The Cost of Distributed AI Innovation

As AI tools proliferate across industries, employees are using them in ways their organizations never anticipated including, making consequential decisions and automating workflows. While this sounds good in theory, in practice, distributed innovation is leading to high coordination costs, knowledge silos, and delayed decision making. In an age where AI is meant to help, deploying AI without a coordinated effort can lead to increase costs, loss of productivity, and compliance risks. Join this panel of experts to learn more about common pitfalls to avoid when deploying AI at scale and opportunities to avoid issues with fractured implementation of AI across your organization.  

What you will learn:

• What is Distributed Innovation in the AI context and how is it adversely impacting organizations deploying AI at scale?

• How organizations work with AI model and service providers to set themselves up for success.

• How AI deployment can be coordinated as part of a strong technology governance process.