세계의 AI 거버넌스 시장 : 제품 유형별, 기능성별, 최종사용자별, 지역별 - 예측(-2029년)

The AI governance market is projected to grow from USD 890.6 million in 2024 to USD 5,776.0 million in 2029, with a CAGR of 45.3% during 2024-2029. The AI governance market is expected to experience substantial expansion in the next few years, fueled by growing recognition of the importance of risk management in AI deployments. Organizations have been investing more in AI governance tools as they realize the criticality of controlling AI risks. Regulated industries in finance and healthcare are leading the way in creating governance solutions for compliance with strict regulations. Increasing demands for trust, transparency, and accountability in using AI systems drive the market further as organizations emphasize responsible and ethical use of AI in various sectors.

"By product type, MLOps tools segment is expected to register the fastest market growth rate during the forecast period."

MLOps tools are expected to mark the highest growth rate during the forecast period as they streamline the entire development, deployment, and monitoring of machine learning models. This, in turn, enables management of the version control and continuous integration of models in a compliant manner with the regulatory standards, adding more transparency to the process. The sheer complexity of AI models and their requirements has been a giant factor that has moved organizations toward the adoption of MLOps tools, as these tools take care of complete AI lifecycle from data handling to real-time monitoring. Also, increased demand for governance and risk management model accountability in regulated industries fuels their growth.

"By functionality, risk management & compliance is expected to register the fastest market growth rate during the forecast period."

Risk management and compliance is expected to register the fastest market growth rate in the AI governance market as regulations continue to pile while the complexity in AI systems increases. Businesses in all industries understand that they need to factor in the risk related to bias, fairness, and transparency in AI models, especially in strictly regulated sectors such as finance, healthcare, and insurance. For example, AI-based governance solutions are being applied by financial firms to adhere to regulations of GDPR within the European Union, or the Fair Lending Act in U.S., which strictly monitors the usage of data and algorithms used in various decision-making processes. Healthcare organizations apply AI governance frameworks for the purpose of risk minimization and improving patient safety through AI-based diagnostic tools while being HIPAA compliant.

"By region, North America to have the largest market share in 2024, and Asia Pacific is slated to grow at the fastest rate during the forecast period."

North America will remain the market leader in 2024, driven by a robust and well-established AI ecosystem, alongside a substantial number of AI related regulations. Early adoption of AI technologies by leading tech companies, such as IBM, Microsoft, and Google, based in the U.S., drives AI governance in this region through embedding strong tools for compliance and risk management into their offerings. Besides, the U.S. government is proactively drafting new regulations regarding AI. For instance, a governance framework is being developed for enterprises, encouraged by the country's National AI Initiative Act.

Meanwhile, the growth in the AI governance market is expected to be the fastest in the Asia Pacific region. Here, AI adoption in China, Japan, and South Korea is occurring at a steep pace. These countries have substantial investments in AI technologies across sectors such as manufacturing, healthcare, and finance. Thus, there is growing demand for governance structures that ensure conformity with locally developing regulations. For instance, the AI regulations which will be implemented by China will focus on the visibility of the transparency and the decrease of biases in AI. This has resulted in investments into the solution for AI governance.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the AI governance market.

• By Company: Tier I - 28%, Tier II - 41%, and Tier III - 31%
• By Designation: C-Level Executives - 36%, D-Level Executives - 40%, and others - 24%
• By Region: North America - 35%, Europe - 21%, Asia Pacific - 30%, Middle East & Africa - 8%, and Latin America - 6%

The report includes the study of key players offering AI governance solutions. It profiles major vendors in the AI governance market. The major players in the AI governance market include Microsoft (US), IBM (US), Google (US), Salesforce (US), SAP (Germany), AWS (US), SAS Institute (US), FICO (US), Accenture (Ireland), Qlik (US), H2O.AI (US), Alteryx (US), DataRobot (UK), Dataiku (US), Domino Data Lab (US), SparkCognition (US), Collibra (US), OneTrust (US), Quest Software (US), Fiddler AI (US), Untangle AI (Singapore), 2021.AI (Denmark), Howso (US), Monitaur (US), Mind Foundry (UK), Credo AI (US), Holistic AI (UK), Fairly AI (Canada), Enzai (UK), ValidMind (US), FairNow (US), Mona Labs (US), Arthur AI (US), Trustible (US), Atlan (Singapore), ModelOp (US), Neptune AI (Poland), Patronus AI (US), and Datatron (US).

Research coverage

This research report categorizes the AI governance Market by Product Type (Data Privacy Tools, End-To-End AI Governance Platforms, Data Governance Platforms, MLOps Tools, LLMOps Tools, Responsible AI Toolkits, AI Governance Consulting Services, and AI Governance as a Service), by Functionality (Model Lifecycle Management, Risk Management & Compliance , Monitoring & Auditing, Transparency & Explainability, Data Governance, Ethics & Responsible AI, and Others), by End User (BFSI, Telecommunications, Government & Defense, Healthcare & Life Sciences, Manufacturing, Media & Entertainment, Retail & Consumer Goods, Software & Technology Providers, Automotive, and other enterprises), and by Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI governance market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, mergers and acquisitions, and recent developments associated with the AI governance market. Competitive analysis of upcoming startups in the AI governance market ecosystem is covered in this report.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI governance market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

• Analysis of key drivers (Increasing regulatory compliance pressures driving organizations to adopt governance frameworks, awareness of risk mitigation efforts prompting investments in AI governance tools, AI governance adoption in regulated industries fuels growth of governance solutions, demand for trust and transparency expanding the AI governance market), restraints (Lack of harmonized global standards for AI governance, high costs of implementing AI governance frameworks, and complexity in monitoring and managing AI models post-deployment), opportunities (Growing demand for ethical AI creates opportunities in bias mitigation solutions, integration with MLOps platforms expands the governance market, growth in AI adoption by SMEs fuels demand for scalable governance solutions, emerging regulatory frameworks open new market segments), and challenges (Resistance to change in established workflows, and limited understanding of AI risks and governance needs).
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI governance market.
• Market Development: Comprehensive information about lucrative markets - the report analyses the AI governance market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI governance market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), IBM (US), Google (US), Salesforce (US), SAP (Germany), AWS (US), SAS Institute (US), FICO (US), Accenture (Ireland), Qlik (US), H2O.AI (US), Alteryx (US), DataRobot (UK), Dataiku (US), Domino Data Lab (US), SparkCognition (US), Collibra (US), OneTrust (US), Quest Software (US), Fiddler AI (US), Untangle AI (Singapore), 2021.AI (Denmark), Howso (US), Monitaur (US), Mind Foundry (UK), and Credo AI (US) among others in the AI governance market. The report also helps stakeholders understand the pulse of the AI governance market and provides them with information on key market drivers, restraints, challenges, and opportunities.

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
  • 1.2.1 INCLUSIONS AND EXCLUSIONS
• 1.3 STUDY SCOPE
  • 1.3.1 MARKET SEGMENTATION & REGIONS COVERED
• 1.4 YEARS CONSIDERED
• 1.5 CURRENCY CONSIDERED
• 1.6 STAKEHOLDERS
• 1.7 SUMMARY OF CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Breakup of primary profiles
    • 2.1.2.2 Key insights from industry experts
• 2.2 DATA TRIANGULATION
• 2.3 MARKET SIZE ESTIMATION
  • 2.3.1 TOP-DOWN APPROACH
  • 2.3.2 BOTTOM-UP APPROACH
• 2.4 MARKET FORECAST
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN AI GOVERNANCE MARKET
• 4.2 AI GOVERNANCE MARKET: TOP THREE FUNCTIONALITIES
• 4.3 NORTH AMERICAN AI GOVERNANCE MARKET: TOP THREE PRODUCT TYPES AND END USERS
• 4.4 AI GOVERNANCE MARKET: BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Increasing regulatory compliance pressures driving organizations to adopt governance frameworks
    • 5.2.1.2 Awareness of risk mitigation efforts prompting investments in AI governance tools
    • 5.2.1.3 Need for compliance, credibility, safety, and decision-making fuels adoption of governance solutions
    • 5.2.1.4 Demand for trust and transparency
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Lack of harmonized global standards for AI governance
    • 5.2.2.2 High costs of implementing AI governance frameworks
    • 5.2.2.3 Complexity in monitoring and managing AI models post-deployment
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Growing demand for ethical AI creating opportunities in bias mitigation solutions
    • 5.2.3.2 Integration with MLOps platforms
    • 5.2.3.3 Rising adoption of AI by SMEs fueling demand for scalable governance solutions
    • 5.2.3.4 Emerging regulatory frameworks open new market segments
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Resistance to change in established workflows
    • 5.2.4.2 Limited understanding of AI risks and governance needs
• 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
• 5.4 PRICING ANALYSIS
  • 5.4.1 PRICING DATA, BY PRODUCT TYPE
  • 5.4.2 PRICING DATA, BY FUNCTIONALITY
• 5.5 SUPPLY CHAIN ANALYSIS
• 5.6 ECOSYSTEM
  • 5.6.1 END-TO-END AI GOVERNANCE PLATFORM VENDORS
  • 5.6.2 AI GOVERNANCE TOOLS VENDORS
  • 5.6.3 TRANSPARENCY AND EXPLAINABILITY VENDORS
  • 5.6.4 CLOUD HYPERSCALERS
  • 5.6.5 MLOPS AND LLMOPS VENDORS
  • 5.6.6 END USERS
  • 5.6.7 DATA PRIVACY VENDORS
  • 5.6.8 DATA GOVERNANCE AND CATALOG VENDORS
• 5.7 TECHNOLOGY ANALYSIS
  • 5.7.1 KEY TECHNOLOGIES
    • 5.7.1.1 Machine Learning (ML)
    • 5.7.1.2 Explainable AI (XAI)
    • 5.7.1.3 Federated Learning (FL)
    • 5.7.1.4 Differential privacy
    • 5.7.1.5 Automated model monitoring
  • 5.7.2 COMPLEMENTARY TECHNOLOGIES
    • 5.7.2.1 Cybersecurity
    • 5.7.2.2 Data encryption
    • 5.7.2.3 Identity & Access Management (IAM)
    • 5.7.2.4 Data Quality Management (DQM)
    • 5.7.2.5 Risk management systems
  • 5.7.3 ADJACENT TECHNOLOGIES
    • 5.7.3.1 Cloud computing
    • 5.7.3.2 Blockchain
    • 5.7.3.3 Natural Language Processing (NLP)
    • 5.7.3.4 Edge computing
    • 5.7.3.5 High-Performance Computing (HPC)
• 5.8 PATENT ANALYSIS
  • 5.8.1 METHODOLOGY
  • 5.8.2 PATENTS FILED, BY DOCUMENT TYPE
  • 5.8.3 INNOVATION AND PATENT APPLICATIONS
• 5.9 KEY CONFERENCES AND EVENTS (2025-2026)
• 5.10 REGULATORY LANDSCAPE
  • 5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.10.2 REGULATIONS: AI GOVERNANCE
    • 5.10.2.1 North America
      • 5.10.2.1.1 Algorithmic Accountability Act (2019, reintroduced in 2022) (US)
      • 5.10.2.1.2 Directive on Automated Decision-making (Canada)
    • 5.10.2.2 Europe
      • 5.10.2.2.1 UK AI Regulation White Paper
      • 5.10.2.2.2 European Union (EU) - AI Act
      • 5.10.2.2.3 Gesetz zur Regulierung Kunstlicher Intelligenz (AI Regulation Law)
      • 5.10.2.2.4 Artificial Intelligence 4.0 (AI 4.0) Program
      • 5.10.2.2.5 AI Strategy (2021), Data Protection Act
    • 5.10.2.3 Asia Pacific
      • 5.10.2.3.1 Personal Data Protection Bill (PDPB) & National Strategy on AI (NSAI)
      • 5.10.2.3.2 New Generation Artificial Intelligence Development Plan & AI Ethics Guidelines
      • 5.10.2.3.3 Framework Act on Intelligent Informatization
      • 5.10.2.3.4 AI Ethics Framework (Australia) & AI Strategy (New Zealand)
      • 5.10.2.3.5 Model AI Governance Framework
      • 5.10.2.3.6 Data Security Law (2021), AI Guidelines (China)
    • 5.10.2.4 Middle East & Africa
      • 5.10.2.4.1 Saudi Data & Artificial Intelligence Authority (SDAIA) Regulations
      • 5.10.2.4.2 UAE National AI Strategy 2031
      • 5.10.2.4.3 Qatar National AI Strategy
      • 5.10.2.4.4 National Artificial Intelligence Strategy (2021-2025)
      • 5.10.2.4.5 Egyptian Artificial Intelligence Strategy
      • 5.10.2.4.6 Kuwait National Development Plan (New Kuwait Vision 2035)
    • 5.10.2.5 Latin America
      • 5.10.2.5.1 Brazilian General Data Protection Law (LGPD)
      • 5.10.2.5.2 Federal Law on the Protection of Personal Data Held by Private Parties
      • 5.10.2.5.3 Argentina Personal Data Protection Law (PDPL) & AI Ethics Framework
      • 5.10.2.5.4 Chilean Data Protection Law & National AI Policy
      • 5.10.2.5.5 Colombian Data Protection Law (Law 1581) & AI Ethics Guidelines
      • 5.10.2.5.6 Peruvian Personal Data Protection Law & National AI Strategy
• 5.11 PORTER'S FIVE FORCES ANALYSIS
  • 5.11.1 THREAT OF NEW ENTRANTS
  • 5.11.2 THREAT OF SUBSTITUTES
  • 5.11.3 BARGAINING POWER OF SUPPLIERS
  • 5.11.4 BARGAINING POWER OF BUYERS
  • 5.11.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.12 KEY STAKEHOLDERS & BUYING CRITERIA
  • 5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.12.2 BUYING CRITERIA
• 5.13 INVESTMENT LANDSCAPE AND FUNDING SCENARIO
• 5.14 IMPACT OF GENERATIVE AI ON AI GOVERNANCE MARKET
  • 5.14.1 TOP USE CASES & MARKET POTENTIAL
    • 5.14.1.1 Bias detection and mitigation
    • 5.14.1.2 Automated compliance reporting
    • 5.14.1.3 Policy generation and documentation
    • 5.14.1.4 Dynamic risk assessment
    • 5.14.1.5 Auditing model transparency
• 5.15 AI GOVERNANCE LIFECYCLE FRAMEWORK
  • 5.15.1 ENVIRONMENTAL LAYER
  • 5.15.2 ORGANIZATIONAL LAYER
  • 5.15.3 AI SYSTEM LAYER
• 5.16 EVOLUTION OF AI GOVERNANCE
• 5.17 CASE STUDY ANALYSIS
  • 5.17.1 BFSI
    • 5.17.1.1 Fiddler AI Observability helped Tide scale its ML solutions to support its growth, better understand model outcomes, and align data science and business teams
    • 5.17.1.2 2021.AI collaborated with GF to create AI-derived model that could simulate fraud patterns among household insurance claims
  • 5.17.2 SOFTWARE & TECHNOLOGY PROVIDERS
    • 5.17.2.1 LinkGRC enhanced its GRC service offerings with 2021.AI's AI-based solutions
    • 5.17.2.2 Prometric championed Responsible AI in assessments with long-term partner 2021.AI
  • 5.17.3 RETAIL & CONSUMER GOODS
    • 5.17.3.1 Conjura reduced time to detect and resolve model drift from days to hours with Fiddler

6 AI GOVERNANCE MARKET, BY PRODUCT TYPE

• 6.1 INTRODUCTION
  • 6.1.1 PRODUCT TYPES: AI GOVERNANCE MARKET DRIVERS
• 6.2 DATA PRIVACY TOOLS
  • 6.2.1 NEED FOR DATA PRIVACY TOOLS TO GROW DUE TO INCREASED REGULATORY SCRUTINY AND RISING THREAT OF DATA BREACHES
• 6.3 END-TO-END AI GOVERNANCE PLATFORMS
  • 6.3.1 DEMAND FOR END-TO-END AI GOVERNANCE PLATFORMS TO GROW TO ALIGN AI WITH REGULATORY AND ETHICAL STANDARDS
• 6.4 DATA GOVERNANCE PLATFORMS
  • 6.4.1 DATA GOVERNANCE PLATFORMS TO TRACK DATA QUALITY AND MITIGATE RISKS ASSOCIATED WITH AI BIASES
• 6.5 MLOPS TOOLS
  • 6.5.1 REGULATORY COMPLIANCE AND ETHICAL CONCERNS AROUND AI GOVERNANCE TO PLAY CRITICAL ROLE IN GROWTH OF MLOPS TOOLS
    • 6.5.1.1 Model development
    • 6.5.1.2 Model deployment
    • 6.5.1.3 Model monitoring
• 6.6 LLMOPS TOOLS
  • 6.6.1 CONVERGENCE OF AI GOVERNANCE AND LLMOPS TO ENSURE BETTER MODEL PERFORMANCE TRACKING TO BOOST MARKET GROWTH
• 6.7 RESPONSIBLE AI TOOLKITS
  • 6.7.1 NEED FOR ORGANIZATIONS TO BALANCE INNOVATION WITH GOVERNANCE TO DRIVE GROWTH OF RESPONSIBLE AI TOOLKITS
• 6.8 AI GOVERNANCE CONSULTING SERVICES
  • 6.8.1 AI GOVERNANCE CONSULTING SERVICES TO OFFER CRITICAL EXPERTISE TO NAVIGATE COMPLEXITIES OF ETHICAL AI DEPLOYMENT
• 6.9 AI GOVERNANCE AS A SERVICE
  • 6.9.1 AI GOVERNANCE AS A SERVICE PLATFORMS TO DETECT AND MITIGATE RISKS AND ENHANCE AI SYSTEM ACCOUNTABILITY

7 AI GOVERNANCE MARKET, BY FUNCTIONALITY

• 7.1 INTRODUCTION
  • 7.1.1 FUNCTIONALITIES: AI GOVERNANCE MARKET DRIVERS
• 7.2 MODEL LIFECYCLE MANAGEMENT
  • 7.2.1 MODEL LIFECYCLE MANAGEMENT TO MAINTAIN OPERATIONAL EFFICIENCY, ENSURE COMPLIANCE, AND ADDRESS ETHICAL CONCERNS SURROUNDING AI USAGE
  • 7.2.2 AUTOMATED VERSIONING
  • 7.2.3 MODEL-IN-PRODUCTION MANAGEMENT
  • 7.2.4 AI INVENTORY MANAGEMENT
  • 7.2.5 MODEL DIVERGENCE DETECTION
• 7.3 RISK MANAGEMENT & COMPLIANCE
  • 7.3.1 EFFECTIVE COMPLIANCE FRAMEWORKS COMBINED WITH REGULAR AUDITS AND ETHICAL AI TRAINING TO MINIMIZE RISKS IN AI DEPLOYMENT
  • 7.3.2 MODEL RISK MANAGEMENT
  • 7.3.3 REGULATORY COMPLIANCE
  • 7.3.4 RISK IDENTIFICATION & MITIGATION
  • 7.3.5 THIRD-PARTY RISK EVALUATION
• 7.4 MONITORING & AUDITING
  • 7.4.1 MONITORING AND AUDITING TO ENSURE TRANSPARENCY, ACCOUNTABILITY, AND COMPLIANCE IN DEPLOYMENT AND OPERATION OF AI SYSTEMS
  • 7.4.2 AI MODEL MONITORING
  • 7.4.3 DRIFT & BIAS MITIGATION
  • 7.4.4 ANOMALY DETECTION
  • 7.4.5 PERFORMANCE DEGRADATION ALERTS
• 7.5 TRANSPARENCY & EXPLAINABILITY
  • 7.5.1 TRANSPARENCY & EXPLAINABILITY TO ENSURE ACCOUNTABILITY, ETHICAL INTEGRITY, AND USER TRUST
  • 7.5.2 MODEL PREDICTION EXPLAINABILITY
  • 7.5.3 MODEL TRANSPARENCY
  • 7.5.4 MODEL DOCUMENTATION & REPORTING
• 7.6 DATA GOVERNANCE
  • 7.6.1 DATA GOVERNANCE TO ENSURE AI TRAINING AND OPERATIONS DATA IS ACCURATE, COMPLETE, CONSISTENT, AND PROTECTED FROM BIASES OR MISUSE
  • 7.6.2 DATA LINEAGE
  • 7.6.3 DATA DISCOVERY & CLASSIFICATION
  • 7.6.4 DATA PROVENANCE
• 7.7 ETHICS & RESPONSIBLE AI
  • 7.7.1 ETHICAL AI TO EMPHASIZE FAIRNESS, TRANSPARENCY, AND ACCOUNTABILITY, AND MINIMIZE BIAS
  • 7.7.2 AI POLICY CREATION
  • 7.7.3 POLICY BREACH ALERTS
  • 7.7.4 AI ETHICS MANAGEMENT
  • 7.7.5 ADHERENCE VALIDATION
  • 7.7.6 AI REGISTRY
• 7.8 OTHER FUNCTIONALITY TYPES

8 AI GOVERNANCE MARKET, BY END USER

• 8.1 INTRODUCTION
  • 8.1.1 END USERS: AI GOVERNANCE MARKET DRIVERS
• 8.2 BFSI
  • 8.2.1 FINANCIAL INSTITUTIONS TO LEVERAGE AI GOVERNANCE TOOLS TO ALIGN WITH NEW REGULATIONS, MITIGATE RISKS, AND ENHANCE TRANSPARENCY
  • 8.2.2 BANKING
  • 8.2.3 FINANCIAL SERVICES
  • 8.2.4 INSURANCE
• 8.3 TELECOMMUNICATIONS
  • 8.3.1 NEED TO ADDRESS GROWING USE OF AI IN MANAGING NETWORKS, CUSTOMER DATA, AND SERVICES TO DRIVE MARKET GROWTH
• 8.4 GOVERNMENT & DEFENSE
  • 8.4.1 ADVANCEMENTS IN AI-DRIVEN CYBERSECURITY SYSTEMS TO HIGHLIGHT IMPORTANCE OF GOVERNANCE IN SAFEGUARDING NATIONAL SECURITY, ETHICS, AND COMPLIANCE
• 8.5 HEALTHCARE & LIFE SCIENCES
  • 8.5.1 RISE OF AI-POWERED CLINICAL DECISION SUPPORT SYSTEMS AND RECOMMENDATIONS FOR DIAGNOSIS AND TREATMENT BASED ON VAST DATASETS TO PROPEL MARKET
• 8.6 MANUFACTURING
  • 8.6.1 RISE OF INDUSTRY 4.0 AND NEED TO LEVERAGE AI TO ENHANCE PRODUCTIVITY, STREAMLINE OPERATIONS, AND REDUCE COSTS TO FUEL MARKET GROWTH
• 8.7 RETAIL & CONSUMER GOODS
  • 8.7.1 NEED TO OPTIMIZE OPERATIONS, ENHANCE CUSTOMER EXPERIENCES, AND STREAMLINE SUPPLY CHAINS TO ACCELERATE MARKET GROWTH
• 8.8 SOFTWARE & TECHNOLOGY PROVIDERS
  • 8.8.1 SOFTWARE & TECHNOLOGY PROVIDERS TO RELY ON AI GOVERNANCE TO ENSURE MODELS AND AI SYSTEMS STAY COMPLIANT, ETHICAL, AND TRANSPARENT
  • 8.8.2 CLOUD HYPERSCALERS
  • 8.8.3 FOUNDATION MODEL/LLM PROVIDERS
  • 8.8.4 DATA ANNOTATORS
  • 8.8.5 AI TRAINING DATASET PROVIDERS
  • 8.8.6 IT & IT-ENABLED SERVICE PROVIDERS
• 8.9 AUTOMOTIVE
  • 8.9.1 AI ALGORITHMS TO IMPROVE ELECTRONIC VEHICLE PERFORMANCE WHILE ADHERING TO ENVIRONMENTAL REGULATIONS
• 8.10 MEDIA & ENTERTAINMENT
  • 8.10.1 EMPHASIS ON TRANSPARENCY, INTELLECTUAL PROPERTY PROTECTION, AND PRIVACY TO BOLSTER MARKET GROWTH
• 8.11 OTHER END USERS

9 AI GOVERNANCE MARKET, BY REGION

• 9.1 INTRODUCTION
• 9.2 NORTH AMERICA
  • 9.2.1 NORTH AMERICA: AI GOVERNANCE MARKET DRIVERS
  • 9.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 9.2.3 US
    • 9.2.3.1 Need to improve efficiency, decision-making, and robust governance frameworks to manage risks, ethical concerns, and compliance to drive market
  • 9.2.4 CANADA
    • 9.2.4.1 Increasing data security concerns, need for ethical AI practices, robust government support, and strategic investments to propel market
• 9.3 EUROPE
  • 9.3.1 EUROPE: AI GOVERNANCE MARKET DRIVERS
  • 9.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 9.3.3 UK
    • 9.3.3.1 Regulatory pressures, sector-specific needs, and advancements in AI transparency tools to fuel market growth
  • 9.3.4 GERMANY
    • 9.3.4.1 Advancements coupled with strong regulatory push and corporate accountability to boost demand for AI governance
  • 9.3.5 FRANCE
    • 9.3.5.1 Increasing demand for ethical AI solutions, regulatory compliance, and heightened awareness of risks to accelerate market growth
  • 9.3.6 ITALY
    • 9.3.6.1 Government investment in AI innovation and governance to prioritize responsible and transparent AI usage to boost market growth
  • 9.3.7 SPAIN
    • 9.3.7.1 Increasing regulatory scrutiny from government and European Union (EU) and allocation of significant funds to R&D under National Strategy for Artificial Intelligence to foster market growth
  • 9.3.8 NETHERLANDS
    • 9.3.8.1 Government investment in AI infrastructure to strengthen local AI capabilities to boost demand for AI governance
  • 9.3.9 REST OF EUROPE
• 9.4 ASIA PACIFIC
  • 9.4.1 ASIA PACIFIC: AI GOVERNANCE MARKET DRIVERS
  • 9.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 9.4.3 CHINA
    • 9.4.3.1 Advancements paired with China's strategic goals to mitigate AI risks to accelerate adoption of AI governance solutions
  • 9.4.4 INDIA
    • 9.4.4.1 Government initiatives, increased adoption of AI technologies across industries, and rising concerns over data privacy and ethical use of AI systems to drive market
  • 9.4.5 JAPAN
    • 9.4.5.1 Focus on technological innovation, government support, and increasing awareness of AI's ethical and legal implications to bolster market growth
  • 9.4.6 SOUTH KOREA
    • 9.4.6.1 Investment in AI governance models to balance performance with cost efficiency to accelerate adoption of AI governance solutions
  • 9.4.7 SINGAPORE
    • 9.4.7.1 Introduction of Model AI Governance Framework combined with substantial investments in training programs for local professionals to boost market growth
  • 9.4.8 AUSTRALIA
    • 9.4.8.1 Rising adoption of AI technologies and establishment of National Artificial Intelligence Centre (NAIC) to fuel market growth
  • 9.4.9 REST OF ASIA PACIFIC
• 9.5 MIDDLE EAST & AFRICA
  • 9.5.1 MIDDLE EAST & AFRICA: AI GOVERNANCE MARKET DRIVERS
  • 9.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 9.5.3 SAUDI ARABIA
    • 9.5.3.1 Focus on becoming global leader in AI through its Vision 2030 initiative to bolster market growth
  • 9.5.4 UAE
    • 9.5.4.1 Focus on digital transformation and implementation of UAE Artificial Intelligence Strategy 2031 to boost market growth
  • 9.5.5 QATAR
    • 9.5.5.1 Qatar's commitment to leveraging AI for economic diversification aligning with its National Vision 2030 to enhance market growth
  • 9.5.6 TURKEY
    • 9.5.6.1 Implementation of National Artificial Intelligence Strategy to foster demand for AI governance
  • 9.5.7 REST OF MIDDLE EAST
  • 9.5.8 AFRICA
    • 9.5.8.1 Need for ethical AI deployment, transparency, and regulatory oversight to foster adoption of AI governance
• 9.6 LATIN AMERICA
  • 9.6.1 LATIN AMERICA: AI GOVERNANCE MARKET DRIVERS
  • 9.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 9.6.3 BRAZIL
    • 9.6.3.1 Need for regulatory frameworks, ethical guidelines, governance mechanisms, and evolving data protection landscape to boost market growth
  • 9.6.4 MEXICO
    • 9.6.4.1 Regulatory initiatives, technological advancements, and increasing investment in AI technologies to augment market growth
  • 9.6.5 ARGENTINA
    • 9.6.5.1 Robust technological talent pool nurtured by universities and research institutions to accelerate market growth
  • 9.6.6 REST OF LATIN AMERICA

10 COMPETITIVE LANDSCAPE

• 10.1 OVERVIEW
• 10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
• 10.3 REVENUE ANALYSIS
• 10.4 MARKET SHARE ANALYSIS
  • 10.4.1 MARKET RANKING ANALYSIS
• 10.5 PRODUCT/BRAND COMPARISON
  • 10.5.1 AMAZON SAGEMAKER (AWS)
  • 10.5.2 DOMINO AI GOVERNANCE (DOMINO DATA LABS)
  • 10.5.3 EXPLAINABLE AI (GOOGLE)
  • 10.5.4 WATSONX.GOVERNANCE (IBM)
  • 10.5.5 TRUSTWORTHY AI (SAS INSTITUTE)
  • 10.5.6 RESPONSIBLE AI (SAP)
  • 10.5.7 AI IMPLEMENTATION BUNDLE (SALESFORCE)
  • 10.5.8 FICO RESPONSIBLE AI (FICO)
  • 10.5.9 RESPONSIBLE AI GOVERNANCE & CONSULTING (ACCENTURE)
• 10.6 COMPANY VALUATION AND FINANCIAL METRICS
• 10.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
  • 10.7.1 STARS
  • 10.7.2 EMERGING LEADERS
  • 10.7.3 PERVASIVE PLAYERS
  • 10.7.4 PARTICIPANTS
  • 10.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
    • 10.7.5.1 Company footprint
    • 10.7.5.2 Product type footprint
    • 10.7.5.3 Functionality footprint
    • 10.7.5.4 End-user footprint
    • 10.7.5.5 Regional footprint
• 10.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
  • 10.8.1 PROGRESSIVE COMPANIES
  • 10.8.2 RESPONSIVE COMPANIES
  • 10.8.3 DYNAMIC COMPANIES
  • 10.8.4 STARTING BLOCKS
  • 10.8.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023
    • 10.8.5.1 Detailed list of key start-ups/SMEs
    • 10.8.5.2 Competitive benchmarking of key start-ups/SMEs
• 10.9 COMPETITIVE SCENARIO AND TRENDS
  • 10.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
  • 10.9.2 DEALS

11 COMPANY PROFILES

• 11.1 INTRODUCTION
• 11.2 KEY PLAYERS
  • 11.2.1 IBM
    • 11.2.1.1 Business overview
    • 11.2.1.2 Products/Solutions/Services offered
    • 11.2.1.3 Recent developments
      • 11.2.1.3.1 Product launches
      • 11.2.1.3.2 Deals
    • 11.2.1.4 MnM view
      • 11.2.1.4.1 Right to win
      • 11.2.1.4.2 Strategic choices
      • 11.2.1.4.3 Weaknesses and competitive threats
  • 11.2.2 MICROSOFT
    • 11.2.2.1 Business overview
    • 11.2.2.2 Products/Solutions/Services offered
    • 11.2.2.3 Recent developments
      • 11.2.2.3.1 Product launches
      • 11.2.2.3.2 Deals
    • 11.2.2.4 MnM view
      • 11.2.2.4.1 Right to win
      • 11.2.2.4.2 Strategic choices
      • 11.2.2.4.3 Weaknesses and competitive threats
  • 11.2.3 GOOGLE
    • 11.2.3.1 Business overview
    • 11.2.3.2 Products/Solutions/Services offered
    • 11.2.3.3 Recent developments
      • 11.2.3.3.1 Deals
    • 11.2.3.4 MnM view
      • 11.2.3.4.1 Right to win
      • 11.2.3.4.2 Strategic choices
      • 11.2.3.4.3 Weaknesses and competitive threats
  • 11.2.4 SALESFORCE
    • 11.2.4.1 Business overview
    • 11.2.4.2 Products/Solutions/Services offered
    • 11.2.4.3 Recent developments
      • 11.2.4.3.1 Product launches
      • 11.2.4.3.2 Deals
    • 11.2.4.4 MnM view
      • 11.2.4.4.1 Right to win
      • 11.2.4.4.2 Strategic choices
      • 11.2.4.4.3 Weaknesses and competitive threats
  • 11.2.5 SAP
    • 11.2.5.1 Business overview
    • 11.2.5.2 Products/Solutions/Services offered
    • 11.2.5.3 Recent developments
      • 11.2.5.3.1 Deals
    • 11.2.5.4 MnM view
      • 11.2.5.4.1 Right to win
      • 11.2.5.4.2 Strategic choices
      • 11.2.5.4.3 Weaknesses and competitive threats
  • 11.2.6 AWS
    • 11.2.6.1 Business overview
    • 11.2.6.2 Products/Solutions/Services offered
    • 11.2.6.3 Recent developments
      • 11.2.6.3.1 Product launches
      • 11.2.6.3.2 Deals
  • 11.2.7 SAS INSTITUTE
    • 11.2.7.1 Business overview
    • 11.2.7.2 Products/Solutions/Services offered
    • 11.2.7.3 Recent developments
      • 11.2.7.3.1 Product launches
  • 11.2.8 FICO
    • 11.2.8.1 Business overview
    • 11.2.8.2 Products/Solutions/Services offered
  • 11.2.9 ACCENTURE
    • 11.2.9.1 Business overview
    • 11.2.9.2 Products/Solutions/Services offered
    • 11.2.9.3 Recent developments
      • 11.2.9.3.1 Deals
• 11.3 OTHER PLAYERS
  • 11.3.1 ONETRUST
  • 11.3.2 QLIK
  • 11.3.3 H20.AI
  • 11.3.4 ALTERYX
  • 11.3.5 DATAROBOT
  • 11.3.6 DATAIKU
  • 11.3.7 DOMINO DATA LABS
  • 11.3.8 SPARKCOGNITION
  • 11.3.9 COLLIBRA
  • 11.3.10 QUEST SOFTWARE
  • 11.3.11 SECURITI
• 11.4 START-UPS/SMES
  • 11.4.1 MONITAUR
    • 11.4.1.1 Business overview
    • 11.4.1.2 Products/Solutions/Services offered
    • 11.4.1.3 Recent developments
      • 11.4.1.3.1 Deals
  • 11.4.2 FIDDLER AI
  • 11.4.3 UNTANGLE AI
  • 11.4.4 2021.AI
  • 11.4.5 HOWSO
  • 11.4.6 MIND FOUNDRY
  • 11.4.7 CREDO AI
  • 11.4.8 HOLISTIC AI
  • 11.4.9 FAIRLY AI
  • 11.4.10 ENZAI
  • 11.4.11 VALIDMIND
  • 11.4.12 FAIRNOW
  • 11.4.13 MONA LABS
  • 11.4.14 ARTHUR AI
  • 11.4.15 TRUSTIBLE
  • 11.4.16 ATLAN
  • 11.4.17 MODELOP
  • 11.4.18 NEPTUNE.AI
  • 11.4.19 PATRONUS AI
  • 11.4.20 DATATRON
  • 11.4.21 MODOLUS
  • 11.4.22 CALVIN RISK
  • 11.4.23 SAIDOT
  • 11.4.24 CENSIUS
  • 11.4.25 BREEZEML
  • 11.4.26 ANCH.AI
  • 11.4.27 PRODAGO
  • 11.4.28 QUANTPI
  • 11.4.29 YOOI

12 ADJACENT AND RELATED MARKETS

• 12.1 INTRODUCTION
• 12.2 AI MODEL RISK MANAGEMENT MARKET - GLOBAL FORECAST TO 2029
  • 12.2.1 MARKET DEFINITION
  • 12.2.2 MARKET OVERVIEW
    • 12.2.2.1 AI model risk management market, by offering
    • 12.2.2.2 AI model risk management market, by risk type
    • 12.2.2.3 AI model risk management market, by application
    • 12.2.2.4 AI model risk management market, by vertical
    • 12.2.2.5 AI model risk management market, by region
• 12.3 ARTIFICIAL INTELLIGENCE (AI) MARKET - GLOBAL FORECAST TO 2030
  • 12.3.1 MARKET DEFINITION
  • 12.3.2 MARKET OVERVIEW
    • 12.3.2.1 Artificial intelligence market, by offering
    • 12.3.2.2 Artificial intelligence market, by business function
    • 12.3.2.3 Artificial intelligence market, by technology
    • 12.3.2.4 Artificial intelligence market, by vertical
    • 12.3.2.5 Artificial intelligence market, by region

13 APPENDIX

• 13.1 DISCUSSION GUIDE
• 13.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 13.3 CUSTOMIZATION OPTIONS
• 13.4 RELATED REPORTS
• 13.5 AUTHOR DETAILS