AI Model Risk Management Global Market Size Report 2025
What Is the Forecasted Market Size and Growth Rate for the AI Model Risk Management Market?
The market for AI model risk management has seen swift expansion in the recent past. There will be an increase from $6.17 billion in 2024 to $7.17 billion by 2025, demonstrating a compound annual growth rate (CAGR) of 16.2%. Factors that led to growth during this period include the global application of AI models, rising worries over insurance benefits and liabilities connected to AI model failures, a growing understanding among stakeholders regarding the potential risks of AI models, and the widespread adoption of AI that requires strong risk management frameworks. It also promotes better operational efficiency through efficient governance and management of AI model risks.
Expectations are high for the AI model risk management market size to experience rapid expansion in the coming years, with a projected growth that could reach $12.96 billion by 2029, reflecting a compound annual growth rate (CAGR) of 16.0%. This surge over the forecast period is attributed to factors such as escalating regulatory scrutiny, increased requirements for AI model management, heightened board and executive surveillance of AI model risk management practices, as well as an increased awareness of the ethical consequences of AI and the cyber-related threats targeting AI models. Noteworthy trends that may occur over the forecast period are expedited advancements in AI technologies, the amalgamation of AI model risk management with expansive enterprise risk management frameworks, development of strategies to calculate and evaluate the risks related to AI models, and the constant refinement and adaptation of AI model risk management strategies.
What Factors Are Propelling the Expansion of the AI Model Risk Management Market?
The heightened consciousness about cyber security threats is projected to fuel the expansion of the AI model risk management sector. Cybersecurity threats refer to harmful activities that seek to infiltrate computer systems, either to steal, harm, or interrupt data, including malware, phishing, and DoS attacks, all of which pose a threat to digital security. As digital technology becomes more widely relied upon, this, in turn, provides an enlarging field of opportunity for cybercriminals, leading to an escalation in cybersecurity threats. AI model risk management is utilised in combatting cybersecurity threats to deter vulnerabilities, forecast impending attacks, and bolster 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, with a median estimated expense of $5,369.68 for medium and large businesses, and $24,878.68 when the costs pertain solely to tangible outcomes such as financial loss or data theft. Hence, the escalating cognizance about cyber security threats is propelling the AI model risk management market’s expansion.
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Which Businesses Are at the Forefront of AI Model Risk Management Market Development?
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
What Are the Latest Innovations in the AI Model Risk Management Market?
Key players in the AI model risk management market are centering their efforts on creating novel solutions, such as pioneering artificial intelligence models, to secure a competitive advantage. An advanced AI model is a refined artificial intelligence system adept at carrying out intricate tasks with precision and efficiency. These models predominantly utilize advanced machine learning, deep learning, and natural language processing techniques to analyze extensive data sets, make forecasts, and automate decision-making procedures. For example, in July 2024, Zendata, an American security platform creator, inaugurated an advanced AI model and data usage scanning platform. This evolution boosts governance, bias detection, and regulation across corporate AI ecosystems. This groundbreaking solution provides holistic governance, bias detection, and compliance features across all AI and data ecosystems, catering to the escalating demand for transparent and accountable AI implementation in businesses.
How Is the AI Model Risk Management Market Segmented?
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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Where Is the AI Model Risk Management Market Growth Most Prominent?
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 Is Covered In The AI Model Risk Management Global Market Report?
– Market Size Analysis: Analyze the AI Model Risk Management Market size by key regions, countries, product types, and applications.
– Market Segmentation Analysis: Identify various subsegments within the AI Model Risk Management Market for effective categorization.
– Key Player Focus: Focus on key players to define their market value, share, and competitive landscape.
– Growth Trends Analysis: Examine individual growth trends and prospects in the Market.
– Market Contribution: Evaluate contributions of different segments to the overall AI Model Risk Management Market growth.
– Growth Drivers: Detail key factors influencing market growth, including opportunities and drivers.
– Industry Challenges: Analyze challenges and risks affecting the AI Model Risk Management Market.
– Competitive Developments: Analyze competitive developments, such as expansions, agreements, and new product launches in the market.
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