Events
Chamber Events
AI for Manufacturing: Applied Deep Dive - November 19, 2026 - Cookeville, TN
Name:
AI for Manufacturing: Applied Deep Dive - November 19, 2026 - Cookeville, TN
Date:
November 19, 2026
Time:
1:00 PM - 5:00 PM CST
Registration:
Register Now
Event Description:
Understanding AI is only the starting point. Moving toward implementation requires manufacturers to answer three practical questions: What will it cost? How will company data be protected? How will the organization demonstrate a return on investment?
The afternoon session addresses these concerns through live demonstrations, case studies, and an overview of implementation options. Participants will explore local large language models, open-source AI tools, and vibe coding as possible ways to develop useful solutions while managing cost, security, and business value.
Who should attend: Operations leaders, plant managers, quality and maintenance managers, continuous improvement professionals, and IT partners who want to move beyond basic AI use. The morning session is helpful but not required; participants should have at least a working familiarity with AI tools.
The afternoon session addresses these concerns through live demonstrations, case studies, and an overview of implementation options. Participants will explore local large language models, open-source AI tools, and vibe coding as possible ways to develop useful solutions while managing cost, security, and business value.
Core Business Challenges
- Uncertain subscription costs, including changing per-user pricing and unclear full-deployment expenses
- Data safety concerns involving proprietary processes, drawings, customer information, and quality records
- Uncertain ROI from pilots that demonstrate potential but do not establish measurable business value
Solutions Explored
- Local large language models, including a live demonstration and a discussion of when local hosting may be appropriate
- Open-source tools and an overview of the AI engineering landscape
- Vibe coding demonstrations and case studies showing how small internal tools can be developed quickly
What Participants Will Learn
- Address the cost, data security, and ROI questions that commonly slow AI adoption
- Understand what a locally hosted model is and when it may be appropriate for protecting proprietary information
- Evaluate open-source AI tools and vendor claims more confidently
- Identify internal processes that may be good candidates for small AI-enabled tools
- Develop a more defensible business case for AI investment
- Outline practical next steps to discuss with organizational leadership and IT
Who should attend: Operations leaders, plant managers, quality and maintenance managers, continuous improvement professionals, and IT partners who want to move beyond basic AI use. The morning session is helpful but not required; participants should have at least a working familiarity with AI tools.
