Artificial Intelligence and Analytic Ops to Continuously Improve Business Outcomes

Artificial Intelligence and Analytic Ops to Continuously Improve Business Outcomes

Wednesday, April 18
11:50 AM - 12:30 PM

The time for enterprises to gain market advantage through Artificial Intelligence is now. Already many AI-enabled advances are transforming business processes and customer experiences, but the vast majority of AI-enhanced use cases are still to be discovered, developed, and deployed. In order to discover and capture the value available through deployed AI, new deep learning techniques are the focus of feverish research and development in academia and business. However, even successful AI experiments are often never deployed to business operations, resulting in wasted effort, time, and money, and leaving businesses dangerously exposed to competitors that have integrated AI into their ongoing operations.
Experimentation with AI is essential to realizing the promise of AI, but enterprises face substantial risks that their experiments with AI, even successful ones, will do nothing to improve their business outcomes. We present a framework, inspired by DevOps practices used by software engineers to continuously incorporate new ideas and improvements into applications, that de-risks investments in AI by providing a reliable channel for pipelining successful AI experiments and development into continuously deployed and monitored operational analytics.

Presentation Video


Nick Switanek
Marketing Director of Artificial Intelligence
Nick has worked for Teradata as a field data scientist and in product marketing for advanced analytics. Nick earned his PhD in business and his MS in statistics and machine learning from Stanford University. Prior to joining Teradata, he was a professor at the Kellogg School of Management at Northwestern University, and a data scientist at McKinsey & Co.