When Nvidia Corp Nvidia (NVDA) dropped $2 billion into Synopsys, Inc Synopsys (SNPS), the immediate reaction might have been to file it under "another AI chip deal." But Synopsys' Chief Product Development Officer Shankar Krishnamoorthy says that's missing the point. In an exclusive email interview, he described the investment as a bet on something much bigger: the next decade of engineering itself.
Both companies are set to report earnings after the bell Wednesday, putting their financial results in focus as investors assess the impact of their expanding partnership. But Krishnamoorthy wants investors to think beyond the numbers.
Nvidia's Synopsys Investment Is a Bet on AI Engineering
"The investment reflects a shared vision that the next generation of engineering will be powered by AI, simulation, and holistic system design," Krishnamoorthy said.
That vision is already taking shape. Synopsys and Nvidia are combining their expertise in engineering software and accelerated computing to develop autonomous workflows that help customers tackle increasingly complex design challenges. The collaboration recently produced an end-to-end autonomous verification workflow that, according to Synopsys, "compresses weeks of manual labor into hours of agentic execution," addressing one of the most time-consuming stages of chip verification.
But the larger objective isn't just to design chips faster. It's to rethink how products are engineered from concept to completion.
Synopsys Sees AI Replacing Costly Physical Prototypes
Krishnamoorthy believes one of the biggest shifts will occur well before products reach the factory floor. "Customers can no longer afford the time and cost of creating and testing physical prototypes of their products, from turbine engines to tennis racquets," he said.
Instead, AI models, simulation tools, and digital engineering workflows are increasingly allowing companies to validate designs virtually before committing to expensive physical testing. That's why the convergence of AI and engineering matters beyond the semiconductor industry. Krishnamoorthy said combining Synopsys' engineering software with Nvidia's AI infrastructure is helping accelerate "the industry's transition toward AI-powered, silicon-to-systems design and development."
The phrase "silicon-to-systems" reflects a broader ambition: using AI not just to optimize individual chips, but to improve the design of complete products by integrating hardware, software, and physics into a unified engineering workflow.
Why Investors Should Watch AI Engineering, Not Just AI Chips
Nvidia has become synonymous with the AI infrastructure boom, but Krishnamoorthy suggests the next phase of growth may be driven by the software that enables engineers to build AI-powered products faster and more efficiently.
Rather than viewing the investment as another semiconductor deal, investors may want to see it as a signal that AI is moving deeper into industrial engineering, product development, and simulation—areas that have traditionally relied on lengthy design cycles and costly physical prototypes.
If that transition unfolds as Synopsys expects, the biggest winners may not simply be the companies building AI chips, but those enabling an entirely new way of designing products.
For investors, the trend to watch is whether AI-powered engineering platforms can translate today's strategic vision into measurable productivity gains and broader enterprise adoption over the next several years.
