AI Model Risk Management Market Growth, Trends, and Forecast by 2031

Historic Data: 2021-2023   |   Base Year: 2024   |   Forecast Period: 2025-2031

AI Model Risk Management Market Size and Forecasts (2021 - 2031), Global and Regional Share, Trends, and Growth Opportunity Analysis Report Coverage : By Component (Software, Services); Organization Size (Large Enterprises, SMEs); Deployment (Cloud, On Premises); Risk Type (Security Risk, Ethical Risk, Operational Risk); End Users (BFSI, IT and Telecom, Healthcare, Retail & Ecommerce, Manufacturing, Others)

  • Report Date : Oct 2025
  • Report Code : TIPRE00039714
  • Category : Technology, Media and Telecommunications
  • Status : Upcoming
  • Available Report Formats : pdf-format excel-format
  • No. of Pages : 150
Page Updated: Jan 2025

AI overview of AI Model Risk Management Market


The AI Model Risk Management Market is poised for significant growth, with a projected market size reaching US$ XX million by 2031, reflecting a robust CAGR of 13.2% from 2025 to 2031. This market, which encompasses software and services, is driven by the increasing demand for interactive learning solutions and the integration of gamification in educational systems. Historical data from 2021 to 2023 indicates a strong foundation for this growth, as organizations, both large and small, seek to enhance their risk management strategies through AI technologies. Key trends include the rise of mobile learning and personalized education, which are reshaping how organizations approach training and skill development. The AI Model Risk Management Market report highlights these dynamics, providing valuable insights into market share and future opportunities.


The AI Model Risk Management Market is expected to register a CAGR of 13.2% from 2025 to 2031, with a market size expanding from US$ XX million in 2024 to US$ XX Million by 2031.

The report is segmented by Component (Software, Services); Organization Size (Large Enterprises, SMEs); Deployment (Cloud, On Premises); Risk Type (Security Risk, Ethical Risk, Operational Risk); End Users (BFSI, IT and Telecom, Healthcare, Retail & Ecommerce, Manufacturing, Others). The global analysis is further broken-down at regional level and major countries. The report offers the value in USD for the above analysis and segments

Purpose of the Report

The report AI Model Risk Management Market by The Insight Partners aims to describe the present landscape and future growth, top driving factors, challenges, and opportunities. This will provide insights to various business stakeholders, such as:

  • Technology Providers/Manufacturers: To understand the evolving market dynamics and know the potential growth opportunities, enabling them to make informed strategic decisions.
  • Investors: To conduct a comprehensive trend analysis regarding the market growth rate, market financial projections, and opportunities that exist across the value chain.
  • Regulatory bodies: To regulate policies and police activities in the market with the aim of minimizing abuse, preserving investor trust and confidence, and upholding the integrity and stability of the market.

AI Model Risk Management Market Segmentation

Component

  • Software
  • Services

Organization Size

  • Large Enterprises
  • SMEs

Deployment

  • Cloud
  • On Premises

Component

  • Software
  • Services

End Users

  • BFSI
  • IT and Telecom
  • Healthcare
  • Retail & Ecommerce
  • Manufacturing

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AI Model Risk Management Market: Strategic Insights

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AI Model Risk Management Market Growth Drivers

  • Growing Demand for Interactive and Engaging Learning Solutions: The increasing preference for interactive and engaging educational tools is driving the game-based learning market. Traditional methods are being replaced by more immersive, gamified experiences, which enhance student engagement, motivation, and retention. Game-based learning offers a dynamic, hands-on approach that caters to diverse learning styles, making education more enjoyable and effective. As schools, universities, and corporate training programs seek innovative ways to enhance learning outcomes, the demand for game-based learning solutions continues to grow.
  • Integration of Gamification in Education Systems: Educational institutions are increasingly integrating gamification techniques into their curriculum to improve learning outcomes. By incorporating elements such as leaderboards, achievements, and rewards, game-based learning platforms encourage active participation and healthy competition among learners. This gamification approach is seen as an effective way to boost student engagement, foster collaborative learning, and enhance long-term knowledge retention, driving the market’s growth in both academic and corporate sectors.

AI Model Risk Management Market Future Trends

  • Rise in Mobile Learning and Accessibility: A significant trend in the game-based learning market is the growing adoption of mobile learning solutions. With the widespread use of smartphones and tablets, game-based learning is becoming more accessible to learners worldwide. Mobile platforms provide flexibility, allowing students to learn anytime and anywhere, making education more convenient and adaptable to busy schedules. This trend is driving the expansion of game-based learning applications, particularly for K-12 education, e-learning platforms, and corporate training programs.
  • Personalized Learning Through AI and Adaptive Technologies: The integration of Artificial Intelligence (AI) and adaptive learning technologies into game-based learning platforms is reshaping the market. AI can personalize the learning experience by adapting the difficulty level and content based on individual learner performance. This trend allows for more tailored, self-paced learning, increasing the effectiveness of educational games. As educational institutions and organizations strive to provide more customized learning paths for students, AI-driven game-based learning solutions are gaining traction.

AI Model Risk Management Market Opportunities

  • Expanding in Corporate Training and Skill Development: The corporate training sector presents a significant opportunity for the game-based learning market. Businesses are increasingly adopting gamified solutions to train employees, particularly in soft skills, leadership development, and compliance training. Game-based learning platforms provide an engaging, risk-free environment for employees to develop and practice new skills, making it an attractive option for companies looking to enhance training efficiency. This growing trend in corporate learning offers substantial growth potential for the market.
  • Growth in Developing Regions: The game-based learning market is witnessing substantial growth in developing regions such as Asia-Pacific, Africa, and Latin America. As educational infrastructure improves and mobile penetration increases in these regions, there is a rising demand for affordable, accessible, and engaging learning solutions. Game-based learning offers a cost-effective way to improve education quality in resource-limited areas, providing significant opportunities for market expansion. Tailoring these solutions to local needs and languages further enhances market potential in these regions.

AI Model Risk Management Market Regional Insights

The regional trends and factors influencing the AI Model Risk Management Market throughout the forecast period have been thoroughly explained by the analysts at The Insight Partners. This section also discusses AI Model Risk Management Market segments and geography across North America, Europe, Asia Pacific, Middle East and Africa, and South and Central America.

AI Model Risk Management Market Report Scope

Report Attribute Details
Market size in 2024 US$ XX million
Market Size by 2031 US$ XX Million
Global CAGR (2025 - 2031) 13.2%
Historical Data 2021-2023
Forecast period 2025-2031
Segments Covered By Component
  • Software
  • Services
By Organization Size
  • Large Enterprises
  • SMEs
By Deployment
  • Cloud
  • On Premises
By Component
  • Software
  • Services
Regions and Countries Covered North America
  • US
  • Canada
  • Mexico
Europe
  • UK
  • Germany
  • France
  • Russia
  • Italy
  • Rest of Europe
Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • Rest of Asia-Pacific
South and Central America
  • Brazil
  • Argentina
  • Rest of South and Central America
Middle East and Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Rest of Middle East and Africa
Market leaders and key company profiles
  • Accenture
  • Amazon Web Services
  • DataRobot, Inc.
  • Deloitte
  • Google
  • International Business Machines Corporation
  • LogicGate
  • McKinsey & Company
  • Microsoft
  • SAS Institute

  • AI Model Risk Management Market Players Density: Understanding Its Impact on Business Dynamics

    The AI Model Risk Management Market is growing rapidly, driven by increasing end-user demand due to factors such as evolving consumer preferences, technological advancements, and greater awareness of the product's benefits. As demand rises, businesses are expanding their offerings, innovating to meet consumer needs, and capitalizing on emerging trends, which further fuels market growth.


    ai-model-risk-management-market-cagr

    • Get the AI Model Risk Management Market top key players overview

    Key Selling Points

    • Comprehensive Coverage: The report comprehensively covers the analysis of products, services, types, and end users of the AI Model Risk Management Market, providing a holistic landscape.
    • Expert Analysis: The report is compiled based on the in-depth understanding of industry experts and analysts.
    • Up-to-date Information: The report assures business relevance due to its coverage of recent information and data trends.
    • Customization Options: This report can be customized to cater to specific client requirements and suit the business strategies aptly.

    The research report on the AI Model Risk Management Market can, therefore, help spearhead the trail of decoding and understanding the industry scenario and growth prospects. Although there can be a few valid concerns, the overall benefits of this report tend to outweigh the disadvantages.


    Frequently Asked Questions

    1
    What are the options available for the customization of this report?
    Some of the customization options available based on the request are an additional 3–5 company profiles and country-specific analysis of 3–5 countries of your choice. Customizations are to be requested/discussed before making final order confirmation# as our team would review the same and check the feasibility
    2
    What are the deliverable formats of the market report?
    The report can be delivered in PDF/PPT format; we can also share excel dataset based on the request
    3
    What are the future trends of the AI model risk management market?
    Automated model validation tools and integrated risk management platforms are anticipated to play a significant role in the global AI model risk management market in the coming years
    4
    What are the driving factors impacting the global AI model risk management market?
    Regulatory compliance pressures, growing model complexity & scale, and real-world AI failures & reputational risks are the major factors driving the AI model risk management market
    5
    What is the expected CAGR of the AI model risk management market?
    The global AI model risk management market is expected to grow at a CAGR of 13.2% during the forecast period 2024 - 2031
    6
    Ankita Mittal
    Manager,
    Market Research & Consulting

    Ankita is a dynamic market research and consulting professional with over 8 years of experience across the technology, media, ICT, and electronics & semiconductor sectors. She has successfully led and delivered 100+ consulting and research assignments for global clients such as Microsoft, Oracle, NEC Corporation, SAP, KPMG, and Expeditors International. Her core competencies include market assessment, data analysis, forecasting, strategy formulation, competitive intelligence, and report writing.

    Ankita is adept at handling complete project cycles—from pre-sales proposal design and client discussions to post-sales delivery of actionable insights. She is skilled in managing cross-functional teams, structuring complex research modules, and aligning solutions with client-specific business goals. Her excellent communication, leadership, and presentation abilities have enabled her to consistently deliver value-driven outcomes in fast-paced and evolving market environments.

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