Agentic AI for the Engineering Workflow: From CAD to Simulation to Decision
- Date
- 2026-09-24
- Location
- Online
- Host
- ASME
About this event
Engineering teams are being asked to move faster while dealing with more design complexity, tighter performance targets, and growing pressure to make better decisions earlier. This virtual session looks at how agentic AI can support that reality across the engineering workflow, from CAD to simulation to downstream decision-making, with a focus on where these systems can actually create leverage for advanced manufacturing and robotics teams. About the Event This event is a focused online conversation about how AI agents can be applied inside real engineering workflows, not just as general productivity tools, but as systems that can reason across tasks, coordinate steps, and help teams move from design intent to actionable decisions. The emphasis is on the full chain: how work begins in design environments, how it flows into simulation and analysis, and how those outputs can inform faster, more confident engineering choices. Rather than treating CAD, simulation, and decision support as isolated steps, this session centers on the connections between them. That matters because many bottlenecks in engineering do not come from a single tool; they come from handoffs, iteration loops, and the effort required to translate information from one stage into the next. Agentic AI becomes interesting when it can help bridge those gaps. Because this is a virtual event, it is designed to be accessible to attendees working across software, hardware, manufacturing, and R&D contexts. If your work touches product development, digital engineering, robotics, or advanced manufacturing systems, this event is intended to help you think more concretely about where agentic workflows may fit. What to Expect Expect a structured look at the engineering workflow through the lens of intelligent automation and AI-assisted orchestration. The discussion will move through the lifecycle from design creation to analysis to decision support, showing how these stages relate and where agentic systems may reduce friction, accelerate iteration, or improve consistency. Topics are likely to include: How agentic AI can interact with CAD-centered workflows Where simulation processes create delays, rework, or dependency bottlenecks What it looks like to connect analysis outputs to engineering or operational decisions How robotics and advanced manufacturing teams may evaluate practical use cases The difference between simple automation and agentic systems that can manage multi-step tasks You should also expect a pragmatic tone. This is not just about what AI could theoretically do; it is about how engineering teams can think about usefulness, trust, workflow integration, and decision quality. For technical attendees, that makes the conversation especially relevant: the value of AI in engineering depends on reliability, traceability, and fit with existing processes. Since the event is online, the format supports a broad audience that may include engineers, technical leaders, product thinkers, and operators exploring how intelligent systems can support design and development work. Whether you are deep in simulation, managing engineering programs, or evaluating digital transformation initiatives, the session is meant to give you a clearer map of the landscape. Why Attend If you are hearing more about AI in engineering but want a better framework for separating signal from noise, this event will be useful. Agentic AI is often discussed in broad terms, but its value becomes much clearer when examined inside a specific workflow with clear inputs, outputs, constraints, and decisions. CAD, simulation, and decision-making provide exactly that kind of structure. You will come away with a better understanding of where agentic AI may be most useful in engineering environments, where the limitations are likely to appear, and what kinds of problems are worth prioritizing first. That can help you avoid both extremes: dismissing the opportunity too early or overcommitting to ideas that are not ready for production workflows. This is especially relevant for advanced manufacturing and robotics, where engineering cycles can be expensive, multidisciplinary, and tightly coupled to real-world performance. Faster iteration is valuable, but only if it improves outcomes. Better simulation throughput is valuable, but only if it leads to better decisions. This event focuses on that chain of value. Attendees should leave with practical mental models they can use immediately, including: Where agentic AI may fit within current engineering processes What kinds of workflow handoffs are strongest candidates for AI support How simulation and analysis can become more actionable What to ask when evaluating AI systems for technical teams How to think about decision quality, not just task automation Practical Details This is an online / virtual event, so you can attend from anywhere. That makes it a good fit for distributed engineering teams, practitioners working across time zones, and anyone who wants to engage with the topic without the overhead of travel. The event takes place on Thursday, September 24 at 12:00 AM UTC. If you plan to attend from another region, it is worth checking the time in your local zone ahead of time so you can block the right window on your calendar. Because the topic sits at the intersection of AI, engineering software, robotics, and manufacturing systems, you do not need to come from a single discipline to get value from the session. What matters most is that you care about how design, analysis, and decision-making connect, and how those connections can be improved. If your current work involves product development workflows, digital engineering infrastructure, simulation pipelines, or operational decision support, this event is a strong opportunity to sharpen your thinking on a topic that is moving quickly and becoming harder to ignore.
Who should attend
This event is for people who want a more concrete, engineering-centered view of agentic AI and where it can actually improve technical workflows. - You work in **mechanical engineering, product design, or CAD-heavy development** and want to understand how AI agents could support iteration, reduce repetitive workflow steps, or improve design-to-analysis handoffs. - You are involved in **simulation, CAE, modeling, or validation** and care about how AI might help with setup, orchestration, interpretation, or routing results into faster decisions. - You build or manage **robotics or advanced manufacturing systems** and need better ways to connect engineering data, performance analysis, and operational choices. - You lead **engineering, R&D, product, or technical strategy** and want a clearer framework for evaluating where agentic AI is useful versus where it is mostly hype. - You are responsible for **digital engineering workflows, tooling, or process improvement** and are looking for practical ideas that span multiple systems rather than optimizing one tool in isolation. - You are technically curious about AI but need the conversation grounded in **real workflow constraints, reliability, and decision quality**, not generic automation claims.