AI Model Risk Management Market Expected to Reach USD 15.03 Billion by 2033 Driven by Widespread AI and ML Adoption | SNS Insider

The market for artificial intelligence (AI) model risk management (MRM) is expanding rapidly due to the growing use of AI and ML (machine learning) models in a variety of sectors, such as IT, healthcare, and BFSI (banking, financial services, and insurance).

Austin, Oct. 08, 2025 (GLOBE NEWSWIRE) — The AI Model Risk Management Market Size was valued at USD 5.87 Billion in 2025E and is expected to reach USD 15.03 Billion by 2033 and grow at a CAGR of 12.52% over 2026-2033.

Globally, governments and financial authorities are increasing compliance requirements to guarantee that AI models are ethical, transparent, and explicable. Businesses are required by frameworks such as the EU AI Act and the U.S. advice on model risk management to make sure AI systems are verified, tracked, and recorded. Organizations, particularly in the government, healthcare, and BFSI sectors, are compelled by this demand to adopt next-generation AI-enabled Model Risk Management (MRM) systems. As businesses incorporate AI governance into their operational playbooks, this demand-side push is not only reducing the friction of compliance and reputational risk but also securing market growth.

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In 2025, North America Led the Market with a Share of 44.08%; Asia Pacific is Projected to Propel with the Fastest CAGR of 13.63% During the Forecast Period

North America dominated the global AI Model Risk Management Market in 2024, with over 44.08% revenue share, owing to the favorable technological infrastructure and the stringent regulatory framework along with the presence of the large vendors such as IBM, Microsoft, and SAS. The Asia Pacific region is expected to have the fastest-growing CAGR 13.63%, for the AI Model Risk Management market, which is essentially owing to the astronomical rise in enterprise AI adoption in conjunction with the increasing complexity of deployed models across industries. 

AI Model Risk Management Market Report Scope:

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Segmentation Analysis:

By Component, in 2025, Software Led the Market with a Share of 65.80%, while Services is the Fastest-growing Segment with a CAGR of 13.22%

Software segment held the highest share in 2024, globally, due to organization-wide adoption of advanced platforms for model validation, monitoring, and compliance management. Services segment is expected to grow at the highest growth rate during 2024–2032, owing to the increasing requirement for consulting, integration, and managed services.

By Deployment Mode, in 2025, On-premises Dominated the Market with 60.06% Share, while Cloud is the Fastest-growing Segment with a CAGR of 12.85%

The On-Premises deployment leads the global AI Model Risk Management market due to the fact that majority of the enterprises, especially in highly regulated sectors, such as BFSI and government. Cloud segment is anticipated to be the fastest-growing from, due to its cost-effectiveness, scalability, and provision of real-time analytics.

By Risk, in 2025, Model Risk Dominated the Market with a Share of 35.08%, while Compliance Risk Segment is the Fastest-growing Segment with a CAGR of 13.86%

Model risk segment dominated the market in 2024 as organizations deploying more and more complicated AI and machine learning models that challenge their accuracy, fairness and reliability, continuous validation, monitoring and governance. the compliance risk segment is also expected to be the fastest-growing one as an increase in the global regulatory focus, combined with changing standards of practice in various industries, drives organizations to implement comprehensive MRM solutions.

By Application, in 2025, Credit Risk Management Held the Largest Market Share of 30.10%, while Predictive Maintenance is the Fastest-growing Segment with a CAGR of 14.23%

In 2024, Credit Risk Management held the largest market share of 30.10% in the AI Model Risk Management Market, primarily driven by the rising adoption of AI-based systems in financial institutions to enhance accuracy, efficiency, and regulatory compliance. Predictive Maintenance is emerging as the fastest-growing segment, projected to register a CAGR of 14.23% during the forecast period. This rapid growth is attributed to the increasing integration of IoT sensors, machine learning algorithms, and real-time analytics in industrial operations.

By End-Use, in 2025, BFSI Held the Dominant Market Share of 35.04%, while Healthcare is the Fastest-growing Segment with a CAGR of 15.42%

Due to the widespread use of AI and machine learning-based models for credit scoring, fraud detection, trading, and regulatory compliance within the industry, the BFSI sector now holds the top spot. Healthcare is expected to be the fastest growing segment, driven by the growing adoption of AI in diagnostics, predictive analytics, patient care and drug discovery. 

Key Players:

• Microsoft Corporation
• IBM Corporation
• Google LLC
• Amazon Web Services (AWS)
• H2O.ai
• SAS Institute Inc.
• DataRobot, Inc.
• Alteryx
• UpGuard Inc.
• LogicGate Inc.
• ComplyCube
• BigID
• Holistic AI
• ValidMind Inc.
• Accenture plc
• Deloitte Touche Tohmatsu Limited
• PricewaterhouseCoopers (PwC)
• Ernst & Young (EY)
• Oracle Corporation
• SAP SE

Recent Developments:

• In March 2025, H2O.ai launched the industry’s first Model Risk Management framework for Generative AI, bringing rigorous validation, compliance, and transparency to Generative AI applications in financial services, banking, and other highly regulated sectors. 
• In December 2024, AWS introduced new capabilities for Amazon Bedrock, including industry-first AI safeguards, new agent capabilities, and model customization features, enhancing model risk management and compliance for generative AI applications.

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Exclusive Sections of the Report (The USPs):

• MODEL COMPLEXITY & SCALE METRICS – helps you understand the growing scope of AI governance by tracking the number of models deployed per enterprise, the share of deep learning and generative AI systems requiring advanced oversight, and the year-over-year expansion in model portfolios.
• AUTOMATION & EFFICIENCY INDEX – helps you assess how enterprises are improving operational efficiency by automating risk management workflows, reducing manual intervention, accelerating regulatory reporting, and enhancing decision-making speed.
• INCIDENT & RISK DETECTION PERFORMANCE – helps you evaluate how AI MRM platforms are proactively identifying and mitigating biases, reducing false positives/negatives, and detecting compliance risks before they affect business operations.
• MODEL ERROR & BIAS REDUCTION RATE – helps you analyze the effectiveness of MRM systems in minimizing model drift, bias propagation, and decision inconsistencies across high-impact AI applications.
• REGULATORY REPORTING IMPROVEMENT METRICS – helps you measure time savings and accuracy enhancements in regulatory submissions enabled by automated validation, audit trails, and compliance reporting tools.
• AI GOVERNANCE MATURITY BENCHMARKS – helps you benchmark enterprises based on their adoption of comprehensive AI governance frameworks covering lifecycle monitoring, ethical AI validation, and explainability standards.

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