Scaling AI in Engineering: A Practical Blueprint for Companies of Every Size

In collaboration with

Across industries, engineering leaders are experimenting with AI pilots — but many remain uncertain about how to move from experiments to production-scale adoption. The challenge is not primarily about what algorithms or tools to select, but about creating the right blueprint: where to start, how to integrate with existing workflows, and how to scale in a way that engineers trust and the business can see immediate value.

This webinar shares independent, practical perspectives on how companies of all sizes can bring AI into engineering. We will explore how companies are combining foundation models, predictive physics AI, agentic workflow automation, and open infrastructure into a stepped roadmap that works whether you are a small team seeking efficiency gains or a global enterprise aiming to digitally transform at scale.

Watch it to learn:

• Where AI fits naturally into today’s engineering workflows — and where it doesn’t
• How Physics AI can provide reliable predictions early in design without replacing high-fidelity simulation
• How Agentic AI can codify and scale best practices, improving consistency and productivity across teams
• The importance of foundation models and open integration in building usable systems that adapt to both small and large organization’s current state
• A mental model for helping teams moving from pilots to production — including data, process, and cultural considerations