corporate culture is the cornerstone of effective governance.
Without an effective governance, organizations will not have the right mechanisms and processes in place to navigate complex challenges.
At the senior leadership level, a strong corporate culture means hiring leaders who embody the organization’s values and shared purpose. This foundation sets the tone for the pillars on which the organization is built and executed.
Understanding the Governance Framework
To build on that, the governance framework is one of the foundational pillars. Governance is not just a set of mechanisms and procedures, but is a system that embodies company values, is adaptive and evolves with changes in the organization and its environment. At the heart of effective governance lies the chartering of authority and direction for oversight and control of programs and initiatives. This governing body, in turn, is accountable for the positive or negative performance outcomes that result.
The interplay between culture and governance is particularly crucial in the context of AI. Effective AI governance is built upon a foundation of strong corporate culture, encompassing core values and committed leadership practices.
Effective governance is marked by effective risk management, enabling informed decision-making and accountability for outcomes, upside and downside risks. In the context of AI, governing leadership must consider risks associated with the AI model and its data, as well as the broader organizational and societal environment in which it operates.
The First Step in approaching AI Risk Management
While traditional risk management frameworks like ISO 31000, NIST Risk Management, and COSO provide a solid foundation for managing risks, they do not fully capture the unique complexities of AI systems – and are specific to organizational risk management. Unlike traditional systems, AI models or solutions are socio-technical in nature and involve human-machine interactions, meaning that they are inherently tied to human behavior and societal implications. Therefore, it is essential to approach AI risk management with a different perspective, one that acknowledges and incorporates the human element into the risk framework.
The first step in effective risk management is identifying the appropriate set of risk categories that apply to the organization and business use case. Along with that, financial or healthcare models, may require additional risk categories and attention to industry specific unique risk. By understanding the specific risks that are most relevant to your organization, you can better manage these risks and ensure the long-term success and sustainability of your business.
Finally, it is important to recognize the ‘risk of loss of control over governance’ as one of the key risk factors in the context of AI governance and risk management.
- A strong culture is the foundation of effective governance, including governance of AI.
- Existing risk management frameworks do not fully address the unique risks associated with human agency and AI.
- Careful consideration of relevant risk categories is critical for successful AI governance, including the risk of loss of governance itself.