// TOM'S HARDWARE US — HARDWARE & GADGET
AI's chipmaking frontier may face patent infringement hurdles as autonomous tools take over
As well as fuelling demand for hardware, AI is also helping redesign it to be more efficient and to tackle harder tasks.
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Put to work on different tasks, AI can do a good many specialist skills that even just a few months ago wouldn’t have been thought possible. AI is beginning to take on some of the work required to design the chips that power AI, way beyond simple optimisation. But that brings a potentially expensive problem: what happens if an AI ends up generating a design that infringes somebody else's patent, which then ends up in thousands of chips rolling off production lines? Tom's Hardware Premium spoke with experts like Domenec Forte, professor of electrical and computer engineering at the University of Florida, and Simon Moore, professor of computer engineering at the University of Cambridge, to learn more about a looming issue that could broadly impact the AI chip design market.
This week, Synopsys announced a suite of AgentEngineer tools capable of carrying out long-running tasks that could verify and implement chips, as well as planning analog design and manufacturing. The company said it had more than 50 customer engagements already underway, and planned to offer the tech for general availability by the end of the year.
Synopsys isn't alone in discovering the ability of AI to do such tasks. Competitor Cognichip says its ACI platform can generate specifications and RTL, then automatically produce verification plans and testbenches. And in China, Empyrean Technology recently claimed an AI agent reduced the time taken to complete one circuit layout task from four weeks to one. Even the big AI labs are getting in on the act: OpenAI says its models helped it and Broadcom develop Jalapeño, its first custom inference chip, from initial design to tape-out in just nine months.
It all poses difficult questions for the chip design industry – though not just about whether the sector will remain strong. It’s also about whether AI is a suitable replacement for human ingenuity. The industry relies heavily on intellectual property, and it’s not yet clear what happens when an AI designs something that somebody else already owns. Rather than designing every component of a chip from scratch, companies routinely license processor architectures, controllers, and other memory technologies rather than reinvent the wheel. Arm alone generated nearly $5 billion in its 2026 financial year, which came roughly half from licensing and other revenue and half from the royalties on that. Synopsys makes money that way too, selling a substantial portfolio of "silicon-proven" IP alongside its chip design software.
But by putting AI to the task, some of those blocks could become far easier to create – and working out where they came from far harder. "It mostly amplifies existing problems," said Domenec Forte, professor of electrical and computer engineering at the University of Florida, whose research includes AI-enabled chip-design tools and semiconductor IP protection, in written comments to Tom’s Hardware Premium. "AI can spread a copied design or infringed patent across thousands of chips before anyone notices and without anyone even intending it,” he said.
Copying wouldn’t be as blatant as feeding an Arm core or another piece of proprietary RTL directly into a model. Instead, AI’s skill is in ingesting huge amounts of literature from academic papers and patent applications, then constructing lookalike designs. And in a space where power constraints, performance challenges, and a limited physical area all combine alongside mandated standards all have to follow, there are only a finite number of feasible designs that AI can reach quicker – inadvertently copying others’ homework. "Even a circuit that adds two numbers draws from a well-documented catalogue of textbook designs," said Forte. "Ask for the fastest one, and you'll likely land o