AI Model Risk Management Market Poised for 16% Growth, Set to Hit $13 Billion by 2029

How Are the key drivers contributing to the expansion of the ai model risk management market?
The burgeoning recognition of cyber security risks is foreseen to boost the expansion of AI model risk management in the future. Cybersecurity hazards denote harmful actions aimed at computer systems intending to steal, destroy, or disrupt data. These encompass malware, phishing, and DoS attacks that compromise digital security. With the mounting dependency on digital technology, the attack surface area for cyber criminals is extending, leading to a rise in cybersecurity hazards. AI model risk management plays a crucial role in dealing with these threats by pinpointing susceptibilities, foreseeing probable attacks, and improving security defenses. For example, in July 2022, the UK Department for Digital, Culture, Media, and Sport disclosed that 39% of UK businesses fell victim to a cyber-attack in the previous year. The average projected cost was $5,369.68 for medium and large businesses and it soared to $24,878.68 considering tangible outcomes like financial or data loss. Hence, the escalating awareness about cyber security threats is fueling the advancement of the AI model risk management market.

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What growth opportunities are expected to drive the ai model risk management market's CAGR through 2034?
The rapid expansion of the AI model risk management market is evident in recent years, and the trend is projected to continue. An increase from $6.17 billion in 2024 to $7.17 billion in 2025, boasting a CAGR of 16.2%, is anticipated. Factors propelling the growth during the historic period include the global adoption of AI models, escalating worries about insurance and liability issues relating to failures in AI models, the heightening awareness among involved parties about the inherent dangers of AI models, and industry-wide AI adoption that calls for solid risk management frameworks. Emphasis on enhancing operational efficiency via efficient handling of AI model risks and governance also contributes to market growth.

The projected growth rate for the AI model risk management market over the next few years is expected to be significant, with an estimated value of $12.96 billion by 2029. This represents a compound annual growth rate (CAGR) of 16.0%. Several factors can be attributed to this rise, including intensified regulatory scrutiny for AI model management, increased oversight by executive boards of AI model risk management procedures, the ethical concerns surrounding AI and the associated cybersecurity risks. Key trends to observe during this growth period include the swift progression of AI technologies, the merging of AI model risk management within comprehensive enterprise risk management structures, the innovation of strategies to measure and evaluate AI model-related risks, and ongoing evolution and betterment of AI model risk management tactics.

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What are the emerging trends shaping the future of the ai model risk management market?
Leading firms in the AI model risk management market are emphasizing the creation of cutting-edge solutions, like sophisticated AI models, to secure a competitive advantage. These advanced AI systems are crafted to complete intricate tasks with superior efficiency and accuracy, utilizing the latest technologies in machine learning, deep learning, and natural language processing to assess enormous data volumes, forecast outcomes, and automate decision-making procedures. For example, in July 2024, Zendata, an American security platform developer, introduced an enhanced AI model and data usage scanning platform. This expands governance, bias detection, and adherence within enterprise-wide AI ecosystems. This revolutionary product offers thorough governance, bias detection, and compliance across all AI and data ecosystems, meeting the increasing demand for transparent and ethical AI usage in businesses.

Which growth-oriented segments of the ai model risk management market are leading the industry's development?
The AI model risk managementmarket covered in this report is segmented -

1) By Component: Solution, Service
2) By Deployment Mode: Cloud-Based, On-Premise
3) By Organization Size: Large Enterprises, Small And Medium-sized Enterprises (SMEs)
4) By Application: Model Documentation, Model Governance, Model Monitoring, Model Validation
5) By Industry Vertical: Financial Services, Healthcare, Insurance, Telecommunications

Subsegments:
1) By Solution: AI Model Validation Tools, AI Model Monitoring and Performance Tracking, Risk Assessment and Analytics Software, Explainability and Transparency Tools, Model Governance and Compliance Solutions
2) By Service: AI Model Risk Consulting Services, Model Risk Assessment and Evaluation Services, AI Model Auditing and Compliance Services, AI Model Training and Optimization Services, Ongoing Monitoring and Support Services

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What regions are leading the charge in the ai model risk management market?
North America was the largest region in the AI model risk management market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the AI model risk management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

What companies are at the forefront of innovation in the ai model risk management market?
Major companies operating in the AI model risk management market are Amazon.com Inc., Google LLC, Microsoft Corporation, accenture* plc, International Business Machines Corporation, Deloitte Touche Tohmatsu Limited, PricewaterhouseCoopers International Limited, Ernst & Young, Oracle Corporation, KPMG International Limited, SAP SE, Moody's Analytics, Sas Institute Inc, DataBricks Inc, Teradata Corporation, Palantir Technologies Inc., Fair Isaac Corporation, The MathWorks Inc, DataRobot Inc, H2O.ai, LogicGate, LogicManager

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What Is Covered In The AI Model Risk Management Global Market Report?

•Market Size Forecast: Examine the ai model risk management market size across key regions, countries, product categories, and applications.
•Segmentation Insights: Identify and classify subsegments within the ai model risk management market for a structured understanding.
•Key Players Overview: Analyze major players in the ai model risk management market, including their market value, share, and competitive positioning.
•Growth Trends Exploration: Assess individual growth patterns and future opportunities in the ai model risk management market.
•Segment Contributions: Evaluate how different segments drive overall growth in the ai model risk management market.
•Growth Factors: Highlight key drivers and opportunities influencing the expansion of the ai model risk management market.
•Industry Challenges: Identify potential risks and obstacles affecting the ai model risk management market.
•Competitive Landscape: Review strategic developments in the ai model risk management market, including expansions, agreements, and new product launches.

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