Choose the topic that is relevant to you. In this session we offer focused topics to dig in deeper into specific content segments. So this is the perfect opportunity to share your story, your specific question and get first hand advice from your peers and experts.  All attendees can participate in the roundtable of their choice and it’s a camera on event.

AI at Scale – the Good, the Bad and the Ugly (Erika McBride)

Businesses both large and small are attempting to keep up with, or get ahead of, the competition by developing, deploying and adopting AI at scale. This journey is riddled with pitfalls, from technology to talent, data quality to culture. Join fellow attendees as we discuss hurdles and triumphs, along with lessons learned at Dow, Inc., on the journey towards Dow’s Analytics Everywhere vision.

Data Science and Design: Driving User Adoption and Business Value through UX (Brian O´Neill)

The dirty secret of analytics and data science, especially in the enterprise, is that a whole lot of the work never gets used. Low or no adoption is rampant, and in fact, one leading expert from the International Institute for Analytics thinks the problem is getting worse. However, more tech and data isn’t the solution. If you work with AI/ML/Analytics or Design/UX, join Brian T. O’Neill for a lively Q/A on how design and UX can help drive adoption and business value in your organization.

Selling Data Science: How to Explain Deep Learning Performance to Business Leaders ( Benjamin Ziomek)

“99% Accurate:” Often the phrase that gets the most attention from business leaders looking at a new data science-based product. But as practitioners know, Accuracy is a meaningless term. Unfortunately, throwing out “F1,” “Recall,” and such don’t usually move the needle with business executives. This presentation talks through how to frame data science products in a way that business leaders can understand, and how to get to the heart of what they care about.