AI emerges as the defining innovation driver at 114% growth in patent filings, reshaping semiconductor R&D investment across every layer of the technology stack
Boston, MA – September 1, 2026 – Anaqua, the leading provider of innovation and intellectual property (IP) management technology and services, today announced key findings from its 2026 Semiconductor Industry Patent Report: AI & Innovation Trends, published earlier today. The report, an analysis of global semiconductor patent activity, reveals a market undergoing structural transformation, driven significantly by the demands of artificial intelligence (AI). While overall semiconductor patenting grew 78% over the last five years, patents at the intersection of AI and semiconductors grew 114%, which is nearly 40 percent faster. AI is not merely influencing semiconductor innovation, it is increasingly defining it at every level of the technology stack – across chip architecture, graphics processing units (GPUs), inference processors and custom accelerators for hyperscalers.
"Semiconductors are the foundation of the technology industry, and their advances unlock entire new categories of innovation," said Toni Njim, chief product officer, Anaqua. "We set out to measure exactly how much artificial intelligence (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."
Using Anaqua's AcclaimIP patent analytics platform to analyze more than 700,000 semiconductor patent filings, the report shows AI's influence on nearly every layer of chip innovation.
Key Findings from Anaqua’s 2026 Semiconductor Industry Patent Report:
AI is a disproportionate, structural driver of semiconductor innovation. It’s not just a cyclical bump. AI-and-semiconductor patents grew 114% versus 78% for the broader combined universe. A closer examination of key semiconductor subcategories across the AI landscape makes it even more evident that AI is driving an outsized impact on the chip market. This isn’t a niche trend: AI has become the primary organizing force behind where semiconductor R&D investment and patent filings are being directed.
NVIDIA’s patent footprint may appear smaller relative to its market dominance because its moat isn’t in hardware. NVIDIA holds just 49 GPU-titled semiconductor patents (ranking #7) and ranks #15 in inference chips. Its durable advantage lies in its CUDA (Compute Unified Device Architecture) software ecosystem, introduced in 2006.
IBM leads where the science is hardest. IBM tops AI-semiconductor crossover filings (794) and analog AI (389), with a footprint concentrated in frontier technologies. These include quantum computing, neuromorphic chips and phase-change memory that encodes neural-network weights directly onto the chip (claiming roughly 14 times better energy efficiency, now reaching commercial deployment via its Spyre accelerator).
Qualcomm is quickly pivoting from mobile into the data center. Long anchored in on-device and edge AI, Qualcomm now ranks #9 in inference (655 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). Its analog work spans neuromorphic mobile circuits and its new AI200/AI250 data-center inference accelerators, which lean on power efficiency and memory capacity as differentiators against competitors.
Samsung is leveraging its memory position into broad AI-hardware leadership. Samsung leads AI architecture patenting (1,194 filings), leads HBM (107 filings), 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. It’s the clearest case of a memory manufacturer converting that base into end-to-end AI-chip strength.
China dominates AI inference patenting by a significant margin and is rising fast in GPUs. Chinese government-affiliated entities lead inference and accelerator filings with 5,387 over five years, far ahead of Samsung’s 1,897, spreading across universities, national labs and state research institutes. The same entities rank third in GPU filings, with startups like Moore Threads and Muxi emerging. This can be read as the result of a chip-sovereignty response to U.S. export restrictions.
Intel is strategically positioned for an AI future. Intel leads GPU semiconductor filings with 188. It ranks second, with 967 filings, in the AI-in-IC (integrated circuits)-architecture space. Intel ranks third with 23 patents that address HBM, and fifth in patents granted (225) at the convergence of AI and analog ICs, ranking 8th in inference semiconductor patents with 792.
Hyperscalers have become silicon designers. Alphabet/Google’s tensor processing unit (TPU) and Microsoft’s Maia accelerator-related patenting appear across nearly every AI-and-semiconductor patenting intersection. This reflects cloud giants designing custom chips for their own workloads rather than buying off the shelf, a vertical-integration shift emerging in terms of who controls AI hardware.
