Enabling the AI-Driven Enterprise

The Journey to the AI-Driven Enterprise with Automated Machine Learning

There is a lot of buzz around machine learning and artificial intelligence (AI), but how are organizations using this technology to derive tangible business value? Renowned author and professor Tom Davenport conducted an in-depth study (sponsored by DataRobot) on how organizations have become AI-driven.

In this on-demand webinar, Tom presents his research findings, best practices for AI adoption, use cases on the growth of machine learning, and how automated machine learning technologies make AI more accessible to organizations of all sizes. Additionally, Nathan Patrick Taylor of Symphony Post Acute Network discusses his company’s success using automated machine learning to advance Symphony’s data science initiatives.

Tom and Nathan discuss:

  • The rise in popularity of AI and machine learning, the barriers to adoption, and how automated machine learning addresses them
  • How automated machine learning enables companies to gain insights and make predictions that result in bottom-line value beyond what traditional business intelligence processes have been able to deliver
  • Where data scientists fit in the automated machine learning landscape and the rise of the “Citizen Data Scientist”
  • How successfully operationalizing models is key to gaining value from machine learning and AI
  • Real-world automated machine learning use cases

Speakers

Tom Davenport
Tom Davenport
Author, President’s Distinguished Professor of Information Technology and Management at Babson College, Fellow of the MIT Initiative on the Digital Economy, and independent Senior Advisor to Deloitte’s Analytics and Cognitive Practice
Nathan Patrick Taylor
Nathan Patrick Taylor
Director of Data Science and Analytics, Symphony Post Acute Network