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The explosion in AI usage by businesses over the past few years has driven an unmistakable inflection in innovation, efficiency, and profitability. However, as the technology grows in sophistication and ubiquity, it becomes increasingly difficult both to monitor and understand how the algorithms derive outputs and to anticipate downstream ramifications for a firm鈥檚 business processes as well as society at large.

This opacity can expose businesses鈥攁nd those individuals and communities dependent on them鈥攖o undesirable consequences in the absence of appropriate risk management mechanisms. A poorly deployed AI solution may result in suboptimal decisions based upon flawed outputs and diminished returns on technology investments. Enduring reputational damage may arise if businesses sell or otherwise capitalize on sensitive data and analytical or behavioral insights obtained in inappropriate ways.

Societal concerns have also emerged with regard to AI intruding on individual privacy, locking in systemic bias, and eroding social discourse. Lawmakers and regulators are being pressed to simultaneously keep pace with the impacts of rapidly evolving technology while also addressing public concerns. Companies must therefore carefully navigate discontinuities across regulatory bodies as well as a diverse network of stakeholders in order to maintain their social license to employ AI capabilities.

These risks make it an imperative for business leaders to adopt effective governance practices designed for the diverse risks and dynamic nature of AI.

Click through the framework below to explore the various dimensions that companies need to include in their approach to governance and discover why they matter for responsible AI deployment and operation.

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