Neurosymbolic AI Market Size, Share, Opportunities, And Trends By Application (Knowledge-Based AI Systems, Decision Making, Natural Language Processing, Robotics, Planning And Scheduling), By End-User (Banking, Financial Services, And Insurance (BFSI), Retail And E-Commerce, Automotive & Transportation, Healthcare, Others), And By Geography – Forecasts From 2025 To 2030
Description
Neurosymbolic AI Market Size:
The neurosymbolic AI market is expected to see steady growth over the forecasted period.
The market for neurosymbolic AI is witnessing growth, this is because it can create systems that are more intelligent and data-efficient. This is accomplished by fusing the benefits of symbolic reasoning and neural networks. Symbolic AI provides interpretability, knowledge representation, and logic-based reasoning. Neural networks are capable of recognising patterns in unstructured data, such as text or images. Neurosymbolic systems can apply rules and learn from data. Neurosymbolic AI makes decisions more flexible and transparent. The main drawbacks of purely neural models are their poor explainability and data complexity. This problem is solved by neurosymbolic AI. In fields where learning and reasoning are essential, such as robotics, natural language comprehension, and autonomous systems, neurosymbolic AI is becoming popular.
Neurosymbolic AI Market Overview & Scope:
The neurosymbolic AI market is segmented by:
- Application: Knowledge-based AI systems are expected to have a substantial share of the neurosymbolic AI market. This is because they provide the structured reasoning and explicit logic necessary to complement neural network capabilities. These systems use ontologies, knowledge graphs, and rule-based engines to represent domain-specific knowledge, enabling AI models. Industries like healthcare, finance, and legal tech benefit from this hybrid approach, where regulatory compliance and transparency are critical.
- End User:.Retail and e-commerce hold a considerable share of the neurosymbolic AI market. This is because they need strong, intelligent systems that are accurate as well as explainable and data-efficient. Neurosymbolic AI allows retailers to draw customer insight from neural networks with business rules and symbolic reasoning. They deliver transparent recommendations, personalised marketing, and fraud detection
- Region: The Asia-Pacific Neurosymbolic AI market is witnessing strong growth. This is due to rapid digital transformation and increasing demand for explainable and data-efficient AI systems. Countries like China and India are adopting neurosymbolic AI in various sectors, such as finance, healthcare, education, and autonomous systems.
Top Trends Shaping the Neurosymbolic AI Market:
1. Integration into Industrial AI Systems: A trend in the neurosymbolic AI market is the integration into industrial AI systems. Neurosymbolic AI is being adopted in real-world applications where reliability, traceability, and reasoning are critical. They are used in industries such as manufacturing, automotive, and aerospace.
2. Growing Role in Explainable AI (XAI) Initiatives- Another significant trend is the growing role of explainable AI initiatives. Their ability to provide human-understandable logic behind decisions makes them an important part of the AI market. They are used in sectors like healthcare, law and public policy.
3. Academic-Industry Collaborations and Open Frameworks-There has been an increase in academic-industry collaborations in the neurosymbolic AI market. This is to develop frameworks, benchmarks, and open-source tools for neurosymbolic AI.
Neurosymbolic AI Market Growth Drivers vs. Challenges:
Drivers:
- Rising demand in different sectors: One of the key drivers of neurosymbolic AI is the increasing rise in demand in different sectors. As AI systems are deployed in sectors like healthcare and finance, there is a growing demand for transparency and interpretability. According to the FBI’s report on “Annual Internet Crime Report 2024”, the internet crime losses exceeded $16 billion, showing an increase of 33% in losses from 2023, and people over the age of 60 suffered the most losses at approximately $5 billion. The most complaints were reported from California, Texas, and Florida. Investment fraud cost around $6,5 billion in 2024.
Reducing Data Dependency: Another key driver of the neurosymbolic AI market is the reduction in data dependency. Neurosymbolic uses prior knowledge and rules with the help of symbolic structures to reduce dependency on large datasets. According to Arxiv, Marconato in the year 2023 introduced a neural symbolic continuous learning method. This method uses features from visual data, and it then uses a separate neural network to extract high-level concepts from these features.
Challenges:
- Complexity of Integration Between Symbolic and Neural Systems: One of the major challenges of the neuro-symbolic AI market is the technical complexity of integrating symbolic reasoning with neural networks. Symbolic AI relies on explicit rules and logic, while neural networks learn patterns from data. Creating systems that combine the generalisation power of neural models with the logical structure and interpretability of symbolic systems is complex. This challenge decreases development cost and increases latency. Additionally, there is still a lack of standardised frameworks, tools, and benchmarks, making it difficult for researchers and companies to adopt neurosymbolic methods at scale.
Neurosymbolic AI Market Regional Analysis:
- USA: The U.S. is the global leader; it has a strong presence of tech giants like IBM, Google, Microsoft, and NVIDIA, which are investing heavily in neuro-symbolic research and real-world applications.
- China: China is a major player in the Asia-Pacific region; it has massive national investments in AI, including neurosymbolic systems.
- Germany: Germany is contributing significantly to the region. It has strong industry-academic collaboration in manufacturing, robotics and autonomous systems
- UK: The UK is the home to DeepMind, which is the world’s most advanced AI lab. The government is also providing support through the UK AI Strategy and strong research programs at Oxford, Cambridge, and Imperial College London.
Neurosymbolic AI Market Competitive Landscape:
The market has many notable players, including Kognitos, IBM, Unlikely AI, Robert Bosch GmbH, Franz, Inc., Google, among others.
- Product launch: In June 2025, Kognitos announced the launch of the neurosymbolic AI platform. Kognitos had also secured $25 million in its Series B funding round. This AI platform helps businesses to address automation use cases, consolidate their AI tools, and reduce technology sprawl.
Product Launch: In July 2024, Mendel announced the launch of its neuro-symbolic AI. Mendel’s Clinical AI system can automate the identification of patient cohorts from unstructured and structured EMR, and it has outperformed GPT-4. This AI will help automate the identification of patient reports from unstructured and structured EMR.
Neurosymbolic AI Market Segmentation:
By Application
- Knowledge-based AI Systems
- Decision Making
- Natural Language Processing
- Robotics
- Planning and Scheduling
- Banking, Financial Services, and Insurance (BFSI)
- Retail and E-Commerce
- Automotive & Transportation
- Healthcare
- Others
By Region
Table Of Contents
1. EXECUTIVE SUMMARY
2. MARKET SNAPSHOT
2.1. Market Overview
2.2. Market Definition
2.3. Scope of the Study
2.4. Market Segmentation
3. BUSINESS LANDSCAPE
3.1. Market Drivers
3.2. Market Restraints
3.3. Market Opportunities
3.4. Porter’s Five Forces Analysis
3.5. Industry Value Chain Analysis
3.6. Policies and Regulations
3.7. Strategic Recommendations
4. TECHNOLOGICAL OUTLOOK
5. NEUROSYMBOLIC AI MARKET BY APPLICATION
5.1. Introduction
5.2. Knowledge-based AI Systems
5.3. Decision Making
5.4. Natural Language Processing
5.5. Robotics
5.6. Planning and Scheduling
6. NEUROSYMBOLIC AI MARKET BY END-USER
6.1. Introduction
6.2. Banking, Financial Services, and Insurance (BFSI)
6.3. Retail and E-Commerce
6.4. Automotive & Transportation
6.5. Healthcare
6.6. Others
7. NEUROSYMBOLIC AI MARKET BY GEOGRAPHY
7.1. Introduction
7.2. North America
7.2.1. USA
7.2.2. Canada
7.2.3. Mexico
7.3. South America
7.3.1. Brazil
7.3.2. Argentina
7.3.3. Others
7.4. Europe
7.4.1. United Kingdom
7.4.2. Germany
7.4.3. France
7.4.4. Italy
7.4.5. Spain
7.4.6. Others
7.5. Middle East & Africa
7.5.1. Saudi Arabia
7.5.2. UAE
7.5.3. Others
7.6. Asia Pacific
7.6.1. China
7.6.2. India
7.6.3. Japan
7.6.4. South Korea
7.6.5. Thailand
7.6.6. Others
8. COMPETITIVE ENVIRONMENT AND ANALYSIS
8.1. Major Players and Strategy Analysis
8.2. Market Share Analysis
8.3. Mergers, Acquisitions, Agreements, and Collaborations
8.4. Competitive Dashboard
9. COMPANY PROFILES
9.1. Kognitos
9.2. IBM
9.3. Unlikely AI
9.4. Robert Bosch GmbH
9.5. Franz, Inc
9.6. Google
10. APPENDIX
10.1. Currency
10.2. Assumptions
10.3. Base and Forecast Years Timeline
10.4. Key benefits for the stakeholders
10.5. Research Methodology
10.6. Abbreviations
Companies Profiled
Kognitos
IBM
Unlikely AI
Robert Bosch GmbH
Franz, Inc
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