Generative AI Mini Conference

Join us Friday, April 5th from 9:30 am – 12:00 pm in the LaRose Digital Theatre for a half-day conference. Keynotes will be from Shiva Kommareddi, Managing Director at Accenture, and David Levine, Professor at Elon University School of Law.

Schedule of Conference

9:30 am – 10:00 am Continental Breakfast
10:00 am – 10:50 am Generative AI: What Does Enterprise Adoption Look Like? with Shiva Kommareddi
11:00 am – 12:00 pm What Do We Know and What Can’t We Know About Generative AI? with David Levine

About the sessions and the speakers

Generative AI: What Does Enterprise Adoption Look Like?

Generative AI: What Does Enterprise Adoption Look Like? will delve into the evolving landscape of Generative AI within the industry, spotlighting use cases currently drawing significant attention. It explores practical examples of Generative AI applications across various sectors, including Customer Service, Marketing, and Operations, providing a comprehensive overview of how these technologies are being utilized to enhance efficiency and innovate processes. The presentation examines the impact of Generative AI on the job market, identifying specific roles that might be affected and offering strategies for professionals to adapt and prepare for these changes. This discussion aims to equip attendees with a deeper understanding of Generative AI’s potential and its implications for the future of work.

About Shiva Kommareddi

Kommareddi is an accomplished entrepreneur with a notable track record of founding two successful ventures, both of which culminated in acquisitions, including a prominent one by Accenture. Throughout his impressive career, he has garnered a wealth of experience working for industry giants such as i2, SAS, and Accenture. These roles have not only contributed to his vast expertise but have also significantly shaped his entrepreneurial journey, thanks to the diverse corporate cultures of these organizations. Kommareddi’s insights into the application of Generative AI within the industry stand out, especially regarding its transformative potential in supply chain management and operations. He articulates with clarity the specific areas where Generative AI can deliver game-changing value, reflecting his deep understanding of technology’s impact on the business landscape.

What Do We Know and What Can’t We Know About Generative AI?

The launch of ChatGPT in November 2022 heralded the sudden and unexpected beginning of a new era in technology. In just 18 months, the world has been forced to grapple with a technology that not only computes but creates. A fundamental question must be answered if we are to understand how to think about, use, regulate, and harness generative AI for good; namely, what do we need to know and what can’t we know about generative AI? This presentation grapples with the main issues of AI understanding and information access, through the lens of trade secret law — itself the primary law way that private companies are using to monetize AI.

About David Levine

David Levine is a Professor of Law at Elon University School of Law; an Affiliate Scholar at the Center for Internet and Society at Stanford Law School; and a Fellow at the University of North Carolina’s Center for Information, Technology, and Public Life, and University of Milan’s Information Law Center. Dave was a Visiting Research Collaborator at Princeton University’s Center for Information Technology Policy (CITP) from 2014-2017. David is the co-author of Information Law, Governance, and Cybersecurity (West 2019), the founder of the award-winning Hearsay Culture (KZSU-FM, Stanford University), and numerous law review articles. David has been credited for creating the scholarly field of trade secrecy and information access and focuses on how new technologies can be understood, implemented, and regulated. His work has been recognized and influenced by policymakers in the United States and throughout the globe.

  • Location & Parking Information
  • Questions? Contact Manoj Chari, director of the Center for Organizational Analytics, at or (336) 278-5912.