Agentic AI in Engineering: From Experimentation to Business Impact

How to identify the right opportunities, build the right foundation, and scale with confidence

29 10 月, 2026, 10:00 a.m. ET

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Agentic AI is moving rapidly from experimentation toward real engineering and product development use cases. But for manufacturing leaders, the challenge is no longer simply identifying what AI can do. The harder question is deciding where to apply it, where it can create differentiated business value, and whether the organization has the data, context, governance, and processes needed to scale it. Join Jeff Hojlo, research vice president, Industrial Ecosystems, Engineering & Product Innovation Strategies at IDC, and Josh Epstein, chief marketing & strategy officer at Aras, for a strategic conversation grounded in findings from IDC’s Early Adopter Agentic AI Functional Use Case Study. They will examine how manufacturers are beginning to apply agentic AI in R&D, engineering, and the broader product lifecycle, and how leaders can evaluate opportunities that deserve investment.

The discussion will go beyond individual AI use cases to examine the foundation beneath them. Engineering decisions rarely depend on a single document or data source. They depend on product configurations, requirements, changes, approvals, relationships, history, and downstream impact. As AI takes on more complex work, connected and contextualized product information becomes increasingly important to the quality and trustworthiness of the outcome. Jeff and Josh will explore how the digital thread can provide that context, how AI itself may help accelerate and strengthen it, and how organizations can move from isolated pilots to repeatable business value.

The goal is not to provide another list of AI possibilities. It is to help engineering and manufacturing leaders develop a clearer framework for answering three questions:

Where should we apply agentic AI? What must be true for it to work? And how do we turn it into a business advantage?

How to Think About Agentic AI in Your Business

  • How to identify the right starting points for agentic AI
  • How to distinguish an interesting AI demo from a scalable business use case
  • Why product context matters as much as access to data
  • How AI and the digital thread can reinforce one another
  • How to move from experimentation to an operating model for AI

Agentic AI is moving faster than most engineering organizations can operationalize it. Register to hear IDC and Aras discuss how to separate opportunity from hype, identify where AI can create meaningful engineering and business value, and build the product-data foundation required to scale it.