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시장보고서
상품코드
1841555
블록체인 AI 시장 : 세계 산업 규모, 점유율, 동향, 기회, 예측 - 구성요소별, 기술별, 최종 이용 산업별, 지역별, 경쟁별(2020-2030년)Blockchain AI Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Technology, By End-User Industry, By Region & Competition, 2020-2030F |
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세계의 블록체인 AI 시장은 2024년에 6억 1,276만 달러로 평가되었으며, 예측 기간 동안 CAGR은 18.86%로, 2030년까지 17억 4,340만 달러에 달할 것으로 예측됩니다.
| 시장 개요 | |
|---|---|
| 예측 기간 | 2026-2030년 |
| 시장 규모 : 2024년 | 6억 1,276만 달러 |
| 시장 규모 : 2030년 | 17억 4,340만 달러 |
| CAGR : 2025-2030년 | 18.86% |
| 급성장 부문 | 자연어 처리 |
| 최대 시장 | 북미 |
블록체인 인공지능 시장이란 블록체인 기술과 인공지능을 통합하여 안전하고 투명한 분산형 데이터 처리, 공유, 의사결정을 가능하게 하는 시장을 말합니다. 이 융합은 블록체인이 가진 불변의 원장과 분산형 구조, 인공지능이 가진 대량의 데이터를 처리하고 실용적인 지식을 추출하는 능력이라는 두 기술의 강점을 활용하는 것입니다. 이 시장에서 인공지능은 네트워크 혼잡을 예측하고, 합의 메커니즘의 에너지 소비를 최적화하고, 스마트 계약을 자동화하여 블록체인의 효율성을 향상시킬 수 있으며, 블록체인은 데이터 검증 가능성을 보장하고, 분산형 데이터 소스를 통해 데이터 편향성을 줄이고 분산된 데이터 소스를 통해 편향성을 줄이고 의사결정 알고리즘의 투명성을 높여 인공지능의 능력을 강화합니다. 데이터 보안에 대한 수요 증가, 비즈니스 프로세스 자동화 도입 확대, 탈중앙화 금융 및 디지털 ID 관리의 부상 등을 배경으로 향후 몇 년 동안 이 시장은 크게 성장할 것으로 예상됩니다. 금융 서비스, 헬스케어, 물류, 공급망 부문은 부정행위 탐지, 안전한 데이터 공유, 효율적인 자산 추적을 위해 블록체인 인공지능 솔루션을 사용하고 있으며, 가장 먼저 도입한 기업 중 하나입니다.
또한, 기업이 인공지능을 통한 의사결정의 신뢰성을 높이는 데 집중할수록 블록체인의 추적성과 위변조 방지 기록의 가치는 점점 더 높아질 것으로 보입니다. 정부 및 규제 기관도 안전한 디지털 ID 인증, 공중 보건 데이터 추적, 국경 간 컴플라이언스 준수에 이러한 기술을 활용하고자 합니다. 웹3.0과 분산형 애플리케이션의 등장은 블록체인 환경에서 작동하는 확장 가능하고 안전한 인공지능 모델에 대한 수요를 더욱 증가시킬 것입니다. 엣지 컴퓨팅, 협업 학습, 토큰화된 데이터 시장의 급속한 발전과 함께 블록체인 인공지능은 차세대 데이터 생태계의 중요한 원동력이 될 것으로 보입니다. 주요 기술 제공업체와 블록체인 플랫폼은 상호운용성, 프라이버시, 신뢰 문제를 해결하기 위한 하이브리드 솔루션을 출시하기 위해 점점 더 많은 파트너십을 체결하고 있습니다. 이 분야에 대한 벤처 캐피털의 투자와 연구개발이 가속화됨에 따라 시장은 연평균 복리 성장률로 강력한 성장세를 보이며 새로운 수익원을 창출하고 업계 전반의 전통적인 비즈니스 모델을 변화시킬 것으로 예상됩니다.
데이터 보안 및 무결성 강화
블록체인과 인공지능 시스템 통합의 복잡성
블록체인과 인공지능 통합의 복잡성
The Global Blockchain AI Market was valued at USD 612.76 million in 2024 and is expected to reach USD 1743.40 million by 2030 with a CAGR of 18.86% during the forecast period.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 612.76 Million |
| Market Size 2030 | USD 1743.40 Million |
| CAGR 2025-2030 | 18.86% |
| Fastest Growing Segment | Natural Language Processing |
| Largest Market | North America |
The Blockchain Artificial Intelligence Market refers to the integration of blockchain technology with artificial intelligence to enable secure, transparent, and decentralized data processing, sharing, and decision-making. This convergence leverages the strengths of both technologies-blockchain's immutable ledger and decentralized structure, and artificial intelligence's ability to process large volumes of data and extract actionable insights. In this market, artificial intelligence can improve blockchain efficiency by predicting network congestions, optimizing energy consumption in consensus mechanisms, and automating smart contracts, while blockchain enhances artificial intelligence capabilities by ensuring data provenance, reducing bias through decentralized data sources, and increasing transparency in decision-making algorithms. The market is expected to rise significantly in the coming years, driven by growing demand for data security, increased adoption of automation in business processes, and the rise of decentralized finance and digital identity management. The financial services, healthcare, logistics, and supply chain sectors are among the earliest adopters, using blockchain artificial intelligence solutions for fraud detection, secure data sharing, and efficient asset tracking.
Moreover, as businesses focus on enhancing trust in artificial intelligence decisions, blockchain's traceability and tamper-proof records will become increasingly valuable. Governments and regulatory bodies are also exploring the use of these technologies for secure digital identity verification, public health data tracking, and cross-border compliance. The rise of Web3 and decentralized applications further fuels demand for scalable and secure artificial intelligence models that can function within blockchain environments. With rapid advancements in edge computing, federated learning, and tokenized data marketplaces, blockchain artificial intelligence will become a key enabler of next-generation data ecosystems. Major technology providers and blockchain platforms are increasingly forming partnerships to launch hybrid solutions that address issues of interoperability, privacy, and trust. As venture capital investment and research and development in this space accelerate, the market is expected to experience a strong compound annual growth rate, creating new revenue streams and transforming traditional business models across industries.
Key Market Drivers
Enhanced Data Security and Integrity
The Blockchain Artificial Intelligence Market is driven by the critical need for enhanced data security and integrity across industries, as organizations handle vast amounts of sensitive data in AI-driven applications. Blockchain's decentralized and immutable ledger ensures tamper-proof data storage, addressing vulnerabilities in traditional centralized systems that are prone to breaches and manipulation. By integrating artificial intelligence with blockchain, businesses can secure AI training datasets, model outputs, and decision-making processes, ensuring transparency and trust.
This synergy is vital in sectors like finance, healthcare, and supply chain, where data breaches can lead to significant financial and reputational losses. Artificial intelligence enhances blockchain's security by enabling real-time threat detection and predictive analytics to identify potential vulnerabilities, while blockchain provides a verifiable audit trail for artificial intelligence decisions. This combination mitigates risks associated with data tampering and unauthorized access, fostering trust among stakeholders.
sAs organizations increasingly rely on artificial intelligence for automation and insights, the demand for secure, decentralized data management solutions grows, driving investments in blockchain artificial intelligence platforms to protect intellectual property, customer data, and operational integrity in a rapidly digitizing world.
In 2024, global data breaches exposed over 3.5 billion records, with 68% involving sensitive AI training data. Blockchain-based systems reduced data tampering incidents by 40% in pilot projects. By 2026, 75% of enterprises using artificial intelligence are expected to adopt blockchain for data integrity, with cybersecurity spending projected to reach USD200 billion, reflecting a 25% annual increase in demand for secure blockchain artificial intelligence solutions.
Key Market Challenges
Integration Complexity Between Blockchain and Artificial Intelligence Systems
One of the most significant challenges confronting the Blockchain Artificial Intelligence Market is the complexity of integrating blockchain infrastructure with artificial intelligence architectures. Blockchain technology is inherently decentralized and immutable, designed for secure record-keeping and data transparency. On the other hand, artificial intelligence systems thrive on continuous data input, real-time learning, and frequent model updates. The contrasting operational mechanisms of these technologies often result in architectural incompatibilities when organizations attempt to merge them into a single functional framework.
For instance, the immutable nature of blockchain can conflict with the evolving models of artificial intelligence, which require constant data revision and model training. As a result, any deployment that attempts to record artificial intelligence models and training data on the blockchain may encounter limitations in performance scalability, processing latency, and data storage constraints. Furthermore, smart contracts, which are essential to blockchain functionality, are typically deterministic and may not align well with the probabilistic nature of artificial intelligence algorithms.
Additionally, interoperability between legacy systems and modern blockchain-artificial intelligence integrations is limited. Organizations may struggle to bridge the gap between centralized enterprise databases and decentralized ledgers while trying to maintain system performance and compliance. This integration difficulty can also lead to elevated development costs, delayed project implementation timelines, and higher resource allocation for workforce upskilling and system configuration.
Moreover, there is a lack of standardized protocols for ensuring secure communication between artificial intelligence engines and blockchain nodes. Enterprises must often develop proprietary middleware solutions to enable cross-platform data exchange, which adds another layer of operational complexity. Until there are unified frameworks and toolkits specifically designed to facilitate seamless integration, the implementation barrier will continue to impede the widespread adoption of blockchain-artificial intelligence solutions across multiple sectors.
Key Market Trends
Integration Complexity Between Blockchain and Artificial Intelligence
One of the foremost challenges facing the Blockchain Artificial Intelligence Market is the complexity associated with integrating blockchain technology with artificial intelligence systems. These two technologies operate on fundamentally different architectural principles. Blockchain is a decentralized, immutable ledger that emphasizes transparency and trust, whereas artificial intelligence systems are inherently centralized and rely heavily on data aggregation and computational scalability. Integrating them demands substantial customization, new protocols, and infrastructure upgrades.
Businesses often struggle with aligning their existing artificial intelligence models with blockchain-based data flows, particularly when it comes to training machine learning algorithms on decentralized data sets. Moreover, latency issues in blockchain networks can significantly impact the responsiveness of artificial intelligence applications that require real-time data processing. For instance, in financial services or predictive maintenance in manufacturing, delays in data processing could reduce the effectiveness of artificial intelligence outputs.
Additionally, developers and data scientists face a steep learning curve in understanding both domains deeply enough to implement cohesive solutions. This lack of skilled personnel exacerbates deployment timelines and increases project costs. Organizations are required to invest in cross-functional teams, combining expertise from both artificial intelligence and blockchain sectors, which further complicates project coordination.
The absence of standardized frameworks and protocols also contributes to interoperability issues, impeding widespread adoption across different industries. Consequently, until unified architectural models and standard development platforms emerge, the integration of blockchain and artificial intelligence will remain a significant technical and operational hurdle for enterprises.
In this report, the Global Blockchain AI Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Blockchain AI Market.
Global Blockchain AI Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: