AI Model Risk Management Market 2025

AI Model Risk Management Market Size

The global AI model risk management market reached a value of nearly $6,170.00 million in 2024, having grown at a compound annual growth rate (CAGR) of 13.14% since 2019. The market is expected to grow from $6,170.00 million in 2024 to $11,412.12 million in 2029 at a rate of 13.09%. The market is then expected to grow at a CAGR of 12.77% from 2029 and reach $20,816.68 million in 2034. Growth in the historic period resulted from the rising demand for cloud adoption, surge in digital transactions, growing awareness of cyber security threats and growing government initiatives. Factors that negatively affected growth in the historic period was lack of skilled professionals and integration challenges with legacy systems. Going forward, the rise in use of AI and ML models in regulated industries, expansion of internal audit and compliance functions, growing complexity of AI models and increase in model failure incidents will drive the growth. Factor that could hinder the growth of the AI model risk management market in the future include resistance to change within organizations, high cost and complexity of implementation and impact of trade war and tariff.

AI Model Risk Management Market Drivers

The key drivers of the AI model risk management market include: Rise In Use Of AI And ML Models In Regulated Industries Rise in use of AI and ML models in regulated industries is expected to propel the growth of the AI model risk management market going forward. The rising number of AI model failure incidents ranging from biased outputs and inaccurate predictions to regulatory breaches has intensified the need for robust AI Model Risk Management solutions. As AI systems are deployed in high-impact areas such as credit scoring, medical diagnostics and compliance monitoring, even minor failures can lead to significant financial, legal and reputational consequences. These incidents highlight the urgent need for frameworks that ensure continuous monitoring, performance validation and risk mitigation throughout the model lifecycle. Organizations are increasingly adopting comprehensive governance platforms to proactively detect and manage model risks, reinforcing accountability and building trust in AI-driven decisions. The rise in use of AI and ML models in regulated industries growth contribution during the forecast period in 2024 is 1.50%.

AI Model Risk Management Market Restraints

The key restraints on the AI model risk management market include: Resistance To Change Within Organizations Resistance to change within organizations is expected to hamper the growth of the AI model risk management market. Resistance to change remains a significant barrier to the adoption of AI Model Risk Management solutions. Many organizations are hesitant to overhaul existing risk governance practices or integrate new technologies into established workflows. This resistance often stems from a lack of awareness, fear of disruption and skepticism toward AI-driven oversight mechanisms. In some cases, organizational inertia and rigid hierarchical structures further delay decision-making and slow the implementation of model governance frameworks. As a result, even when the need for AI risk management is acknowledged, internal pushback can hinder timely adoption and reduce the overall effectiveness of risk mitigation efforts. Growth affected by resistance to change within organizations during the forecast period in 2024 is -2.03%.

AI Model Risk Management Market Trends

Major trends shaping the AI model risk management market include: Development Of Digital Identity To AI Agents Major companies operating in the AI model risk management market are focusing on developing innovative products such as digital identity to increase their market presence in the market. Digital identity refers to the digital representation of an entity, such as a user, device, or system, used to authenticate and authorize access to AI models, data, or infrastructure. Managing digital identities is critical to prevent unauthorized access, data misuse and model manipulation. For example, in May 2025, Microsoft Corporation, a US-based technology company, introduced Entra Agent ID, granting unique digital identities to AI agents enabling role-based access controls, credential revocation and full action logging. By assigning unique digital identities to AI agents, organizations can track, monitor and authenticate every action taken by AI systems. This parallels user identity management for humans, which is foundational for accountability and compliance. The ability to revoke or update an agent’s credentials helps rapidly respond to emerging risks, such as security breach or discovery of unethical agent behavior. Advancements In AI Technology In AI model Risk Management Major companies operating in the AI model risk management market are focusing on developing innovative solutions, such as advanced artificial intelligence (AI) models, to gain a competitive edge in the market. An advanced AI model refers to sophisticated artificial intelligence systems designed to perform complex tasks with high accuracy and efficiency. These models often leverage cutting-edge techniques in machine learning, deep learning and natural language processing to analyze vast amounts of data, make predictions and automate decision-making processes. For example, in July 2024, Zendata, a US-based developer of a security platform, launched an advanced AI model and data usage scanning platform, enhancing governance, bias detection and compliance across enterprise AI ecosystems. This innovative offering delivers comprehensive governance, bias detection and compliance capabilities across entire AI and data ecosystems, addressing the growing need for transparent and responsible AI deployment in enterprises.

Opportunities And Recommendations In The AI Model Risk Management Market

Opportunities – The top opportunities in the AI model risk management market segmented by component will arise in the solution segment, which will gain $3,329.46 million of global annual sales by 2029. The top opportunities in the AI model risk management market segmented by deployment mode will arise in the cloud-based segment, which will gain $3,652.45 million of global annual sales by 2029. The top opportunities in the AI model risk management market segmented by organization size will arise in the large enterprises segment, which will gain $2,899.76 million of global annual sales by 2029. The top opportunities in the AI model risk management market segmented by application will arise in the model validation segment, which will gain $1,724.68 million of global annual sales by 2029. The top opportunities in the AI model risk management market segmented by industry vertical will arise in the IT & telecommunications segment, which will gain $1,668.25 million of global annual sales by 2029. The AI model risk management market size will gain the most in the USA at $1,520.54 million. Recommendations- To take advantage of the opportunities, The Business Research Company recommends the AI model risk management companies to focus on strengthening digital identity capabilities for AI agents, focus on advancing AI model capabilities to strengthen governance and compliance, focus on the fastest growing service segment to maximize market expansion, focus on the cloud-based segment to capture high-growth opportunities, focus on the SME segment to drive high-growth market penetration, expand in emerging markets, focus on forming strategic partnerships to enhance capabilities and market reach, focus on structuring value-based pricing to reflect model complexity and compliance needs, focus on targeted digital campaigns for high-value decision makers, focus on building thought leadership through industry collaboration and data-driven insights, focus on the model monitoring segment to accelerate growth and resilience and focus on the healthcare segment to capture high-growth potential.