Nvidia Corp (NASDAQ:NVDA) and Synopsys, Inc (NASDAQ:SNPS) are set to report earnings after the bell Wednesday, putting the companies’ financial results in focus as investors assess the impact of their expanding AI partnership. Nvidia’s $2 billion investment in Synopsys may signal a bet on something much bigger than electronic design automation (EDA) software.
In an exclusive email interview with Benzinga, Synopsys Chief Product Development Officer Shankar Krishnamoorthy said the investment reflects a broader shift toward AI-powered engineering—one that could eventually change how everything from semiconductors to turbine engines is designed.
Nvidia’s Synopsys Investment Is a Bet on AI Engineering
Krishnamoorthy said the strategic value of Nvidia’s investment extends beyond capital, describing it as a reflection of where engineering is headed over the next decade.
“The investment reflects a shared vision that the next generation of engineering will be powered by AI, simulation, and holistic system design,” he told Benzinga.
That vision is already shaping the partnership between the two companies. According to Krishnamoorthy, Synopsys and Nvidia are combining 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.
The larger objective, however, is not simply 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, according to Synopsys, is 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.
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