Presentation: Generating Business Value with Applied Machine Learning and AI

Talk:

The what: While AI continues to evolve at a rapid pace – adoption rates growing day over day – projects still fail at a disappointingly high rate. The why: In the past, capturing data at scale and building models was the challenge, but today we’re confronted with the issue of making AI more robust while avoiding the risk of unintended consequences.  While the tools are new, many challenges remain the same.  This session will cover:

• Building blocks to develop requirements for AI-driven projects 
• Examples of identifying and mitigating project risks and unintended consequences 
• How to build the business case for an AI project (and get buy in)