According to MarketsandMarkets™, the AI Model Risk Management Market is projected to grow from USD 5.7 billion in 2024 to USD 10.5 billion by 2029, registering a CAGR of 12.9% during the forecast period.
The AI Model Risk Management Market market is expected to grow significantly during the forecast period by increasing the need to establish robust security protocols, monitor compliance and respond effectively to emerging threats, the rising need to automate risk assessment for degraded manual errors, and the need to automate model lifecycle, improve efficiency and surge quality of the final production models.
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Key Takeaways
- Model risk management is now a critical pillar in AI strategy, responding to cyber threats, regulatory scrutiny, and public trust demands.
- The complexity of model validation, interpretation, and lifecycle monitoring requires automation, advanced analytics, and thorough audit trails for compliance.
- Generative AI is a major growth catalyst for automating compliance processes, dynamic risk monitoring, and actionable insights.
- Healthcare is leading vertical growth, driven by technological innovation, sensitive data requirements, and rapidly evolving standards.
Go to Market Insights
- Enterprises should prioritize adoption of AI model risk management to automate compliance and risk evaluation, reducing manual errors and streamlining audit processes.
- Target verticals with stringent regulatory standards (e.g., financial services, healthcare, life sciences) where maintaining model integrity and patient data privacy is critical.
- Invest in managed services for expert oversight on cloud infrastructure, regulatory updates, and ongoing risk mitigation—especially as AI adoption scales.
- Encourage integration of generative AI to dynamically update risk strategies, increase transparency, and enhance trust in AI-driven business decisions.
By Software type, the Model Management software segment holds the largest market size during the forecast period.
Model management software ensures the efficient deployment and operation of AI and machine learning models within organizations. It provides comprehensive audit trails and documentation to demonstrate compliance and support regulatory audits. Moreover, the software helps manage model lifecycle processes such as development, versioning, and documentation, ensuring that models are up-to-date and perform reliably. It facilitates robust validation and testing to detect and mitigate biases, ensuring that models adhere to regulatory standards and ethical guidelines. Additionally, model management software supports continuous monitoring and performance tracking, allowing for prompt detection of model drift and other issues.
By services, managed services to register for the fastest growing segment during the forecast period.
Managed services are expected to experience significant growth due to several key factors. Firstly, the growing complexity of regulations requires specialized knowledge, making managed services attractive to companies. Secondly, with the increasing adoption of cloud-based services, as businesses shift their IT infrastructure to cloud-based solutions, they face complexities in managing and optimizing these environments effectively. Lastly, Managed services have advanced tools and technologies that help identify, assess, and reduce risks more effectively. By providing top-notch solutions, the companies keep up with the latest developments.
By region, North America accounted for the largest market size during the forecast period.
Several key factors contribute to North America having the largest market size in model risk management. The region has large financial institutions and tech companies investing heavily in advanced technologies, including AI and machine learning models. The AI Model risk management market across North America is driven by a high level of technological infrastructure and expertise, facilitating the integration of advanced AI model risk management tools. Moreover, North America boasts a highly mature market with significant investments in AI technology. Organizations across various sectors, including finance, healthcare, and retail, extensively leverage AI.
Some major players in the AI Model Risk Management Market include Microsoft(US), IBM(US), SAS Institute (US), AWS (US), H2O.ai (US), Google (US), LogicGate (US), LogicManager (US), C3 AI (US), MathWorks (US), Alteryx (US), DataBricks (US), Robust Intelligence (US), CIMCON Software (US), Empowered Systems (UK), Mitratech (US), Yields.io (Belgium), MeticStream (US), iManage (US), UpGuard (US), Apparity (US), AuditBoard (US), NAVEX Global (US), Scrut Automation (India), DataTron (US), Krista (US), Fairly AI (Canada), ModelOp (US), Armilla AI (Canada), Crowe (US), and ValidMind (US).
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