Organizations must adopt concrete, dynamic frameworks to manage AI risks. This pinpointing, prioritization and management of AI risks now should be part of a holistic, long-term strategy to create value for the future.
Many organizations are generating significant value with artificial intelligence (AI) and recognize that this technology will shape the future. At the same time, organizations are discovering that AI could expose them to a fast-changing universe or risks and ethical pitfalls that regulators signal they’ll be watching for – and potentially penalizing. The keys to success are identifying potential risks, evaluating and prioritizing these risks and understanding the foundations for managing these risks. Based on headlines alone, it’s clear that global efforts to manage the risks of AI are just beginning. The earlier organizations adopt concrete, dynamic frameworks to manage AI risks, the more successful their long-term AI efforts will be in creating value without material erosion.
This article was originally published on McKinsey.com on May 3, 2021, and is reprinted here by permission.