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 PROVIDERS 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
5.8.3.1 Top 10 applicants in AI governance market 86
5.9 KEY CONFERENCES AND EVENTS (2024–2025) 92
5.10 REGULATORY LANDSCAPE 92
5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES,
AND OTHER ORGANIZATIONS 93
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) 97
5.10.2.2 Europe 97
5.10.2.2.1 UK AI Regulation White Paper 97
5.10.2.2.2 European Union (EU) - AI Act 97
5.10.2.2.3 Gesetz zur Regulierung Künstlicher Intelligenz
(AI Regulation Law) 97
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 98
 
5.10.2.3 Asia Pacific 98
5.10.2.3.1 Personal Data Protection Bill (PDPB) & National Strategy on AI (NSAI) 98
5.10.2.3.2 New Generation Artificial Intelligence Development Plan & AI Ethics Guidelines 98
5.10.2.3.3 Framework Act on Intelligent Informatization 98
5.10.2.3.4 AI Ethics Framework (Australia) & AI Strategy (New Zealand) 98
5.10.2.3.5 Model AI Governance Framework 98
5.10.2.3.6 Data Security Law (2021), AI Guidelines (China) 99
5.10.2.4 Middle East & Africa 99
5.10.2.4.1 Saudi Data & Artificial Intelligence Authority (SDAIA) Regulations 99
5.10.2.4.2 UAE National AI Strategy 2031 99
5.10.2.4.3 Qatar National AI Strategy 99
5.10.2.4.4 National Artificial Intelligence Strategy (2021–2025) 99
5.10.2.4.5 Egyptian Artificial Intelligence Strategy 99
5.10.2.4.6 Kuwait National Development Plan
(New Kuwait Vision 2035) 99
5.10.3 LATIN AMERICA 100
5.10.3.1.1 Brazilian General Data Protection Law (LGPD) 100
5.10.3.1.2 Federal Law on the Protection of Personal Data Held
by Private Parties 100
5.10.3.1.3 Argentina Personal Data Protection Law (PDPL) &
AI Ethics Framework 100
5.10.3.1.4 Chilean Data Protection Law & National AI Policy 100
5.10.3.1.5 Colombian Data Protection Law (Law 1581) &
AI Ethics Guidelines 101
5.10.3.1.6 Peruvian Personal Data Protection
Law & National AI Strategy 101
5.11 PORTER’S FIVE FORCES ANALYSIS 101
5.11.1 THREAT OF NEW ENTRANTS 102
5.11.2 THREAT OF SUBSTITUTES 102
5.11.3 BARGAINING POWER OF SUPPLIERS 102
5.11.4 BARGAINING POWER OF BUYERS 103
5.11.5 INTENSITY OF COMPETITIVE RIVALRY 103
5.12 KEY STAKEHOLDERS & BUYING CRITERIA 103
5.12.1 KEY STAKEHOLDERS IN BUYING PROCESS 103
5.12.2 BUYING CRITERIA 104
5.13 INVESTMENT LANDSCAPE AND FUNDING SCENARIO 105
5.14 IMPACT OF GENERATIVE AI ON AI GOVERNANCE MARKET 109
5.14.1 TOP USE CASES & MARKET POTENTIAL 109
5.14.1.1 Bias detection and mitigation 110
5.14.1.2 Automated compliance reporting 110
5.14.1.3 Policy generation and documentation 110
5.14.1.4 Dynamic risk assessment 110
5.14.1.5 Auditing model transparency 110
5.15 AI GOVERNANCE LIFECYCLE FRAMEWORK 111
5.15.1 ENVIRONMENTAL LAYER 111
5.15.2 ORGANIZATIONAL LAYER 112
5.15.3 AI SYSTEM LAYER 112
5.16 EVOLUTION OF AI GOVERNANCE 113
5.17 CASE STUDY ANALYSIS 114
5.17.1 BFSI 115
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 115
5.17.1.2 2021.AI collaborated with GF to create AI-derived model that could simulate fraud patterns among household insurance claims 115
5.17.2 SOFTWARE & TECHNOLOGY PROVIDERS 116
5.17.2.1 LinkGRC enhanced its GRC service offerings with 2021.AI’s AI-based solutions 116
5.17.2.2 Prometric championed Responsible AI in assessments with long-term partner 2021.AI 117
5.17.3 RETAIL & CONSUMER GOODS 117
5.17.3.1 Conjura reduced time to detect and resolve model drift from days to hours with Fiddler 117
6 AI GOVERNANCE MARKET, BY PRODUCT TYPE 118
6.1 INTRODUCTION 119
6.1.1 PRODUCT TYPES: AI GOVERNANCE MARKET DRIVERS 119
6.2 DATA PRIVACY TOOLS 121
6.2.1 NEED FOR DATA PRIVACY TOOLS TO GROW DUE TO INCREASED REGULATORY SCRUTINY AND RISING THREAT OF DATA BREACHES 121
6.3 END-TO-END AI GOVERNANCE PLATFORMS 122
6.3.1 DEMAND FOR END-TO-END AI GOVERNANCE PLATFORMS TO GROW TO
ALIGN AI WITH REGULATORY AND ETHICAL STANDARDS 122
6.4 DATA GOVERNANCE PLATFORMS 124
6.4.1 DATA GOVERNANCE PLATFORMS TO TRACK DATA QUALITY AND MITIGATE RISKS ASSOCIATED WITH AI BIASES 124
6.5 MLOPS TOOLS 125
6.5.1 REGULATORY COMPLIANCE AND ETHICAL CONCERNS AROUND AI GOVERNANCE TO PLAY CRITICAL ROLE IN GROWTH OF MLOPS TOOLS 125
6.5.1.1 Model development 126
6.5.1.2 Model deployment 127
6.5.1.3 Model monitoring 128
6.6 LLMOPS TOOLS 129
6.6.1 CONVERGENCE OF AI GOVERNANCE AND LLMOPS TO ENSURE BETTER MODEL PERFORMANCE TRACKING TO BOOST MARKET GROWTH 129
 
6.7 RESPONSIBLE AI TOOLKITS 130
6.7.1 NEED FOR ORGANIZATIONS TO BALANCE INNOVATION WITH GOVERNANCE TO DRIVE GROWTH OF RESPONSIBLE AI TOOLKITS 130
6.8 AI GOVERNANCE CONSULTING SERVICES 131
6.8.1 AI GOVERNANCE CONSULTING SERVICES TO OFFER CRITICAL EXPERTISE TO NAVIGATE COMPLEXITIES OF ETHICAL AI DEPLOYMENT 131
6.9 AI GOVERNANCE AS A SERVICE 133
6.9.1 AI GOVERNANCE AS A SERVICE PLATFORMS TO DETECT AND MITIGATE RISKS AND ENHANCE AI SYSTEM ACCOUNTABILITY 133
7 AI GOVERNANCE MARKET, BY FUNCTIONALITY 134
7.1 INTRODUCTION 135
7.1.1 FUNCTIONALITIES: AI GOVERNANCE MARKET DRIVERS 135
7.2 MODEL LIFECYCLE MANAGEMENT 137
7.2.1 MODEL LIFECYCLE MANAGEMENT TO MAINTAIN OPERATIONAL EFFICIENCY, ENSURE COMPLIANCE, AND ADDRESS ETHICAL CONCERNS SURROUNDING AI USAGE 137
7.2.2 AUTOMATED VERSIONING 138
7.2.3 MODEL-IN-PRODUCTION MANAGEMENT 139
7.2.4 AI INVENTORY MANAGEMENT 140
7.2.5 MODEL DIVERGENCE DETECTION 141
7.3 RISK MANAGEMENT & COMPLIANCE 142
7.3.1 EFFECTIVE COMPLIANCE FRAMEWORKS COMBINED WITH REGULAR AUDITS AND ETHICAL AI TRAINING TO MINIMIZE RISKS IN AI DEPLOYMENT 142
7.3.2 MODEL RISK MANAGEMENT 143
7.3.3 REGULATORY COMPLIANCE 144
7.3.4 RISK IDENTIFICATION & MITIGATION 145
7.3.5 THIRD-PARTY RISK EVALUATION 146
7.4 MONITORING & AUDITING 147
7.4.1 MONITORING AND AUDITING TO ENSURE TRANSPARENCY, ACCOUNTABILITY, AND COMPLIANCE IN DEPLOYMENT AND OPERATION OF AI SYSTEMS 147
7.4.2 AI MODEL MONITORING 148
7.4.3 DRIFT & BIAS MITIGATION 149
7.4.4 ANOMALY DETECTION 150
7.4.5 PERFORMANCE DEGRADATION ALERTS 151
7.5 TRANSPARENCY & EXPLAINABILITY 152
7.5.1 TRANSPARENCY & EXPLAINABILITY TO ENSURE ACCOUNTABILITY, ETHICAL INTEGRITY, AND USER TRUST 152
7.5.2 MODEL PREDICTION EXPLAINABILITY 153
7.5.3 MODEL TRANSPARENCY 154
7.5.4 MODEL DOCUMENTATION & REPORTING 155
 
7.6 DATA GOVERNANCE 156
7.6.1 DATA GOVERNANCE TO ENSURE AI TRAINING AND OPERATIONS DATA IS ACCURATE, COMPLETE, CONSISTENT, AND PROTECTED FROM BIASES OR MISUSE 156
7.6.2 DATA LINEAGE 157
7.6.3 DATA DISCOVERY & CLASSIFICATION 158
7.6.4 DATA PROVENANCE 159
7.7 ETHICS & RESPONSIBLE AI 160
7.7.1 ETHICAL AI TO EMPHASIZE FAIRNESS, TRANSPARENCY, AND ACCOUNTABILITY, AND MINIMIZE BIAS 160
7.7.2 AI POLICY CREATION 161
7.7.3 POLICY BREACH ALERTS 162
7.7.4 AI ETHICS MANAGEMENT 164
7.7.5 ADHERENCE VALIDATION 165
7.7.6 AI REGISTRY 166
7.8 OTHER FUNCTIONALITY TYPES 167
8 AI GOVERNANCE MARKET, BY END USER 168
8.1 INTRODUCTION 169
8.1.1 END USERS: AI GOVERNANCE MARKET DRIVERS 169
8.2 BFSI 171
8.2.1 FINANCIAL INSTITUTIONS TO LEVERAGE AI GOVERNANCE TOOLS TO ALIGN WITH NEW REGULATIONS, MITIGATE RISKS, AND ENHANCE TRANSPARENCY 171
8.2.2 BANKING 172
8.2.3 FINANCIAL SERVICES 173
8.2.4 INSURANCE 174
8.3 TELECOMMUNICATIONS 175
8.3.1 NEED TO ADDRESS GROWING USE OF AI IN MANAGING NETWORKS, CUSTOMER DATA, AND SERVICES TO DRIVE MARKET GROWTH 175
8.4 GOVERNMENT & DEFENSE 176
8.4.1 ADVANCEMENTS IN AI-DRIVEN CYBERSECURITY SYSTEMS TO HIGHLIGHT IMPORTANCE OF GOVERNANCE IN SAFEGUARDING NATIONAL SECURITY, ETHICS, AND COMPLIANCE 176
8.5 HEALTHCARE & LIFE SCIENCES 177
8.5.1 RISE OF AI-POWERED CLINICAL DECISION SUPPORT SYSTEMS AND RECOMMENDATIONS FOR DIAGNOSIS AND TREATMENT BASED ON VAST DATASETS TO PROPEL MARKET 177
8.6 MANUFACTURING 178
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 178
8.7 RETAIL & CONSUMER GOODS 180
8.7.1 NEED TO OPTIMIZE OPERATIONS, ENHANCE CUSTOMER EXPERIENCES,
AND STREAMLINE SUPPLY CHAINS TO ACCELERATE MARKET GROWTH 180
 
8.8 SOFTWARE & TECHNOLOGY PROVIDERS 181
8.8.1 SOFTWARE & TECHNOLOGY PROVIDERS TO RELY ON AI GOVERNANCE TO ENSURE MODELS AND AI SYSTEMS STAY COMPLIANT, ETHICAL, AND TRANSPARENT 181
8.8.2 CLOUD HYPERSCALERS 183
8.8.3 FOUNDATION MODEL/LLM PROVIDERS 184
8.8.4 DATA ANNOTATORS 185
8.8.5 AI TRAINING DATASET PROVIDERS 186
8.8.6 IT & IT-ENABLED SERVICE PROVIDERS 187
8.9 AUTOMOTIVE 188
8.9.1 AI ALGORITHMS TO IMPROVE ELECTRONIC VEHICLE PERFORMANCE WHILE ADHERING TO ENVIRONMENTAL REGULATIONS 188
8.10 MEDIA & ENTERTAINMENT 189
8.10.1 EMPHASIS ON TRANSPARENCY, INTELLECTUAL PROPERTY PROTECTION,
AND PRIVACY TO BOLSTER MARKET GROWTH 189
8.11 OTHER END USERS 190
9 AI GOVERNANCE MARKET, BY REGION 192
9.1 INTRODUCTION 193
9.2 NORTH AMERICA 195
9.2.1 NORTH AMERICA: AI GOVERNANCE MARKET DRIVERS 195
9.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK 195
9.2.3 US 200
9.2.3.1 Need to improve efficiency, decision-making, and robust governance frameworks to manage risks, ethical concerns, and compliance to drive market 200
9.2.4 CANADA 201
9.2.4.1 Increasing data security concerns, need for ethical AI practices, robust government support, and strategic investments to propel market 201
9.3 EUROPE 203
9.3.1 EUROPE: AI GOVERNANCE MARKET DRIVERS 203
9.3.2 EUROPE: MACROECONOMIC OUTLOOK 203
9.3.3 UK 207
9.3.3.1 Regulatory pressures, sector-specific needs, and advancements in
AI transparency tools to fuel market growth 207
9.3.4 GERMANY 209
9.3.4.1 Advancements coupled with strong regulatory push and
corporate accountability to boost demand for AI governance 209
9.3.5 FRANCE 210
9.3.5.1 Increasing demand for ethical AI solutions, regulatory compliance, and heightened awareness of risks to accelerate market growth 210
9.3.6 ITALY 212
9.3.6.1 Government investment in AI innovation and governance to prioritize responsible and transparent AI usage to boost market growth 212
 
9.3.7 SPAIN 213
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 213
9.3.8 NETHERLANDS 215
9.3.8.1 Government investment in AI infrastructure to strengthen local AI capabilities to boost demand for AI governance 215
9.3.9 REST OF EUROPE 216
9.4 ASIA PACIFIC 218
9.4.1 ASIA PACIFIC: AI GOVERNANCE MARKET DRIVERS 218
9.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK 218
9.4.3 CHINA 224
9.4.3.1 Advancements paired with China's strategic goals to mitigate
AI risks to accelerate adoption of AI governance solutions 224
9.4.4 INDIA 225
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 225
9.4.5 JAPAN 227
9.4.5.1 Focus on technological innovation, government support, and increasing awareness of AI's ethical and legal implications to bolster market growth 227
9.4.6 SOUTH KOREA 228
9.4.6.1 Investment in AI governance models to balance performance with cost efficiency to accelerate adoption of AI governance solutions 228
9.4.7 SINGAPORE 230
9.4.7.1 Introduction of Model AI Governance Framework combined with substantial investments in training programs for local professionals to boost market growth 230
9.4.8 AUSTRALIA 231
9.4.8.1 Rising adoption of AI technologies and establishment of
National Artificial Intelligence Centre (NAIC) to fuel market growth 231
9.4.9 REST OF ASIA PACIFIC 232
9.5 MIDDLE EAST & AFRICA 234
9.5.1 MIDDLE EAST & AFRICA: AI GOVERNANCE MARKET DRIVERS 234
9.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 234
9.5.3 SAUDI ARABIA 238
9.5.3.1 Focus on becoming global leader in AI through its Vision 2030 initiative to bolster market growth 238
9.5.4 UAE 240
9.5.4.1 Focus on digital transformation and implementation of UAE
Artificial Intelligence Strategy 2031 to boost market growth 240
9.5.5 QATAR 241
9.5.5.1 Qatar’s commitment to leveraging AI for economic diversification aligning with its National Vision 2030 to enhance market growth 241
 
9.5.6 TURKEY 242
9.5.6.1 Implementation of National Artificial Intelligence Strategy to
foster demand for AI governance 242
9.5.7 REST OF MIDDLE EAST 243
9.5.8 AFRICA 245
9.5.8.1 Need for ethical AI deployment, transparency,
and regulatory oversight to foster adoption of AI governance 245
9.6 LATIN AMERICA 246
9.6.1 LATIN AMERICA: AI GOVERNANCE MARKET DRIVERS 246
9.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK 247
9.6.3 BRAZIL 251
9.6.3.1 Need for regulatory frameworks, ethical guidelines, governance mechanisms, and evolving data protection landscape to
boost market growth 251
9.6.4 MEXICO 252
9.6.4.1 Regulatory initiatives, technological advancements, and
increasing investment in AI technologies to augment market growth 252
9.6.5 ARGENTINA 253
9.6.5.1 Robust technological talent pool nurtured by universities
and research institutions to accelerate market growth 253
9.6.6 REST OF LATIN AMERICA 254
10 COMPETITIVE LANDSCAPE 256
10.1 OVERVIEW 256
10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN 256
10.3 REVENUE ANALYSIS 258
10.4 MARKET SHARE ANALYSIS 259
10.4.1 MARKET RANKING ANALYSIS 260
10.5 PRODUCT/BRAND COMPARISON 262
10.5.1 AMAZON SAGEMAKER (AWS) 262
10.5.2 DOMINO AI GOVERNANCE (DOMINO DATA LABS) 262
10.5.3 EXPLAINABLE AI (GOOGLE) 263
10.5.4 WATSONX.GOVERNANCE (IBM) 263
10.5.5 CREDO AI GOVERNANCE PLATFORM (CREDO AI) 263
10.5.6 GRACE LLM GOVERNANCE (2021.AI) 264
10.5.7 ARTHUR BENCH (ARTHUR AI) 264
10.5.8 PATRONUS AI SUITE (PATRONUS AI) 264
10.5.9 LLM MESH (DATAIKU) 265
10.5.10 GEN AI GOVERNANCE PLATFORM (PORTAL 26) 265
10.6 COMPANY VALUATION AND FINANCIAL METRICS 265
10.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 266
10.7.1 STARS 266
10.7.2 EMERGING LEADERS 266
10.7.3 PERVASIVE PLAYERS 267
10.7.4 PARTICIPANTS 267
10.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 268
10.7.5.1 Company footprint 268
10.7.5.2 Product type footprint 269
10.7.5.3 Functionality footprint 270
10.7.5.4 End-user footprint 271
10.7.5.5 Regional footprint 272
10.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023 273
10.8.1 PROGRESSIVE COMPANIES 273
10.8.2 RESPONSIVE COMPANIES 273
10.8.3 DYNAMIC COMPANIES 273
10.8.4 STARTING BLOCKS 273
10.8.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023 275
10.8.5.1 Detailed list of key start-ups/SMEs 275
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 279
11 COMPANY PROFILES 281
11.1 INTRODUCTION 281
11.2 KEY PLAYERS 281
11.2.1 IBM 281
11.2.1.1 Business overview 281
11.2.1.2 Products/Solutions/Services offered 283
11.2.1.3 Recent developments 283
11.2.1.3.1 Product launches 283
11.2.1.3.2 Deals 284
11.2.1.4 MnM view 284
11.2.1.4.1 Right to win 284
11.2.1.4.2 Strategic choices 285
11.2.1.4.3 Weaknesses and competitive threats 285
11.2.2 MICROSOFT 286
11.2.2.1 Business overview 286
11.2.2.2 Products/Solutions/Services offered 287
11.2.2.3 Recent developments 288
11.2.2.3.1 Product launches 288
11.2.2.4 MnM view 288
11.2.2.4.1 Right to win 288
11.2.2.4.2 Strategic choices 288
11.2.2.4.3 Weaknesses and competitive threats 288
 
11.2.3 GOOGLE 289
11.2.3.1 Business overview 289
11.2.3.2 Products/Solutions/Services offered 290
11.2.3.3 MnM view 291
11.2.3.3.1 Right to win 291
11.2.3.3.2 Strategic choices 291
11.2.3.3.3 Weaknesses and competitive threats 291
11.2.4 SALESFORCE 292
11.2.4.1 Business overview 292
11.2.4.2 Products/Solutions/Services offered 293
11.2.4.3 Recent developments 294
11.2.4.3.1 Product launches 294
11.2.4.4 MnM view 294
11.2.4.4.1 Right to win 294
11.2.4.4.2 Strategic choices 294
11.2.4.4.3 Weaknesses and competitive threats 294
11.2.5 SAP 295
11.2.5.1 Business overview 295
11.2.5.2 Products/Solutions/Services offered 296
11.2.5.3 Recent developments 297
11.2.5.3.1 Deals 297
11.2.5.4 MnM view 297
11.2.5.4.1 Right to win 297
11.2.5.4.2 Strategic choices 297
11.2.5.4.3 Weaknesses and competitive threats 297
11.2.6 AWS 298
11.2.6.1 Business overview 298
11.2.6.2 Products/Solutions/Services offered 299
11.2.6.3 Recent developments 300
11.2.6.3.1 Product launches 300
11.2.6.3.2 Deals 300
11.2.7 SAS INSTITUTE 301
11.2.7.1 Business overview 301
11.2.7.2 Products/Solutions/Services offered 302
11.2.7.3 Recent developments 302
11.2.7.3.1 Product launches 302
11.2.8 FICO 303
11.2.8.1 Business overview 303
11.2.8.2 Products/Solutions/Services offered 304
 
11.2.9 META 305
11.2.9.1 Business overview 305
11.2.9.2 Products/Solutions/Services offered 306
11.2.9.3 Recent developments 307
11.2.9.3.1 Deals 307
11.2.10 ACCENTURE 308
11.2.10.1 Business overview 308
11.2.10.2 Products/Solutions/Services offered 309
11.2.10.3 Recent developments 310
11.2.10.3.1 Deals 310
11.3 OTHER PLAYERS 311
11.3.1 ONETRUST 311
11.3.2 QLIK 312
11.3.3 H20.AI 313
11.3.4 ALTERYX 313
11.3.5 DATAROBOT 314
11.3.6 DATAIKU 315
11.3.7 DOMINO DATA LABS 316
11.3.8 SPARKCOGNITION 316
11.3.9 COLLIBRA 317
11.3.10 QUEST SOFTWARE 317
11.4 START-UPS/SMES 318
11.4.1 MONITAUR 318
11.4.1.1 Business overview 318
11.4.1.2 Products/Solutions/Services offered 319
11.4.1.3 Recent developments 319
11.4.1.3.1 Deals 319
11.4.2 FIDDLER AI 320
11.4.3 UNTANGLE AI 320
11.4.4 2021.AI 321
11.4.5 HOWSO 321
11.4.6 MIND FOUNDRY 322
11.4.7 CREDO AI 323
11.4.8 HOLISTIC AI 324
11.4.9 FAIRLY AI 324
11.4.10 ENZAI 325
11.4.11 VALIDMIND 326
11.4.12 FAIRNOW 327
11.4.13 MONA LABS 327
11.4.14 ARTHUR AI 328
11.4.15 TRUSTIBLE 329
11.4.16 ATLAN 330
11.4.17 MODELOP 331
11.4.18 NEPTUNE.AI 331
11.4.19 PATRONUS AI 332
11.4.20 DATATRON 332
12 ADJACENT AND RELATED MARKETS 333
12.1 INTRODUCTION 333
12.2 AI MODEL RISK MANAGEMENT MARKET – GLOBAL FORECAST TO 2029 333
12.2.1 MARKET DEFINITION 333
12.2.2 MARKET OVERVIEW 334
12.2.2.1 AI model risk management market, by offering 335
12.2.2.2 AI model risk management market, by risk type 335
12.2.2.3 AI model risk management market, by application 336
12.2.2.4 AI model risk management market, by vertical 337
12.2.2.5 AI model risk management market, by region 338
12.3 ARTIFICIAL INTELLIGENCE (AI) MARKET – GLOBAL FORECAST TO 2030 339
12.3.1 MARKET DEFINITION 339
12.3.2 MARKET OVERVIEW 339
12.3.2.1 Artificial intelligence market, by offering 340
12.3.2.2 Artificial intelligence market, by business function 341
12.3.2.3 Artificial intelligence market, by technology 342
12.3.2.4 Artificial intelligence market, by vertical 343
12.3.2.5 Artificial intelligence market, by region 345
13 APPENDIX 347
13.1 DISCUSSION GUIDE 347
13.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 353
13.3 CUSTOMIZATION OPTIONS 355
13.4 RELATED REPORTS 355
13.5 AUTHOR DETAILS 356