Early AI Adoption: How to Avoid Classic Mistakes – With David Carmona of Microsoft

Nicholas DeNittis

Nick DeNittis writes and edits AI industry trends and use-cases for Emerj's editorial and client content. Nick holds an MS in Management from Troy University and has earned several professional analytics certificates, including from the Wharton School.

What AI Means for Financial Services in a Post-COVID World@2x-min

The main difficulty in starting with AI is knowing exactly where to begin. As we will elaborate in this article, there are many exaggerated and misleading claims about the various types of AI technology. Moreover, some executives are too trigger-happy, wanting or needing to integrate AI into their enterprise sans a foundational education or understanding of the challenges. 

Knowing what questions to ask can be a good starting point: What is my current level of AI knowledge? Am I capable of making a sound judgment as to the organizational readiness for AI? What are the processes or workflows ripe for automation? How do I choose a reliable first AI project, and on what basis?

On Emerj's AI in Business podcast, we're fortunate to have access to enterprise AI leaders from Fortune 500 companies and leading tech firms. In many of our interviews, we ask them directly what questions best helped them find the proper framework to deploy their organizations' first AI projects successfully.

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