Summary

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.

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Table of Contents

1 INTRODUCTION 35
1.1 STUDY OBJECTIVES 35
1.2 MARKET DEFINITION 35
1.2.1 INCLUSIONS AND EXCLUSIONS 36
1.3 STUDY SCOPE 37
1.3.1 MARKET SEGMENTATION & REGIONS COVERED 37
1.4 YEARS CONSIDERED 40
1.5 CURRENCY CONSIDERED 40
1.6 STAKEHOLDERS 40
1.7 SUMMARY OF CHANGES 41
2 RESEARCH METHODOLOGY 42
2.1 RESEARCH DATA 42
2.1.1 SECONDARY DATA 43
2.1.2 PRIMARY DATA 43
2.1.2.1 Breakup of primary profiles 44
2.1.2.2 Key insights from industry experts 44
2.2 DATA TRIANGULATION 45
2.3 MARKET SIZE ESTIMATION 46
2.3.1 TOP-DOWN APPROACH 46
2.3.2 BOTTOM-UP APPROACH 47
2.4 MARKET FORECAST 51
2.5 RESEARCH ASSUMPTIONS 52
2.6 RESEARCH LIMITATIONS 53
3 EXECUTIVE SUMMARY 54
4 PREMIUM INSIGHTS 59
4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN AI GOVERNANCE MARKET 59
4.2 AI GOVERNANCE MARKET: TOP THREE FUNCTIONALITIES 59
4.3 NORTH AMERICAN AI GOVERNANCE MARKET: TOP THREE PRODUCT TYPES
AND END USERS 60
4.4 AI GOVERNANCE MARKET: BY REGION 60
5 MARKET OVERVIEW AND INDUSTRY TRENDS 61
5.1 INTRODUCTION 61

5.2 MARKET DYNAMICS 61
5.2.1 DRIVERS 62
5.2.1.1 Increasing regulatory compliance pressures driving organizations to adopt governance frameworks 62
5.2.1.2 Awareness of risk mitigation efforts prompting investments in AI governance tools 63
5.2.1.3 Need for compliance, credibility, safety, and decision-making fuels adoption of governance solutions 63
5.2.1.4 Demand for trust and transparency 64
5.2.2 RESTRAINTS 64
5.2.2.1 Lack of harmonized global standards for AI governance 64
5.2.2.2 High costs of implementing AI governance frameworks 65
5.2.2.3 Complexity in monitoring and managing AI models post-deployment 65
5.2.3 OPPORTUNITIES 66
5.2.3.1 Growing demand for ethical AI creating opportunities in bias mitigation solutions 66
5.2.3.2 Integration with MLOps platforms 66
5.2.3.3 Rising adoption of AI by SMEs fueling demand for scalable governance solutions 67
5.2.3.4 Emerging regulatory frameworks open new market segments 67
5.2.4 CHALLENGES 68
5.2.4.1 Resistance to change in established workflows 68
5.2.4.2 Limited understanding of AI risks and governance needs 68
5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 69
5.4 PRICING ANALYSIS 70
5.4.1 PRICING DATA, BY PRODUCT TYPE 72
5.4.2 PRICING DATA, BY FUNCTIONALITY 73
5.5 SUPPLY CHAIN ANALYSIS 74
5.6 ECOSYSTEM 76
5.6.1 END-TO-END AI GOVERNANCE PLATFORM VENDORS 78
5.6.2 AI GOVERNANCE TOOLS VENDORS 79
5.6.3 TRANSPARENCY AND EXPLAINABILITY VENDORS 79
5.6.4 CLOUD HYPERSCALERS 79
5.6.5 MLOPS AND LLMOPS VENDORS 79
5.6.6 END USERS 80
5.6.7 DATA PRIVACY VENDORS 80
5.6.8 DATA GOVERNANCE AND CATALOG VENDORS 80
5.7 TECHNOLOGY ANALYSIS 80
5.7.1 KEY TECHNOLOGIES 81
5.7.1.1 Machine Learning (ML) 81
5.7.1.2 Explainable AI (XAI) 81
5.7.1.3 Federated Learning (FL) 81

5.7.1.4 Differential privacy 82
5.7.1.5 Automated model monitoring 82
5.7.2 COMPLEMENTARY TECHNOLOGIES 82
5.7.2.1 Cybersecurity 82
5.7.2.2 Data encryption 82
5.7.2.3 Identity & Access Management (IAM) 83
5.7.2.4 Data Quality Management (DQM) 83
5.7.2.5 Risk management systems 83
5.7.3 ADJACENT TECHNOLOGIES 84
5.7.3.1 Cloud computing 84
5.7.3.2 Blockchain 84
5.7.3.3 Natural Language Processing (NLP) 84
5.7.3.4 Edge computing 84
5.7.3.5 High-Performance Computing (HPC) 85
5.8 PATENT ANALYSIS 85
5.8.1 METHODOLOGY 85
5.8.2 PATENTS FILED, BY DOCUMENT TYPE 85
5.8.3 INNOVATION AND PATENT APPLICATIONS 86
5.9 KEY CONFERENCES AND EVENTS (2025–2026) 91
5.10 REGULATORY LANDSCAPE 92
5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 92
5.10.2 REGULATIONS: AI GOVERNANCE 96
5.10.2.1 North America 96
5.10.2.1.1 Algorithmic Accountability Act (2019, reintroduced in 2022) (US) 96
5.10.2.1.2 Directive on Automated Decision-making (Canada) 96
5.10.2.2 Europe 96
5.10.2.2.1 UK AI Regulation White Paper 96
5.10.2.2.2 European Union (EU) - AI Act 96
5.10.2.2.3 Gesetz zur Regulierung Künstlicher Intelligenz (AI Regulation Law) 96
5.10.2.2.4 Artificial Intelligence 4.0 (AI 4.0) Program 97
5.10.2.2.5 AI Strategy (2021), Data Protection Act 97
5.10.2.3 Asia Pacific 97
5.10.2.3.1 Personal Data Protection Bill (PDPB) & National Strategy on AI (NSAI) 97
5.10.2.3.2 New Generation Artificial Intelligence Development Plan & AI Ethics Guidelines 97
5.10.2.3.3 Framework Act on Intelligent Informatization 97
5.10.2.3.4 AI Ethics Framework (Australia) & AI Strategy (New Zealand) 97
5.10.2.3.5 Model AI Governance Framework 98
5.10.2.3.6 Data Security Law (2021), AI Guidelines (China) 98

5.10.2.4 Middle East & Africa 98
5.10.2.4.1 Saudi Data & Artificial Intelligence Authority (SDAIA) Regulations 98
5.10.2.4.2 UAE National AI Strategy 2031 98
5.10.2.4.3 Qatar National AI Strategy 98
5.10.2.4.4 National Artificial Intelligence Strategy (2021–2025) 98
5.10.2.4.5 Egyptian Artificial Intelligence Strategy 98
5.10.2.4.6 Kuwait National Development Plan
(New Kuwait Vision 2035) 99
5.10.2.5 Latin America 99
5.10.2.5.1 Brazilian General Data Protection Law (LGPD) 99
5.10.2.5.2 Federal Law on the Protection of Personal Data Held by Private Parties 99
5.10.2.5.3 Argentina Personal Data Protection Law (PDPL) & AI Ethics Framework 99
5.10.2.5.4 Chilean Data Protection Law & National AI Policy 99
5.10.2.5.5 Colombian Data Protection Law (Law 1581) &
AI Ethics Guidelines 100
5.10.2.5.6 Peruvian Personal Data Protection Law &
National AI Strategy 100
5.11 PORTER’S FIVE FORCES ANALYSIS 100
5.11.1 THREAT OF NEW ENTRANTS 101
5.11.2 THREAT OF SUBSTITUTES 101
5.11.3 BARGAINING POWER OF SUPPLIERS 101
5.11.4 BARGAINING POWER OF BUYERS 102
5.11.5 INTENSITY OF COMPETITIVE RIVALRY 102
5.12 KEY STAKEHOLDERS & BUYING CRITERIA 102
5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS 102
5.12.2 BUYING CRITERIA 103
5.13 INVESTMENT LANDSCAPE AND FUNDING SCENARIO 104
5.14 IMPACT OF GENERATIVE AI ON AI GOVERNANCE MARKET 108
5.14.1 TOP USE CASES & MARKET POTENTIAL 108
5.14.1.1 Bias detection and mitigation 109
5.14.1.2 Automated compliance reporting 109
5.14.1.3 Policy generation and documentation 109
5.14.1.4 Dynamic risk assessment 109
5.14.1.5 Auditing model transparency 109
5.15 AI GOVERNANCE LIFECYCLE FRAMEWORK 110
5.15.1 ENVIRONMENTAL LAYER 110
5.15.2 ORGANIZATIONAL LAYER 111
5.15.3 AI SYSTEM LAYER 111
5.16 EVOLUTION OF AI GOVERNANCE 112

5.17 CASE STUDY ANALYSIS 114
5.17.1 BFSI 114
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 114
5.17.1.2 2021.AI collaborated with GF to create AI-derived model that could simulate fraud patterns among household insurance claims 114
5.17.2 SOFTWARE & TECHNOLOGY PROVIDERS 115
5.17.2.1 LinkGRC enhanced its GRC service offerings with 2021.AI’s AI-based solutions 115
5.17.2.2 Prometric championed Responsible AI in assessments with long-term partner 2021.AI 116
5.17.3 RETAIL & CONSUMER GOODS 116
5.17.3.1 Conjura reduced time to detect and resolve model drift from days to hours with Fiddler 116
6 AI GOVERNANCE MARKET, BY PRODUCT TYPE 117
6.1 INTRODUCTION 118
6.1.1 PRODUCT TYPES: AI GOVERNANCE MARKET DRIVERS 118
6.2 DATA PRIVACY TOOLS 120
6.2.1 NEED FOR DATA PRIVACY TOOLS TO GROW DUE TO INCREASED REGULATORY SCRUTINY AND RISING THREAT OF DATA BREACHES 120
6.3 END-TO-END AI GOVERNANCE PLATFORMS 121
6.3.1 DEMAND FOR END-TO-END AI GOVERNANCE PLATFORMS TO GROW TO ALIGN AI WITH REGULATORY AND ETHICAL STANDARDS 121
6.4 DATA GOVERNANCE PLATFORMS 123
6.4.1 DATA GOVERNANCE PLATFORMS TO TRACK DATA QUALITY AND MITIGATE RISKS ASSOCIATED WITH AI BIASES 123
6.5 MLOPS TOOLS 124
6.5.1 REGULATORY COMPLIANCE AND ETHICAL CONCERNS AROUND AI GOVERNANCE TO PLAY CRITICAL ROLE IN GROWTH OF MLOPS TOOLS 124
6.5.1.1 Model development 125
6.5.1.2 Model deployment 126
6.5.1.3 Model monitoring 127
6.6 LLMOPS TOOLS 128
6.6.1 CONVERGENCE OF AI GOVERNANCE AND LLMOPS TO ENSURE BETTER MODEL PERFORMANCE TRACKING TO BOOST MARKET GROWTH 128
6.7 RESPONSIBLE AI TOOLKITS 129
6.7.1 NEED FOR ORGANIZATIONS TO BALANCE INNOVATION WITH GOVERNANCE TO DRIVE GROWTH OF RESPONSIBLE AI TOOLKITS 129
6.8 AI GOVERNANCE CONSULTING SERVICES 130
6.8.1 AI GOVERNANCE CONSULTING SERVICES TO OFFER CRITICAL EXPERTISE TO NAVIGATE COMPLEXITIES OF ETHICAL AI DEPLOYMENT 130
6.9 AI GOVERNANCE AS A SERVICE 132
6.9.1 AI GOVERNANCE AS A SERVICE PLATFORMS TO DETECT AND MITIGATE RISKS AND ENHANCE AI SYSTEM ACCOUNTABILITY 132
7 AI GOVERNANCE MARKET, BY FUNCTIONALITY 133
7.1 INTRODUCTION 134
7.1.1 FUNCTIONALITIES: AI GOVERNANCE MARKET DRIVERS 134
7.2 MODEL LIFECYCLE MANAGEMENT 136
7.2.1 MODEL LIFECYCLE MANAGEMENT TO MAINTAIN OPERATIONAL EFFICIENCY, ENSURE COMPLIANCE, AND ADDRESS ETHICAL CONCERNS SURROUNDING AI USAGE 136
7.2.2 AUTOMATED VERSIONING 137
7.2.3 MODEL-IN-PRODUCTION MANAGEMENT 138
7.2.4 AI INVENTORY MANAGEMENT 139
7.2.5 MODEL DIVERGENCE DETECTION 140
7.3 RISK MANAGEMENT & COMPLIANCE 141
7.3.1 EFFECTIVE COMPLIANCE FRAMEWORKS COMBINED WITH REGULAR AUDITS AND ETHICAL AI TRAINING TO MINIMIZE RISKS IN AI DEPLOYMENT 141
7.3.2 MODEL RISK MANAGEMENT 142
7.3.3 REGULATORY COMPLIANCE 143
7.3.4 RISK IDENTIFICATION & MITIGATION 144
7.3.5 THIRD-PARTY RISK EVALUATION 145
7.4 MONITORING & AUDITING 146
7.4.1 MONITORING AND AUDITING TO ENSURE TRANSPARENCY, ACCOUNTABILITY, AND COMPLIANCE IN DEPLOYMENT AND OPERATION OF AI SYSTEMS 146
7.4.2 AI MODEL MONITORING 147
7.4.3 DRIFT & BIAS MITIGATION 148
7.4.4 ANOMALY DETECTION 149
7.4.5 PERFORMANCE DEGRADATION ALERTS 150
7.5 TRANSPARENCY & EXPLAINABILITY 151
7.5.1 TRANSPARENCY & EXPLAINABILITY TO ENSURE ACCOUNTABILITY, ETHICAL INTEGRITY, AND USER TRUST 151
7.5.2 MODEL PREDICTION EXPLAINABILITY 152
7.5.3 MODEL TRANSPARENCY 153
7.5.4 MODEL DOCUMENTATION & REPORTING 154
7.6 DATA GOVERNANCE 155
7.6.1 DATA GOVERNANCE TO ENSURE AI TRAINING AND OPERATIONS DATA IS ACCURATE, COMPLETE, CONSISTENT, AND PROTECTED FROM BIASES OR MISUSE 155
7.6.2 DATA LINEAGE 156
7.6.3 DATA DISCOVERY & CLASSIFICATION 157
7.6.4 DATA PROVENANCE 158
7.7 ETHICS & RESPONSIBLE AI 159
7.7.1 ETHICAL AI TO EMPHASIZE FAIRNESS, TRANSPARENCY, AND ACCOUNTABILITY, AND MINIMIZE BIAS 159
7.7.2 AI POLICY CREATION 160
7.7.3 POLICY BREACH ALERTS 161
7.7.4 AI ETHICS MANAGEMENT 163
7.7.5 ADHERENCE VALIDATION 164
7.7.6 AI REGISTRY 165
7.8 OTHER FUNCTIONALITY TYPES 166
8 AI GOVERNANCE MARKET, BY END USER 167
8.1 INTRODUCTION 168
8.1.1 END USERS: AI GOVERNANCE MARKET DRIVERS 168
8.2 BFSI 170
8.2.1 FINANCIAL INSTITUTIONS TO LEVERAGE AI GOVERNANCE TOOLS TO ALIGN WITH NEW REGULATIONS, MITIGATE RISKS, AND ENHANCE TRANSPARENCY 170
8.2.2 BANKING 171
8.2.3 FINANCIAL SERVICES 172
8.2.4 INSURANCE 173
8.3 TELECOMMUNICATIONS 174
8.3.1 NEED TO ADDRESS GROWING USE OF AI IN MANAGING NETWORKS, CUSTOMER DATA, AND SERVICES TO DRIVE MARKET GROWTH 174
8.4 GOVERNMENT & DEFENSE 175
8.4.1 ADVANCEMENTS IN AI-DRIVEN CYBERSECURITY SYSTEMS TO HIGHLIGHT IMPORTANCE OF GOVERNANCE IN SAFEGUARDING NATIONAL SECURITY, ETHICS, AND COMPLIANCE 175
8.5 HEALTHCARE & LIFE SCIENCES 176
8.5.1 RISE OF AI-POWERED CLINICAL DECISION SUPPORT SYSTEMS AND RECOMMENDATIONS FOR DIAGNOSIS AND TREATMENT BASED ON VAST DATASETS TO PROPEL MARKET 176
8.6 MANUFACTURING 177
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 177
8.7 RETAIL & CONSUMER GOODS 179
8.7.1 NEED TO OPTIMIZE OPERATIONS, ENHANCE CUSTOMER EXPERIENCES, AND STREAMLINE SUPPLY CHAINS TO ACCELERATE MARKET GROWTH 179
8.8 SOFTWARE & TECHNOLOGY PROVIDERS 180
8.8.1 SOFTWARE & TECHNOLOGY PROVIDERS TO RELY ON AI GOVERNANCE TO ENSURE MODELS AND AI SYSTEMS STAY COMPLIANT, ETHICAL, AND TRANSPARENT 180
8.8.2 CLOUD HYPERSCALERS 182
8.8.3 FOUNDATION MODEL/LLM PROVIDERS 183
8.8.4 DATA ANNOTATORS 184
8.8.5 AI TRAINING DATASET PROVIDERS 185
8.8.6 IT & IT-ENABLED SERVICE PROVIDERS 186
8.9 AUTOMOTIVE 187
8.9.1 AI ALGORITHMS TO IMPROVE ELECTRONIC VEHICLE PERFORMANCE WHILE ADHERING TO ENVIRONMENTAL REGULATIONS 187

8.10 MEDIA & ENTERTAINMENT 188
8.10.1 EMPHASIS ON TRANSPARENCY, INTELLECTUAL PROPERTY PROTECTION, AND PRIVACY TO BOLSTER MARKET GROWTH 188
8.11 OTHER END USERS 189
9 AI GOVERNANCE MARKET, BY REGION 191
9.1 INTRODUCTION 192
9.2 NORTH AMERICA 194
9.2.1 NORTH AMERICA: AI GOVERNANCE MARKET DRIVERS 194
9.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK 194
9.2.3 US 199
9.2.3.1 Need to improve efficiency, decision-making, and robust governance frameworks to manage risks, ethical concerns, and compliance to drive market 199
9.2.4 CANADA 200
9.2.4.1 Increasing data security concerns, need for ethical AI practices, robust government support, and strategic investments to propel market 200
9.3 EUROPE 202
9.3.1 EUROPE: AI GOVERNANCE MARKET DRIVERS 202
9.3.2 EUROPE: MACROECONOMIC OUTLOOK 202
9.3.3 UK 206
9.3.3.1 Regulatory pressures, sector-specific needs, and advancements in AI transparency tools to fuel market growth 206
9.3.4 GERMANY 208
9.3.4.1 Advancements coupled with strong regulatory push and corporate accountability to boost demand for AI governance 208
9.3.5 FRANCE 209
9.3.5.1 Increasing demand for ethical AI solutions, regulatory compliance, and heightened awareness of risks to accelerate market growth 209
9.3.6 ITALY 211
9.3.6.1 Government investment in AI innovation and governance to prioritize responsible and transparent AI usage to boost market growth 211
9.3.7 SPAIN 212
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 212
9.3.8 NETHERLANDS 214
9.3.8.1 Government investment in AI infrastructure to strengthen local AI capabilities to boost demand for AI governance 214
9.3.9 REST OF EUROPE 215
9.4 ASIA PACIFIC 217
9.4.1 ASIA PACIFIC: AI GOVERNANCE MARKET DRIVERS 217
9.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK 217

9.4.3 CHINA 223
9.4.3.1 Advancements paired with China's strategic goals to mitigate AI risks to accelerate adoption of AI governance solutions 223
9.4.4 INDIA 224
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 224
9.4.5 JAPAN 226
9.4.5.1 Focus on technological innovation, government support, and increasing awareness of AI's ethical and legal implications to bolster market growth 226
9.4.6 SOUTH KOREA 227
9.4.6.1 Investment in AI governance models to balance performance with cost efficiency to accelerate adoption of AI governance solutions 227
9.4.7 SINGAPORE 229
9.4.7.1 Introduction of Model AI Governance Framework combined with substantial investments in training programs for local professionals to boost market growth 229
9.4.8 AUSTRALIA 230
9.4.8.1 Rising adoption of AI technologies and establishment of National Artificial Intelligence Centre (NAIC) to fuel market growth 230
9.4.9 REST OF ASIA PACIFIC 231
9.5 MIDDLE EAST & AFRICA 233
9.5.1 MIDDLE EAST & AFRICA: AI GOVERNANCE MARKET DRIVERS 233
9.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 233
9.5.3 SAUDI ARABIA 237
9.5.3.1 Focus on becoming global leader in AI through its Vision 2030 initiative to bolster market growth 237
9.5.4 UAE 239
9.5.4.1 Focus on digital transformation and implementation of UAE Artificial Intelligence Strategy 2031 to boost market growth 239
9.5.5 QATAR 240
9.5.5.1 Qatar’s commitment to leveraging AI for economic diversification aligning with its National Vision 2030 to enhance market growth 240
9.5.6 TURKEY 241
9.5.6.1 Implementation of National Artificial Intelligence Strategy to foster demand for AI governance 241
9.5.7 REST OF MIDDLE EAST 242
9.5.8 AFRICA 244
9.5.8.1 Need for ethical AI deployment, transparency, and regulatory oversight to foster adoption of AI governance 244
9.6 LATIN AMERICA 245
9.6.1 LATIN AMERICA: AI GOVERNANCE MARKET DRIVERS 245
9.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK 246

9.6.3 BRAZIL 250
9.6.3.1 Need for regulatory frameworks, ethical guidelines, governance mechanisms, and evolving data protection landscape to boost market growth 250
9.6.4 MEXICO 251
9.6.4.1 Regulatory initiatives, technological advancements, and increasing investment in AI technologies to augment market growth 251
9.6.5 ARGENTINA 252
9.6.5.1 Robust technological talent pool nurtured by universities and research institutions to accelerate market growth 252
9.6.6 REST OF LATIN AMERICA 253
10 COMPETITIVE LANDSCAPE 255
10.1 OVERVIEW 255
10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN 255
10.3 REVENUE ANALYSIS 257
10.4 MARKET SHARE ANALYSIS 258
10.4.1 MARKET RANKING ANALYSIS 259
10.5 PRODUCT/BRAND COMPARISON 261
10.5.1 AMAZON SAGEMAKER (AWS) 261
10.5.2 DOMINO AI GOVERNANCE (DOMINO DATA LABS) 261
10.5.3 EXPLAINABLE AI (GOOGLE) 262
10.5.4 WATSONX.GOVERNANCE (IBM) 262
10.5.5 TRUSTWORTHY AI (SAS INSTITUTE) 262
10.5.6 RESPONSIBLE AI (SAP) 263
10.5.7 AI IMPLEMENTATION BUNDLE (SALESFORCE) 263
10.5.8 FICO RESPONSIBLE AI (FICO) 263
10.5.9 RESPONSIBLE AI GOVERNANCE & CONSULTING (ACCENTURE) 264
10.6 COMPANY VALUATION AND FINANCIAL METRICS 264
10.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 265
10.7.1 STARS 265
10.7.2 EMERGING LEADERS 265
10.7.3 PERVASIVE PLAYERS 265
10.7.4 PARTICIPANTS 265
10.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 267
10.7.5.1 Company footprint 267
10.7.5.2 Product type footprint 268
10.7.5.3 Functionality footprint 269
10.7.5.4 End-user footprint 270
10.7.5.5 Regional footprint 271
10.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023 272
10.8.1 PROGRESSIVE COMPANIES 272
10.8.2 RESPONSIVE COMPANIES 272
10.8.3 DYNAMIC COMPANIES 272
10.8.4 STARTING BLOCKS 272
10.8.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023 274
10.8.5.1 Detailed list of key start-ups/SMEs 274
10.8.5.2 Competitive benchmarking of key start-ups/SMEs 277
10.9 COMPETITIVE SCENARIO AND TRENDS 278
10.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS 278
10.9.2 DEALS 280
11 COMPANY PROFILES 283
11.1 INTRODUCTION 283
11.2 KEY PLAYERS 283
11.2.1 IBM 283
11.2.1.1 Business overview 283
11.2.1.2 Products/Solutions/Services offered 285
11.2.1.3 Recent developments 285
11.2.1.3.1 Product launches 285
11.2.1.3.2 Deals 286
11.2.1.4 MnM view 287
11.2.1.4.1 Right to win 287
11.2.1.4.2 Strategic choices 287
11.2.1.4.3 Weaknesses and competitive threats 287
11.2.2 MICROSOFT 288
11.2.2.1 Business overview 288
11.2.2.2 Products/Solutions/Services offered 289
11.2.2.3 Recent developments 290
11.2.2.3.1 Product launches 290
11.2.2.3.2 Deals 290
11.2.2.4 MnM view 290
11.2.2.4.1 Right to win 290
11.2.2.4.2 Strategic choices 291
11.2.2.4.3 Weaknesses and competitive threats 291
11.2.3 GOOGLE 292
11.2.3.1 Business overview 292
11.2.3.2 Products/Solutions/Services offered 293
11.2.3.3 Recent developments 294
11.2.3.3.1 Deals 294
11.2.3.4 MnM view 294
11.2.3.4.1 Right to win 294
11.2.3.4.2 Strategic choices 294
11.2.3.4.3 Weaknesses and competitive threats 295

11.2.4 SALESFORCE 296
11.2.4.1 Business overview 296
11.2.4.2 Products/Solutions/Services offered 297
11.2.4.3 Recent developments 298
11.2.4.3.1 Product launches 298
11.2.4.3.2 Deals 298
11.2.4.4 MnM view 298
11.2.4.4.1 Right to win 298
11.2.4.4.2 Strategic choices 299
11.2.4.4.3 Weaknesses and competitive threats 299
11.2.5 SAP 300
11.2.5.1 Business overview 300
11.2.5.2 Products/Solutions/Services offered 301
11.2.5.3 Recent developments 302
11.2.5.3.1 Deals 302
11.2.5.4 MnM view 302
11.2.5.4.1 Right to win 302
11.2.5.4.2 Strategic choices 302
11.2.5.4.3 Weaknesses and competitive threats 302
11.2.6 AWS 303
11.2.6.1 Business overview 303
11.2.6.2 Products/Solutions/Services offered 304
11.2.6.3 Recent developments 305
11.2.6.3.1 Product launches 305
11.2.6.3.2 Deals 305
11.2.7 SAS INSTITUTE 307
11.2.7.1 Business overview 307
11.2.7.2 Products/Solutions/Services offered 308
11.2.7.3 Recent developments 308
11.2.7.3.1 Product launches 308
11.2.8 FICO 309
11.2.8.1 Business overview 309
11.2.8.2 Products/Solutions/Services offered 310
11.2.9 ACCENTURE 311
11.2.9.1 Business overview 311
11.2.9.2 Products/Solutions/Services offered 312
11.2.9.3 Recent developments 313
11.2.9.3.1 Deals 313
11.3 OTHER PLAYERS 314
11.3.1 ONETRUST 314
11.3.2 QLIK 315
11.3.3 H20.AI 316
11.3.4 ALTERYX 316
11.3.5 DATAROBOT 317
11.3.6 DATAIKU 318
11.3.7 DOMINO DATA LABS 319
11.3.8 SPARKCOGNITION 319
11.3.9 COLLIBRA 320
11.3.10 QUEST SOFTWARE 320
11.3.11 SECURITI 321
11.4 START-UPS/SMES 322
11.4.1 MONITAUR 322
11.4.1.1 Business overview 322
11.4.1.2 Products/Solutions/Services offered 323
11.4.1.3 Recent developments 323
11.4.1.3.1 Deals 323
11.4.2 FIDDLER AI 324
11.4.3 UNTANGLE AI 324
11.4.4 2021.AI 325
11.4.5 HOWSO 325
11.4.6 MIND FOUNDRY 326
11.4.7 CREDO AI 327
11.4.8 HOLISTIC AI 328
11.4.9 FAIRLY AI 328
11.4.10 ENZAI 329
11.4.11 VALIDMIND 330
11.4.12 FAIRNOW 331
11.4.13 MONA LABS 331
11.4.14 ARTHUR AI 332
11.4.15 TRUSTIBLE 333
11.4.16 ATLAN 334
11.4.17 MODELOP 335
11.4.18 NEPTUNE.AI 335
11.4.19 PATRONUS AI 336
11.4.20 DATATRON 336
11.4.21 MODOLUS 337
11.4.22 CALVIN RISK 338
11.4.23 SAIDOT 339
11.4.24 CENSIUS 340
11.4.25 BREEZEML 341
11.4.26 ANCH.AI 342
11.4.27 PRODAGO 343
11.4.28 QUANTPI 344
11.4.29 YOOI 345
12 ADJACENT AND RELATED MARKETS 346
12.1 INTRODUCTION 346
12.2 AI MODEL RISK MANAGEMENT MARKET – GLOBAL FORECAST TO 2029 346
12.2.1 MARKET DEFINITION 346
12.2.2 MARKET OVERVIEW 347
12.2.2.1 AI model risk management market, by offering 348
12.2.2.2 AI model risk management market, by risk type 348
12.2.2.3 AI model risk management market, by application 349
12.2.2.4 AI model risk management market, by vertical 350
12.2.2.5 AI model risk management market, by region 351
12.3 ARTIFICIAL INTELLIGENCE (AI) MARKET – GLOBAL FORECAST TO 2030 352
12.3.1 MARKET DEFINITION 352
12.3.2 MARKET OVERVIEW 352
12.3.2.1 Artificial intelligence market, by offering 353
12.3.2.2 Artificial intelligence market, by business function 354
12.3.2.3 Artificial intelligence market, by technology 355
12.3.2.4 Artificial intelligence market, by vertical 356
12.3.2.5 Artificial intelligence market, by region 358
13 APPENDIX 360
13.1 DISCUSSION GUIDE 360
13.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 365
13.3 CUSTOMIZATION OPTIONS 367
13.4 RELATED REPORTS 367
13.5 AUTHOR DETAILS 368