Artificial intelligence has spent the past two years becoming a better assistant. Synopsys, Inc. (NASDAQ:SNPS) believes the next phase is something fundamentally different: AI that no longer assists engineers, but increasingly manages entire engineering workflows on its own.
In an exclusive email interview with Benzinga, Synopsys Chief Product Development Officer Shankar Krishnamoorthy said investors should look beyond today’s AI copilots and task-specific assistants. The more important shift, he said, is the emergence of autonomous engineering—a transition that could reshape how semiconductors and other complex products are designed.
Synopsys Says AI Is Moving Beyond Copilots
For much of the generative AI boom, software companies have focused on AI assistants that help users complete individual tasks. Krishnamoorthy believes that phase is already giving way to something more ambitious.
“The most important trend to watch is the transition from AI-assisted to autonomous engineering,” he told Benzinga.
Rather than helping engineers solve isolated problems, AI is beginning to coordinate entire product development workflows. According to Krishnamoorthy, “AI will orchestrate end-to-end engineering workflows across design, verification, simulation, and system validation.”
That marks a significant shift in how AI creates value. Instead of acting as another software tool inside an engineer’s workflow, autonomous AI increasingly becomes the workflow itself, coordinating multiple stages of product development while allowing engineers to focus on higher-value innovation.
Autonomous Engineering Could Become the Next Competitive Advantage
The transition is being driven by a growing engineering challenge rather than advances in AI alone.
As chip designs and intelligent systems become more sophisticated, Krishnamoorthy said engineering teams are managing unprecedented complexity across hardware, software and physics. In response, “organizations are moving beyond point solutions and task-specific AI assistants toward autonomous engineering workflows that can help manage this complexity at scale.”
That evolution, he said, will ultimately separate industry leaders from the rest.
“The companies that successfully combine agentic AI, accelerated computing, and multiphysics simulation will be best positioned to improve engineering velocity, deliver first-time right silicon, and advance innovation.”
While “first-time right silicon” is an industry term for producing a chip that works correctly without costly redesigns, the broader message is straightforward: companies that can automate more of the engineering process may be able to innovate faster while reducing development costs and delays.
Why Investors Should Watch Autonomous Engineering
The AI conversation has largely centered on chatbots, coding assistants and productivity software. Synopsys argues the next competitive battleground lies deeper inside enterprise engineering, where AI is evolving from an assistant into an orchestrator.
That shift is particularly relevant as Synopsys is set to report earnings after the market closes Wednesday. Investors will be looking not only for evidence that demand for AI-enabled engineering software remains strong, but also for signs that customers are adopting more autonomous workflows rather than standalone AI features.
If Synopsys’ vision proves correct, the next winners in AI may not simply be the companies building more capable models. They could be the companies embedding those models into end-to-end engineering systems that redesign how products are conceived, tested and brought to market.
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