Explainable AI Patent Landscape 2026
Explainable AI Patent Landscape in 2026
Explainable AI is in an active growth phase, with filings expanding rapidly and India emerging as the dominant filing jurisdiction. The applicant field is moderately concentrated, with academic institutions and patent assertion vehicles sharing the top tier alongside established technology companies.
Indian universities and global tech firms share the top tier
SR University leads the IBM, operating through multiple entities, ranks third among named applicants with 95 patent families under its primary listing.
The top five filers account for 24% of the combined output of the hundred largest filers, indicating moderate concentration. A clear tier gap separates the top two academic filers from the next cluster of corporate and portfolio applicants, suggesting that research institutions currently drive volume while commercial players pursue more selective, strategically targeted filings.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | SR University | 151 | |
| 2 | Vellore Institute of Technology | 140 | |
| 3 | International Business Machines Corporation | 95 | |
| 4 | Strong Force VCN Portfolio 2019 LLC | 93 | |
| 5 | UMNAI Ltd. | 87 | |
| 6 | Fujitsu Ltd. | 84 | |
| 7 | Strong Force TX Portfolio 2018 LLC | 46 | |
| 8 | Telefonaktiebolaget LM Ericsson | 44 | |
| 9 | CVR College of Engineering | 43 | |
| 10 | SR University Warangal | 42 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | Easwari Engineering College | 41 | |
| 12 | Koneru Lakshmaiah Education Foundation | 38 | |
| 13 | NOIDA INST OF ENG & TECH | 38 | |
| 14 | Siemens AG | 37 | |
| 15 | Microsoft Technology Licensing LLC | 35 | |
| 16 | Kalinga University Raipur | 34 | |
| 17 | Intel Corporation | 33 | |
| 18 | Nozomu Kubota | 33 | |
| 19 | Robert Bosch GmbH | 32 | |
| 20 | Saveetha Engineering College | 28 |
The dual presence of Indian universities and US-based patent assertion vehicles (Strong Force VCN Portfolio 2019 LLC and Strong Force TX Portfolio 2018 LLC) in the top ten points to two structurally distinct competitive pressures: academic publication-driven IP and assertion-oriented portfolio aggregation. Technology companies such as IBM, Fujitsu, and Siemens occupy a third tier, filing fewer but likely higher-commercial-value families.
Filings from the most recent 18–24 months are under-counted due to publication lag and should not be interpreted as a slowdown in activity. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Rapid annual growth and an AI-core technology mix with broad application spread
The filing trend reveals sustained expansion from 2017 onward, while the technology composition shows a dominant AI-methods core radiating into healthcare, business process, and image-recognition applications.
Annual filing trend
Filings grew from a small base in 2017, accelerating sharply through 2021 and maintaining high volume through 2024. The 2025–2026 data points are subject to publication lag and understate true activity; the growth trajectory should be read from the 2017–2024 window, which shows a 69% recent-period expansion.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G06N (Computing based on AI models) dominates the IPC mix by a wide margin, confirming that foundational model-interpretability methods are the core filing area. G06F (Electric digital data processing) and G06Q (Business, commerce and admin data processing) form a secondary layer, with G16H (Healthcare informatics) and A61B (Diagnosis and surgery) together signalling that clinical AI explainability is already a substantial sub-field. Lower-volume branches spanning robotics, wireless networks, and bioinformatics reflect the cross-domain reach of the technology.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Explainable Artificial Intelligence Framework System
A system and method are provided for generating domain-specific explainable recommendations through interpretable machine learning models. The system features an explainable artificial intelligence (AI) framework that combines decision trees and Bayesian inference for recommendation generation, while leveraging Shapley Additive exPlanations (SHAP) values to… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Intelligent vibration digital twin systems and met… | 690 |
| 2 | Method for constructing segmentation-based predict… | 439 |
| 3 | Control tower and enterprise management platform w… | 329 |
| 4 | Robot Fleet Management for Value Chain Networks | 322 |
| 5 | Composite symbolic and non-symbolic artificial int… | 321 |
| 6 | Configurable Machine Learning Method Selection and… | 279 |
| 7 | Artificial intelligence selection and configuration | 272 |
| 8 | Interpretable deep learning framework for mining a… | 247 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents.
What the patent structure means for R&D investment
The combination of a growth-stage lifecycle, moderate concentration, active collaboration among large corporate players, and India as the lead jurisdiction creates a distinctive competitive environment with both openings and risks for new entrants.
Active growth stage with no sign of saturation
The field is classified as Growth, with annual filings still rising and recent-window expansion of 69%. The technology is past its earliest experimental phase but has not yet entered the crowded plateau typical of mature domains. This window typically offers the best return on foundational method patents before the landscape consolidates.
Growth stageModerate concentration with a split between academia and industry
The top five filers hold 24% of the hundred largest filers’ combined output — meaningful but not dominant. Indian academic institutions occupy the top two positions by volume, while corporate and portfolio filers cluster in the middle tier. An R&D team entering now faces volume competition from universities but less incumbent lock-in from commercial players than in more mature AI sub-fields.
Moderate concentrationIBM leads co-filing activity, partnering with MIT and internal entities
The most active co-filing pair is IBM (via its Chinese entity) and MIT, with four joint families on record. IBM also collaborates with IBM Deutschland GmbH (two families), and Fujitsu co-filed with BG Negev Technologies and Applications (one family). Collaborative activity is currently limited to a small set of corporate-academic pairs, leaving substantial room for new alliances, particularly in clinical and industrial XAI applications.
Limited co-filingIndia dominates filings; the US is the leading commercial jurisdiction
India accounts for the largest share of patent records among all jurisdictions, driven by high-volume university filings. The United States follows as the primary commercial jurisdiction, with China, WIPO PCT, and the EPO forming the next tier. For a commercially oriented XAI portfolio, US and PCT filings remain the most strategically critical, while the Indian volume reflects academic output that may carry different enforceability characteristics.
India-led, US commercialGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
| Applicant | Collaborator | Co-filings |
|---|---|---|
| International Business Machines Corporation | Massachusetts Institute of Technology | 4 |
| International Business Machines Corporation | IBM China Co., Ltd. | 2 |
| International Business Machines Corporation | IBM DEUTSCHLAND GMBH | 2 |
| Fujitsu Ltd. | BG Negev Technologies and Applications Ltd. | 1 |
Co-filing pairs, ranked by the number of jointly-filed patent families.
Academic volume leaders and a resurgent patent portfolio player at the top
SR University and Vellore Institute of Technology lead by patent family count, both classified as new entrants to the ranked list. Strong Force VCN Portfolio 2019 LLC shows the strongest recent momentum among established filers, while IBM’s trajectory has declined from its prior level.
SR University
SR University tops the ranking with 151 patent families and is classified as a new entrant, meaning its entire portfolio has been built recently. Its technology focus is concentrated on neural-network AI methods (G06N 3) and general machine-learning computing (G06N 20), with a meaningful secondary position in healthcare informatics (G16H 50). This academic-institution profile suggests volume-oriented filing driven by research output rather than commercial enforcement strategy.
families: 151Strong Force VCN Portfolio 2019 LLC
Strong Force VCN Portfolio 2019 LLC holds 93 patent families and shows the strongest recent-period momentum among top filers at +114% versus its prior three-year window. Its technology emphasis falls on business and commerce data processing (G06Q 10) alongside core AI computing classes (G06N 20 and G06N 3), a profile consistent with a patent assertion vehicle targeting enterprise AI deployments. This trajectory makes it a structurally important player to monitor for Freedom-to-Operate purposes.
families: 93| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| SR University | 1 | ▲ new entrant |
| Vellore Institute of Technology | 1 | ▲ new entrant |
| International Business Machines Corporation | 27 | ▼ -54% |
| Strong Force VCN Portfolio 2019 LLC | 62 | ▲ +114% |
| UMNAI Ltd. | 17 | ▼ -76% |
| Fujitsu Ltd. | 45 | ▲ +32% |
| Strong Force TX Portfolio 2018 LLC | 21 | ▬ 0% |
| Telefonaktiebolaget LM Ericsson | 22 | ▲ +10% |
Under-served adjacent branches worth monitoring
Several IPC branches sit at meaningful patent-record volumes relative to the dominant G06N core but carry lower filer density, suggesting areas where differentiated XAI work has begun but has not yet attracted broad competitive attention.
G16H · Healthcare informatics
Healthcare informatics is the fourth-largest branch by record count and holds an 8% share among the top whitespace candidates, yet filer density relative to the dominant AI-methods class remains low. Clinical explainability — producing interpretable outputs for diagnostic models — faces strong regulatory pull from evolving medical AI guidelines, creating a realistic entry path for organizations with both ML and clinical domain expertise. The overlap with A61B (Diagnosis and surgery) reinforces the case for coordinated filing across both classes.
Search this in Eureka →G06V · Image/video recognition
Image and video recognition accounts for a 4% share among the leading adjacent branches and is the primary application domain for computer-vision XAI techniques such as saliency maps and attention visualization. Despite widespread industrial use in quality control, autonomous vehicles, and medical imaging, patent density in this branch is comparatively sparse relative to the core G06N class. Entrants with proprietary visualization or attribution methods could establish defensible positions here before the sub-field attracts broader filing activity.
Search this in Eureka →How leading filers differ across technology routes
Strength of each leader across the main technology routes.
| Player | G06N 3 · Computing based on AI models | G06N 20 · Computing based on AI models | G06N 5 · Computing based on AI models | G16H 50 · Healthcare informatics | G06Q 10 · Business, commerce & admin data processing |
|---|---|---|---|---|---|
| SR University | Strong · 112 | Strong · 62 | Moderate · 43 | Moderate · 45 | Emerging · 20 |
| Vellore Institute of Technology | Strong · 99 | Strong · 65 | Moderate · 20 | Moderate · 39 | Emerging · 15 |
| Strong Force VCN Portfolio 2019 LLC | Strong · 54 | Strong · 71 | Moderate · 32 | Absent | Strong · 77 |
| International Business Machines Corporation | Strong · 33 | Strong · 60 | Strong · 52 | Absent | Absent |
| UMNAI Ltd. | Strong · 75 | Absent | Strong · 39 | Absent | Absent |
| Fujitsu Ltd. | Strong · 35 | Strong · 32 | Strong · 45 | Absent | Absent |
| Strong Force TX Portfolio 2018 LLC | Strong · 35 | Strong · 42 | Moderate · 18 | Absent | Moderate · 15 |
Frequently asked questions
The landscape covers 5,644 patent families in scope globally, spanning academic institutions, technology corporations, and patent portfolio entities.
SR University leads the ranking with 151 patent families, followed by Vellore Institute of Technology with 140. Both are Indian academic institutions classified as new entrants to the ranked list.
India is the leading jurisdiction by patent-record count, reflecting high-volume filing by Indian universities. The United States is the primary commercial jurisdiction, followed by China, WIPO PCT, and the EPO.
The field is in a Growth stage. The most recent comparable window shows 69% expansion. Filing volumes from 2025 onward are under-counted due to publication lag and should not be read as a plateau.
G06N (Computing based on AI models) is by far the dominant IPC class. Secondary activity concentrates in G06F (Electric digital data processing), G06Q (Business and commerce), G16H (Healthcare informatics), and G06V (Image and video recognition).
Healthcare informatics (G16H) and image/video recognition (G06V) have meaningful activity levels but comparatively low filer density relative to the core AI-methods class, making them adjacent branches where differentiated filing positions may still be achievable.
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Disclaimer. This page is generated from PatSnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. PatSnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.