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Strategic AI Risk Management & Quantification

In: AI and the Boardroom

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  • Rohan Sharma

Abstract

Ensuring your AI initiatives are both effective and secure requires understanding the risks they pose and developing structured mitigation strategies. Are you ready to manage the complex risks associated with deploying AI? This chapter explores a systematic approach to AI risk management through three key steps: mapping risks, measuring their impact, and managing them effectively—all underpinned by strong governance to embed risk management in your organization’s culture. Mapping involves identifying risks in the specific contexts of AI use, while measuring focuses on assessing their potential impact and likelihood. Managing these risks means prioritizing actions and continuously monitoring mitigation strategies to keep them effective. Start by building a culture that prioritizes risk management, integrating it into every stage of the AI lifecycle, and fostering cross-functional collaboration. Effective risk management is an ongoing process that helps build trust and ensures sustainable success for AI initiatives. How will your organization rise to the challenge of managing AI risk effectively?

Suggested Citation

  • Rohan Sharma, 2024. "Strategic AI Risk Management & Quantification," Springer Books, in: AI and the Boardroom, chapter 0, pages 287-295, Springer.
    • Handle: RePEc:spr:sprchp:979-8-8688-0796-1_23
    DOI: 10.1007/979-8-8688-0796-1_23
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