Artificial intelligence (AI) is fundamentally driving the transformation of the semiconductor industry. Rather than merely influencing chip development, AI is defining innovation across the entire stack – chip architecture, graphics processing units (GPUs), inference processors and custom hyperscaler accelerators, among many others.
Newly released findings from Anaqua’s 2026 Semiconductor Industry Patent Report: AI & Innovation Trends quantify the shift. Global semiconductor patenting grew 78% over the past five years. Patents specifically combining AI and semiconductors surged 114% – outpacing broader industry growth by nearly 40%.
“Semiconductors are the foundation of the technology industry, and their advances unlock entire new categories of innovation,” said Toni Njim, chief product officer at Anaqua. “We set out to measure exactly how much AI is driving that foundation forward, and the answer is clear: AI isn’t just influencing semiconductor innovation anymore. It’s defining it, and the scale of that impact is astounding.”
Some of the Report’s Key Insights
- Hyperscalers have become silicon designers. Patenting tied to Alphabet/Google’s tensor processing unit (TPU) and Microsoft’s Maia accelerator appears across nearly every AI-and-semiconductor intersection – evidence of cloud giants designing custom chips for their own workloads rather than buying off the shelf, a shift quietly changing who controls AI hardware.
- IBM leads where the science is hardest, topping AI-semiconductor crossover filings with 794 and analog AI with 389 patent filings. Its footprint concentrates in frontier technologies: quantum computing, neuromorphic chips and phase-change memory that encodes neural-network weights directly onto the chip, claiming roughly 14 times better energy efficiency and now reaching commercial deployment through its Spyre accelerator.
- At first glance, NVIDIA’s patent footprint looks modest compared to its market dominance, and the reason is strategic. The company holds 49 GPU-titled semiconductor patents, ranking seventh, and sits at #15 in inference chip patent filings. Its durable advantage lies elsewhere – in the CUDA (Compute Unified Device Architecture) software ecosystem it introduced in 2006. Its moat is code, not silicon.
- Samsung is converting its memory position into broad AI-hardware leadership. It leads AI architecture patenting with 1,194 filings, leads high-bandwidth memory (HBM) with 107, and ranks second in both inference and analog AI, spanning neural processing units (NPUs), processing-in-memory (PIM) and its Exynos system-on-chip (SoC) line.
- Long anchored in on-device and edge AI, Qualcomm now ranks #9 in inference chips (655 patent filings, notably with none granted five years ago) and shows some of the steepest growth in the report, up 186% in AI architecture (252 filings), with a rising GPU position (#4, 134 filings).
- China dominates AI inference patenting. Government-affiliated entities – universities, national labs and state research institutes – lead inference and accelerator filings with 5,387 patents over five years, far ahead of Samsung’s 1,897 patent filings in second place, and ranks third in GPUs, with startups such as Moore Threads and Muxi emerging.
Anaqua’s Semiconductor Industry Patent Report draws on 713,755 semiconductor-related filings over the latest five-year period, including more than 174,000 in the most recent 12 months alone. The analysis was built with Anaqua’s AcclaimIP patent analytics platform, accessed between May and June of 2026. A free copy of the report is available at https://go.anaqua.com/2026-semiconductor-patent-report.
