세계 AI 모델 리스크 관리 시장 규모는 2023년에 57억 달러, 2024년 64억 5,000만 달러에서 2032년에는 172억 6,000만 달러에 이르고, 예측 기간(2025-2032년) CAGR은 13.1%를 나타낼 전망입니다.
세계 AI 모델 리스크 관리 시장은 금융, 항공, 의료, 자동차, 제조 등 필수 분야에서의 AI 통합에 대한 수요가 지속적으로 증가함에 따라 확대되고 있습니다. 기업의 의사결정과 리스크 관리에서 AI에 대한 의존도가 점점 더 높아지고 있으며, 컴플라이언스, 신뢰성, 투명성이 높은 모델 운영의 필요성이 부각되고 있습니다. 규제 지침의 강화로 인해 책임, 설명 가능성, 공정성이 강조되면서 기업들은 거버넌스 및 검증 기술에 대한 투자를 늘리고 있습니다. 모델 편향과 데이터 유출 사례가 빈번하게 발생함에 따라 AI 리스크를 효과적으로 식별, 평가, 완화하기 위한 종합적인 리스크 관리 프레임워크의 필요성이 대두되고 있습니다. 또한, 설명 가능한 AI, 규제 기술, 증가하는 컴플라이언스 요구사항의 수용으로 기업들은 업무 효율성을 높이고 AI의 성과에 대한 신뢰를 구축할 수 있는 통합 리스크 관리 솔루션을 요구하고 있습니다.
Global AI Model Risk Management Market size was valued at USD 5.7 billion in 2023 and is poised to grow from USD 6.45 billion in 2024 to USD 17.26 billion by 2032, growing at a CAGR of 13.1% during the forecast period (2025-2032).
The global AI model risk management market is expanding as the demand for AI integration in essential sectors like finance, aviation, healthcare, automotive, and manufacturing continues to rise. Companies increasingly rely on AI for decision-making and risk management, highlighting the need for compliant, reliable, and transparent model operations. Enhanced regulatory guidance emphasizes accountability, explainability, and fairness, prompting businesses to invest in governance and validation technologies. The escalation of notable instances of model biases and data breaches has intensified the need for comprehensive risk management frameworks to effectively identify, assess, and mitigate AI risks. Furthermore, the acceptance of explainable AI, regulatory technology, and expanding compliance demands drives organizations to seek integrated risk management solutions that enhance operational efficiency and foster trust in AI outcomes.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global AI Model Risk Management market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global AI Model Risk Management Market Segments Analysis
Global AI Model Risk Management Market is segmented by Component, Deployment Model, Risk, Application, End Use and region. Based on Component, the market is segmented into Software and Services. Based on Deployment Model, the market is segmented into On-premises and Cloud. Based on Risk, the market is segmented into Model risk, Operational risk, Compliance risk, Reputational risk and Strategic risk. Based on Application, the market is segmented into Credit risk management, Fraud detection and prevention, Algorithmic trading, Predictive maintenance and Others. Based on End Use, the market is segmented into BFSI, IT & telecom, Healthcare, Automotive, Retail and e-commerce, Manufacturing, Government and defense and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global AI Model Risk Management Market
The growing reliance on artificial intelligence within business operations is giving rise to significant risks associated with model failures, biases, and cybersecurity threats. Companies are increasingly aware that these operational vulnerabilities can heighten their overall risk, prompting them to invest in scalable and automated risk management solutions. These tools are designed to efficiently monitor, validate, and secure AI implementations, enabling organizations to mitigate potential disruptions and safeguard their reputation. As a result, there is a strong push towards enhancing risk management capabilities to ensure AI technologies are deployed safely and effectively, ultimately supporting robust business continuity.
Restraints in the Global AI Model Risk Management Market
A significant constraint in the Global AI Model Risk Management market is the high cost associated with implementation, especially for small and medium-sized enterprises. Many organizations find the expenses related to technology integration, ongoing monitoring, compliance requirements, and associated labor to be prohibitive. As a result, these financial barriers can restrict the ability of numerous companies to adopt and effectively utilize advanced AI model risk management systems. This economic challenge can ultimately hinder the overall growth and accessibility of sophisticated risk management solutions in the market, limiting participation to a smaller group of organizations with more substantial resources.
Market Trends of the Global AI Model Risk Management Market
The Global AI Model Risk Management market is increasingly emphasizing the integration of explainable and responsible AI principles. Companies are actively seeking solutions that enhance transparency, auditability, and interpretability of AI systems, reflecting a broader demand for ethical governance frameworks. This trend is fueled by growing regulatory pressures and the necessity to foster stakeholder trust while addressing biases and unintended consequences that may arise from automated systems. By prioritizing responsible AI practices, organizations aim to ensure compliance, minimize risk, and enhance the overall reliability of their AI models, ultimately leading to more sustainable and socially acceptable AI deployment strategies.