The far-reaching impacts and potential value when deploying Generative AI are accelerating experimental, consumer, and, soon, enterprise use cases. And even though much media coverage has focused on consumer use cases, the opportunities are widespread—and some are already here. Still, questions remain about how individuals and enterprises could use Generative AI to deliver efficiency gains, product improvements, new experiences, or operational change. Similarly, we are only beginning to see how Generative AI could be commercialized and how to build sustainable business models.
Even so, Generative AI is in its infancy and not without risk. Some of the most important risks to address relate to privacy and security, managing bias, transparency and traceability of results, IP ownership, and equal access, especially for those at greater risk of job displacement. As such, participants should balance commercialization, regulation, ethics, co-creation, and even philosophy, as well as expand the group of stakeholder thinkers and contributors beyond technologists and enthusiasts.
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