Manufacturing is living through one of the most consequential periods in its history. Markets are shifting, supply chains are evolving, and customer expectations are rising. Decades from now, we’ll look back and say, “remember when everything changed?” What creates stability during these times is a connected, intelligent foundation that brings data, people, and processes together. At the center of this transformation is AI, which isn’t just another feature. It’s a new operating model for how products are designed, engineered, and delivered. But transformation at this scale doesn’t arrive in a single leap. It builds. At Autodesk, we frame that journey in three stages of customer outcomes:
The foundation for this AI work? It’s data. Data defines how well teams collaborate, how confident decisions are made, and how effectively AI can deliver value. And Fusion’s data platform has rapidly evolved to support exactly that. Once your product data is structured and connected inside Fusion, the next step is making that data available to the rest of the manufacturing ecosystem Fusion now exposes a growing set of desktop and cloud APIs that give teams access to product and manufacturing data. Desktop APIs extend the Fusion client and automate workflows inside the modeling environment, while cloud APIs can help teams access and query supported BOM-level data without moving entire datasets. Together, these capabilities help Fusion support a digital thread across engineering and enterprise systems. The bigger shift is AI agents interacting directly with software. To support this, we have Fusion MCPs. Together, APIs connect systems, and MCPs enable agents to act. This is where the call to action becomes real: you’re no longer just integrating tools. You’re defining how AI is incorporated in engineering workflows. One of the first places you’ll see this come to life is Autodesk Assistant. Instead of assisting with individual steps, Assistant analyzes the constraints, dependencies, and decisions that shape the design and manufacturing process, helping teams make better decisions, coordinate across tools and disciplines, and move from insight to action while keeping professionals in control. This can help teams reduce manual coordination and potentially reduce costs down the line. Then we move to systems-level automation: using Assistant in Fusion to help teams understand how changes in one part of the product development and manufacturing process can affect others. Over time, this can help manufacturers respond more quickly to supply changes or design updates by surfacing relevant context and recommended next steps within connected workflows. The goal is not to remove human oversight, but to give teams better information to make decisions across the systems that shape how products are designed and manufactured. APIs, MCPs, and Autodesk Assistant are building blocks. What matters now is reliability and seamless integration into existing workflows. The companies that win in this next era won’t be the ones experimenting with AI, but the ones applying it to real problems inside real workflows at scale. Driving better decisions and measurable outcomes without added complexity.