Published: 04 April 2024
Data and analytics leaders are challenged to effectively govern AI due to its rapidly evolving characteristics and potential to amplify human bias. This research provides a comprehensive approach to extend governance to include AI-specific considerations like trust, transparency and diversity.
Artificial intelligence (AI) is becoming mission-critical in the enterprise. The criticality, scalability and democratization of AI all require governance to balance the AI’s value with the new risks it poses.
It is possible to organize and base AI governance on common governance pillars, because good governance embodies similar characteristics regardless of domain.
AI encompasses a continually evolving technological landscape in which there are trade-offs between scale, explainability, accessibility, speed, skills and cost. This complexity — together with the ambiguity intrinsic to AI’s predictive and generative nature — leads to a lack of clarity around AI’s reputational, business and societal impacts.
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Analysts:
Svetlana Sicular, Peter Krensky, Saul Judah
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