AI Model Risk Management Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2024 to 2032
The Global AI Model Risk Management Market was valued at USD 5.3 billion in 2023 and is projected to grow at a CAGR of 11.1% from 2024 to 2032. Market growth is driven by increasing regulatory compliance demands worldwide, compelling organizations to implement robust AI risk management frameworks. As regulatory bodies introduce more stringent guidelines regarding AI usage, businesses must adopt solutions that automate monitoring and validation, reducing non-compliance risks while ensuring adherence to regulations. The rising complexity of AI models is another significant growth driver. With organizations deploying advanced AI technologies, including deep learning and ensemble methods, the associated risks also increase.
Ensuring these models remain transparent, interpretable, and reliable requires comprehensive risk management. By utilizing advanced analytics and automated monitoring, organizations can better understand and mitigate potential issues in their AI models, supporting more informed decision-making. The market is segmented by component into software and services. In 2023, the software segment captured over 70% of the market share, expected to surpass USD 9 billion by 2032. The growth of this segment is fueled by the rising need for automation in risk assessment processes.
AI-powered software enhances efficiency by automating the identification and evaluation of risks, providing real-time insights, and streamlining the validation of AI models. By risk type, the AI model risk management market is categorized into model risk, operational risk, compliance risk, reputational risk, and strategic risk. In 2023, the model risk segment accounted for around 31% of the market. The increasing complexity of AI and machine learning models amplifies the need to manage model risk.
As organizations adopt sophisticated algorithms for applications like predictive analytics and decision-making, the risk of biases, overfitting, and performance issues rises. This drives the need for robust model risk management practices to ensure accountability and transparency. The U.S. dominated the market in 2023, holding over 75% of the global market share, with projections to reach around USD 2.5 billion by 2032. As AI adoption expands across industries such as finance, healthcare, and insurance, regulatory bodies are imposing more stringent guidelines. This increased regulatory focus requires businesses to invest in advanced AI model risk management solutions to ensure compliance and effectively navigate the evolving regulatory landscape
Ensuring these models remain transparent, interpretable, and reliable requires comprehensive risk management. By utilizing advanced analytics and automated monitoring, organizations can better understand and mitigate potential issues in their AI models, supporting more informed decision-making. The market is segmented by component into software and services. In 2023, the software segment captured over 70% of the market share, expected to surpass USD 9 billion by 2032. The growth of this segment is fueled by the rising need for automation in risk assessment processes.
AI-powered software enhances efficiency by automating the identification and evaluation of risks, providing real-time insights, and streamlining the validation of AI models. By risk type, the AI model risk management market is categorized into model risk, operational risk, compliance risk, reputational risk, and strategic risk. In 2023, the model risk segment accounted for around 31% of the market. The increasing complexity of AI and machine learning models amplifies the need to manage model risk.
As organizations adopt sophisticated algorithms for applications like predictive analytics and decision-making, the risk of biases, overfitting, and performance issues rises. This drives the need for robust model risk management practices to ensure accountability and transparency. The U.S. dominated the market in 2023, holding over 75% of the global market share, with projections to reach around USD 2.5 billion by 2032. As AI adoption expands across industries such as finance, healthcare, and insurance, regulatory bodies are imposing more stringent guidelines. This increased regulatory focus requires businesses to invest in advanced AI model risk management solutions to ensure compliance and effectively navigate the evolving regulatory landscape
Report Content
CHAPTER 1 METHODOLOGY & SCOPE
1.1 Research design
1.1.1 Research approach
1.1.2 Data collection methods
1.2 Base estimates and calculations
1.2.1 Base year calculation
1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
1.4.1 Primary sources
1.4.2 Data mining sources
1.5 Market definitions
CHAPTER 2 EXECUTIVE SUMMARY
2.1 Industry 360° synopsis, 2021 - 2032
CHAPTER 3 INDUSTRY INSIGHTS
3.1 Industry ecosystem analysis
3.1.1 Software providers
3.1.2 Service providers
3.1.3 Technology providers
3.1.4 End users
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Case study
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
3.8.1 Growth drivers
3.8.1.1 Increasing adoption of AI technologies
3.8.1.2 The shift towards data-driven decision-making
3.8.1.3 The need for robust risk management
3.8.1.4 Growing demand for enhanced governance frameworks
3.8.2 Industry pitfalls & challenges
3.8.2.1 Lack of skilled professionals
3.8.2.2 Data privacy and security concerns
3.9 Growth potential analysis
3.10 Porter’s analysis
3.11 PESTEL analysis
CHAPTER 4 COMPETITIVE LANDSCAPE, 2023
4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix
CHAPTER 5 MARKET ESTIMATES & FORECAST, BY COMPONENT, 2021 - 2032 ($BN)
5.1 Key trends
5.2 Software
5.3 Services
5.3.1 Professional
5.3.2 Managed
CHAPTER 6 MARKET ESTIMATES & FORECAST, BY DEPLOYMENT MODEL, 2021 - 2032 ($BN)
6.1 Key trends
6.2 On-premises
6.3 Cloud
CHAPTER 7 MARKET ESTIMATES & FORECAST, BY RISK, 2021 - 2032 ($BN)
7.1 Key trends
7.2 Model risk
7.3 Operational risk
7.4 Compliance risk
7.5 Reputational risk
7.6 Strategic risk
CHAPTER 8 MARKET ESTIMATES & FORECAST, BY APPLICATION, 2021 - 2032 ($BN)
8.1 Key trends
8.2 Credit risk management
8.3 Fraud detection and prevention
8.4 Algorithmic trading
8.5 Predictive maintenance
8.6 Others
CHAPTER 9 MARKET ESTIMATES & FORECAST, BY END USE, 2021 - 2032 ($BN)
9.1 Key trends
9.2 BFSI
9.3 IT & telecom
9.4 Healthcare
9.5 Automotive
9.6 Retail and e-commerce
9.7 Manufacturing
9.8 Government and defense
9.9 Others
CHAPTER 10 MARKET ESTIMATES & FORECAST, BY REGION, 2021 - 2032 ($BN)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Spain
10.3.5 Italy
10.3.6 Russia
10.3.7 Nordics
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Southeast Asia
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Argentina
10.6 MEA
10.6.1 UAE
10.6.2 South Africa
10.6.3 Saudi Arabia
CHAPTER 11 COMPANY PROFILES
11.1 Alteryx
11.2 Apparity
11.3 Axioma
11.4 Databricks
11.5 DataRobot
11.6 Empowered Systems
11.7 FICO
11.8 Friss
11.9 Google
11.10 IBM
11.11 Kx Systems
11.12 MathWorks
11.13 Microsoft
11.14 Quantiphi
11.15 RiskLens
11.16 SAS
11.17 TIBCO Software
11.18 ValidMind
11.19 Yields.io
11.20 Zest AI
CHAPTER 1 METHODOLOGY & SCOPE
1.1 Research design
1.1.1 Research approach
1.1.2 Data collection methods
1.2 Base estimates and calculations
1.2.1 Base year calculation
1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
1.4.1 Primary sources
1.4.2 Data mining sources
1.5 Market definitions
CHAPTER 2 EXECUTIVE SUMMARY
2.1 Industry 360° synopsis, 2021 - 2032
CHAPTER 3 INDUSTRY INSIGHTS
3.1 Industry ecosystem analysis
3.1.1 Software providers
3.1.2 Service providers
3.1.3 Technology providers
3.1.4 End users
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Case study
3.6 Key news & initiatives
3.7 Regulatory landscape
3.8 Impact forces
3.8.1 Growth drivers
3.8.1.1 Increasing adoption of AI technologies
3.8.1.2 The shift towards data-driven decision-making
3.8.1.3 The need for robust risk management
3.8.1.4 Growing demand for enhanced governance frameworks
3.8.2 Industry pitfalls & challenges
3.8.2.1 Lack of skilled professionals
3.8.2.2 Data privacy and security concerns
3.9 Growth potential analysis
3.10 Porter’s analysis
3.11 PESTEL analysis
CHAPTER 4 COMPETITIVE LANDSCAPE, 2023
4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix
CHAPTER 5 MARKET ESTIMATES & FORECAST, BY COMPONENT, 2021 - 2032 ($BN)
5.1 Key trends
5.2 Software
5.3 Services
5.3.1 Professional
5.3.2 Managed
CHAPTER 6 MARKET ESTIMATES & FORECAST, BY DEPLOYMENT MODEL, 2021 - 2032 ($BN)
6.1 Key trends
6.2 On-premises
6.3 Cloud
CHAPTER 7 MARKET ESTIMATES & FORECAST, BY RISK, 2021 - 2032 ($BN)
7.1 Key trends
7.2 Model risk
7.3 Operational risk
7.4 Compliance risk
7.5 Reputational risk
7.6 Strategic risk
CHAPTER 8 MARKET ESTIMATES & FORECAST, BY APPLICATION, 2021 - 2032 ($BN)
8.1 Key trends
8.2 Credit risk management
8.3 Fraud detection and prevention
8.4 Algorithmic trading
8.5 Predictive maintenance
8.6 Others
CHAPTER 9 MARKET ESTIMATES & FORECAST, BY END USE, 2021 - 2032 ($BN)
9.1 Key trends
9.2 BFSI
9.3 IT & telecom
9.4 Healthcare
9.5 Automotive
9.6 Retail and e-commerce
9.7 Manufacturing
9.8 Government and defense
9.9 Others
CHAPTER 10 MARKET ESTIMATES & FORECAST, BY REGION, 2021 - 2032 ($BN)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Spain
10.3.5 Italy
10.3.6 Russia
10.3.7 Nordics
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Southeast Asia
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Argentina
10.6 MEA
10.6.1 UAE
10.6.2 South Africa
10.6.3 Saudi Arabia
CHAPTER 11 COMPANY PROFILES
11.1 Alteryx
11.2 Apparity
11.3 Axioma
11.4 Databricks
11.5 DataRobot
11.6 Empowered Systems
11.7 FICO
11.8 Friss
11.9 Google
11.10 IBM
11.11 Kx Systems
11.12 MathWorks
11.13 Microsoft
11.14 Quantiphi
11.15 RiskLens
11.16 SAS
11.17 TIBCO Software
11.18 ValidMind
11.19 Yields.io
11.20 Zest AI
