Distinguished Seminar Series on AI-Driven Workforce and Business Development
Advancements in Artificial Intelligence (AI) are transforming businesses, reshaping education, and redefining the future of work. While AI provides enormous business opportunities such as increased effectiveness and work productivity, its accelerated adoption has raised critical questions about business sustainability, market dominance, cybersecurity, and reskilling of workers. Tennessee businesses and government agencies are not immune to the significant effects of advanced AI technologies. The proposed Distinguished Seminar Series will stimulate discussions and strategies to navigate the role of AI in business and workforce development where we must develop capacity to capture value and reduce risks simultaneously in an AI-driven business environment. The seminars will be organized by the PIs in partnership with AI Tennessee Initiative, Haslam College of Business, College of Emerging and Collaborative Studies, TN Department of Economic Development, TN Department of Labor, and TN Chamber of Commerce & Industry. Overall, we aim to accomplish the following objectives:
Create awareness for the TN business and government agencies about the scale of AI disruption to the business landscape and of the opportunities to increase efficiency, innovation and productivity.
Create a network of research and practice in TN to study the impact of AI on the local business operations in public and private sectors. Use this information to develop a map of skill transformation so that every Tennessean is equipped with knowledge and skills needed not only to survive but also thrive in the AI-driven business environment.
Create a resource hub for TN businesses and public agencies to develop capacity to effectively respond to the disruption caused by AI and other emerging technologies, meanwhile creating and capturing business value through technological innovations.
Our distinguished seminar series features leading experts on AI research, development, and applications tailored to help Tennessee businesses and government agencies navigate AI disruptions and foster sustainable workforce development. The seminars will include thought-provoking talks, practical strategies for adopting AI tools and business models, tutorials for professional upskilling, and panel discussions focused on talent management and reskilling.
We anticipate that the Distinguished Seminar Series will enhance our research collaborations, community involvement, and broader impacts by encouraging dialogue, partnership, and thought leadership. Through this series, we will gather insights and data from the community, which will inform the development of resources tailored to support Tennessee businesses and government agencies in effectively addressing the challenges posed by AI innovations.
AI has found success in a number of different application areas in recent years. One area that could benefit from a new paradigm brought forth by AI is small-molecule drug discovery. Traditional drug discovery methods based on wet lab experimentation have reached a saturation point with fewer and fewer new drug candidates produced despite ever larger lab-based efforts. In recent years, a number of attempts have been made to repurpose AI models developed for other goals toward drug discovery. Some examples include Large Language Models that had originally been developed for language generation and Diffusion Models that had been developed for image generation. We will review the to-date results of these approaches — sharing the limited new drug candidates that have come out of these efforts. We will, then, discuss the novel approach pioneered by Verseon, which combines novel AI model types with a breakthrough molecular modelling approach. We will discuss some specific recent results of our novel AI technology in predicting drug gene interactions.
Biography
Ed Ratner is the Head of Machine Learning at Verseon. He is also a Fellow of the National Academy of Inventors since 2024. Verseon acquired Edammo Inc. where he was cofounder and CEO in 2022. Edammo has developed breakthrough AI technology and was chosen as one of the Top 10 AI solution providers by PharmaTech Outlook Magazine and as a Top 10 Predictive Analytics provider by CIO Applications magazine. Previously, Ed founded and served as the CTO of Lyrical Labs. Lyrical Labs was selected for the Cable Labs Innovation Showcase in 2012 for its innovative video encoding technology. Before that, in 2007, Ed co-founded Keystream Corporation, which was recognized with a 2009 Best of Business Award by the Small Business Commerce Association. He was the President, Research & Development, and led the creation of Keystream’s novel in-video ad insertion product. Additionally, he was the VP of R&D/Chief Scientist at Pulsent Corp., which pioneered a proprietary object-based video codec. His work has resulted in 40 issued US patents to date. Ed received his Ph.D. from Stanford University, where he was a Hertz Foundation Fellow. He also won the National Science Foundation and the National Defense Science/Engineering Fellowships. He received his B.S. in Physics from Caltech, where he received the Froehlich Prize for most creative junior, and was a high scorer on the Putnam Exam Competition scoring among the top ten juniors in North America. He has been a Senior Member of IEEE since 2004. In 2018, his paper received the Best Paper Award at ELM 2018 conference in Singapore. In 2022, he was chosen as one of the Top 100 Innovators and Entrepreneurs by the Top 100 magazine.
An AI-Native Approach to Simplifying How Businesses Run
Abstract
At WEX, AI is not simply a technology; or a standalone strategic initiative; it’s the foundation of our company’s strategy. We’re embedding it deep into the fabric of how we build, serve, and operate. This approach will empower us to fulfill WEX’s purpose of simplifying the business of running a business.
Our AI strategy is built on three core pillars: unlocking internal productivity, reimagining customer experiences, and empowering our employees. Powered by our rich proprietary data, we apply AI throughout our software development lifecycle and operations across all of our lines of business to accelerate product/service development and operations. For example, our Claims AI tool transforms a multi-day manual reimbursement process into a “Snap, Scan, Done” experience, and the Fleet Signal Hub turns raw data into actionable insights for fleet managers with automated decision-making and action-taking capabilities.
By investing in a scalable, reliable, and properly governed Data and AI platform with an integrated multi agent framework, we democratize AI applications among all the product development teams across the company at scale and speed. At the same time, we lift up the AI understanding and skills of our employees by both attracting high talents from the industry & universities and training our existing talents across all the roles. Through these efforts, we are actively growing WEX into an AI-native tech company, which will well position WEX in the market. We’ve made significant progress in this direction and are committed to continued investment.
Morgan Frank Assistant Professor at University of Pittsburgh School of Computing and Information
Friday, Oct 3, 2025, 10:00AM
Haslam Business Building 401
AI, Complexity, and the Future of Work
Abstract
Generative AI has wide ranging applications across sectors and the potential to disrupt education, jobs, and careers. While industry leaders warn of lost job opportunities, how can we prepare today’s students and workers for success? In this talk, I will explore why it’s hard to predict job loss from AI and how newly available career data offers a path forward. Using millions of resumes, I will show that workers engaged in the jobs most exposed to LLM automation have experienced salary decreases and job market frictions since the launch of ChatGPT, and that these impacts are most acute for recent college graduates. In the remainder, I will demonstrate how research into skills can illuminate labor market conditions that foster career mobility in the face of labor disruption.
Biography
Morgan Frank is an Assistant Professor at the School of Computing and Information at the University of Pittsburgh, a Digital Fellow in Stanford’s Digital Economy Lab, and a Fellow at Microsoft’s AI Economy Institute. Morgan is interested in the complexity of AI, the future of work, and the socio-economic consequences of technological change. While many studies focus on phenotypic labor trends, Morgan’s recent research examines how genotypic skill-level processes around AI impact individuals and society. Combining labor research with investigations into the nature of AI research and the social or societal implications of AI adoption, Morgan hopes to inform our understanding of AI’s impact.
