AI and Automation in Manufacturing:

Planning for the Future Workforce

Date: Thursday, May 23, 2024

Time: 1:00 - 2:00 pm CST

Join us for an innovative webinar as we delve into the transformative impacts of AI in manufacturing and the crucial role of workforce training in this technological evolution. Our panelists, industry experts at the forefront of AI and automation integration in manufacturing, will address key questions shaping the future of workforce development. 

Topics Discussed Will Include: 

• An overview of AI technologies that could revolutionize manufacturing processes.
• How manufacturers are putting initiatives in place to train employees in AI.
• How companies are addressing the skills gap and training needs of their workforce.
• The new skills required for manufacturing workers in the AI and automation era and the investments that are being made in training programs to support learning of these new skills.

Panelists Include:

Jonathan Hodges

Jonathan spent the last 14 years building SaaS-based AI and data products and leveraging analytics to optimize internal business processes. This includes leading smaller to larger 100+ size teams of data professionals (data scientists, ML and data engineers, architects, analysts) and bringing value to organizations through AI and data monetization strategies and execution.

Tuesday Strong, MBA, MSHRD, MSSM

Tuesday helps engineers improve their effectiveness through coaching and professional development programs. Tuesday authored,  Emotional Intelligence (EQ) in the Age of AI: Navigating the Intersection of Human and Machine Intelligence in Advanced Manufacturing, a training program designed to support engineering managers.

Cliff Wiles

Cliff started with Farmland Foods in 1975 in Crete Nebraska. Became Plant Manager of the Farmland Foods facility in Monmouth Illinois in 1996.  Continued Plant Manager roles with IBP (Tyson) and Cargill until retirement in 2022. Understands the significant change that automation and AI will have on the roles and responsibilities within the manufacturing plant.