The hardest problems are human If the tools exist and early production deployments are under way, why has adoption not moved faster? Tim’ s answer is that the limiting factor is rarely the AI model itself. He says:“ It is the surrounding environment: fragmented data, disconnected IT and OT systems and workflows that are not linked across design, simulation, manufacturing and operations.”
Tim explains that many companies“ still lack a unified digital representation of their products, processes or factories, which makes simulation, validation and scaling much harder”. Without that foundation, even capable tools are difficult to deploy consistently across multiple sites, whether the application is on the factory floor or upstream in engineering.
Many of the hardest remaining problems are, in his words,“ human and workflow-driven”. These include setting up simulations, managing studies and interpreting results. The tools to run individual simulations faster exist. What has not yet arrived at scale is the layer of automation that connects those tools into a continuous workflow.
That is where Tim sees the next wave of transformation arriving. He expects autonomous engineering agents, AI systems capable of configuring and launching simulation runs and proposing subsequent steps, to take over more of that orchestration work. As Tim explains:“ Every engineer will orchestrate a team of agent engineers and become limited only by their imagination.”
“ An AI method 10 times faster but 1 % off from the ground truth is useless to a manufacturer”
Tim Costa Vice President and General Manager of Computational Engineering NVIDIA
32 June 2026