Press Release

AI Model Risk Management Market to Touch USD18.89 Billion by 2030

The AI Model Risk Management Market size was valued at USD10.2 Billion in 2024 and is projected to reach USD18.89 Billion by 2030. Along with this, the market is estimated to grow at a CAGR of around 10.79% during the forecast period, i.e., 2025-30, cites MarkNtel Advisors in the recent research report.

Various factors are associated with the market growth. One of the major reasons is the high adoption of AI across numerous industries for critical decision-making processes. The potential impact of errors, biases, or failures becomes significantly more serious with organizations deploying more advanced & autonomous systems. Hence, various laws & regulatory frameworks are being developed by policymakers in response to these rising concerns at the global level, which is driving the market. This mandates organizations to show transparency, fairness, and accountability in the development & deployment of AI models. Additionally, the growing complexity of AI models further requires robust oversight to prevent unintended consequences, operational disruptions, or ethical violations, especially in deep learning and large-scale language models. This is further driving the market growth. Also, there is an increasing demand for AI model risk management in anti-money laundering, as various cases can easily be flagged using these models by financial firms & security agencies globally.  

Moreover, various trends are shaping the market dynamics, showing how AI risk is managed.  There is a growing emphasis on the explainability and interpretability of AI, one of the foremost trends changing the industry. Industry players are introducing various tools & techniques to make AI-based decisions understandable to both technical & non-technical shareholders. Also, the integration of this with modern enterprise risk management strategies is further helping businesses in monitoring, controlling, and reporting on model risk in a structured and consistent way. There is a movement towards standardizing practices across industries and regions that makes it easier for organizations to adopt shared approaches to AI governance.

Additionally, the market offers numerous opportunities for growth & innovation. Companies offering AI auditing, validation, and compliance services are finding new markets among firms that lack in-house expertise. The popularity of industry-specific risk management solutions is growing rapidly in sectors where AI is used in sensitive or high-stakes applications. The development of global and industry standards is creating various collaboration opportunities between researchers & technology providers, coupled with regulatory bodies. Organizations that can align their AI practices with these evolving standards are better positioned to gain the trust of the public.

However, various challenges are impeding the growing market. The risk of cybersecurity has grown intensively with the market growth that creates losses of data & sometimes leads to financial crises. This involves various threats, including data poisoning and model inversion attacks. The execution capacity is becoming limited due to the lack of skilled professionals in both machine learning and regulatory compliance. As compared to traditional financial models, quantifying risks like bias, drift, or adversarial vulnerabilities remains complex. Moreover, cost barriers remain high for small and mid-sized enterprises that lack the infrastructure for comprehensive risk oversight. Without affordable and scalable tools, achieving its widespread adoption may remain out of reach for many organizations, further stated the research report “AI Model Risk Management Market Analysis, 2025.”

The AI Model Risk Management Market size was valued at USD10.2 Billion in 2024 and is projected to reach USD18.89 Billion by 2030. Along with this, the market is estimated to grow at a CAGR of around 10.79% during the forecast period, i.e., 2025-30, cites MarkNtel Advisors in the recent research report.

Various factors are associated with the market growth. One of the major reasons is the high adoption of AI across numerous industries for critical decision-making processes. The potential impact of errors, biases, or failures becomes significantly more serious with organizations deploying more advanced & autonomous systems. Hence, various laws & regulatory frameworks are being developed by policymakers in response to these rising concerns at the global level, which is driving the market. This mandates organizations to show transparency, fairness, and accountability in the development & deployment of AI models. Additionally, the growing complexity of AI models further requires robust oversight to prevent unintended consequences, operational disruptions, or ethical violations, especially in deep learning and large-scale language models. This is further driving the market growth. Also, there is an increasing demand for AI model risk management in anti-money laundering, as various cases can easily be flagged using these models by financial firms & security agencies globally.  

Moreover, various trends are shaping the market dynamics, showing how AI risk is managed.  There is a growing emphasis on the explainability and interpretability of AI, one of the foremost trends changing the industry. Industry players are introducing various tools & techniques to make AI-based decisions understandable to both technical & non-technical shareholders. Also, the integration of this with modern enterprise risk management strategies is further helping businesses in monitoring, controlling, and reporting on model risk in a structured and consistent way. There is a movement towards standardizing practices across industries and regions that makes it easier for organizations to adopt shared approaches to AI governance.

Additionally, the market offers numerous opportunities for growth & innovation. Companies offering AI auditing, validation, and compliance services are finding new markets among firms that lack in-house expertise. The popularity of industry-specific risk management solutions is growing rapidly in sectors where AI is used in sensitive or high-stakes applications. The development of global and industry standards is creating various collaboration opportunities between researchers & technology providers, coupled with regulatory bodies. Organizations that can align their AI practices with these evolving standards are better positioned to gain the trust of the public.

However, various challenges are impeding the growing market. The risk of cybersecurity has grown intensively with the market growth that creates losses of data & sometimes leads to financial crises. This involves various threats, including data poisoning and model inversion attacks. The execution capacity is becoming limited due to the lack of skilled professionals in both machine learning and regulatory compliance. As compared to traditional financial models, quantifying risks like bias, drift, or adversarial vulnerabilities remains complex. Moreover, cost barriers remain high for small and mid-sized enterprises that lack the infrastructure for comprehensive risk oversight. Without affordable and scalable tools, achieving its widespread adoption may remain out of reach for many organizations, further stated the research report “AI Model Risk Management Market Analysis, 2025.”