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

AI Governance Market by Functionality (Model Lifecycle Management, Risk & Compliance, Monitoring & Auditing, Ethics & Responsible AI), Product Type (End-to-end AI Governance Platforms, MLOps & LLMOps Tools, Data Privacy Tools) - Global Forecast to 2029

US $ 4,950 ￦ 7,194,000

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US $ 6,650 ￦ 9,665,000

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US $ 8,150 ￦ 11,845,000

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US $ 10,000 ￦ 14,534,000

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한글목차

AI 거버넌스 시장 규모는 2024년 8억 9,060만 달러에서 2029년 57억 7,600만 달러로 성장할 것으로 예상되며, 2024-2029년 연평균 45.3%의 CAGR을 기록할 것으로 예측됩니다.

AI 거버넌스 시장은 AI 도입에 있어 리스크 관리의 중요성에 대한 인식이 높아짐에 따라 향후 몇 년 동안 크게 성장할 것으로 예상됩니다. 조직들은 AI 리스크 관리의 중요성을 인식하고 AI 거버넌스 툴에 대한 투자를 늘리고 있습니다. 금융 및 헬스케어와 같은 규제 산업은 엄격한 규제를 준수하기 위한 거버넌스 솔루션을 구축하는 데 있어 업계를 선도하고 있으며, AI 시스템 사용에 대한 신뢰성, 투명성 및 책임에 대한 요구가 높아지면서 조직이 다양한 분야에서 AI의 책임감 있고 윤리적인 사용을 강조함에 따라 시장을 더욱 견인하고 있습니다.

조사 범위
조사 대상 연도	2019-2029년
기준 연도	2023년
예측 기간	2024-2030년
검토 단위	달러(100만 달러)
부문	제품 유형별, 기능성별, 최종사용자별, 지역별
대상 지역	북미, 유럽, 아시아태평양, 중동 및 아프리카, 라틴아메리카

MLOps 툴은 머신러닝 모델의 개발, 배포, 모니터링 전반을 효율화하기 때문에 예측 기간 동안 가장 높은 성장률을 기록할 것으로 예상됩니다. AI 모델과 그 요구사항이 매우 복잡하다는 점이 조직이 MLOps 툴을 채택하게 만드는 주요 요인으로 작용하고 있으며, 이는 규제 표준을 준수하는 모델의 버전 관리와 지속적인 통합을 가능하게 하고, 프로세스의 투명성을 높입니다. 이러한 도구는 데이터 처리에서 실시간 모니터링에 이르기까지 AI의 전체 라이프사이클을 관리하기 때문입니다. 또한, 규제 산업에서 거버넌스 및 리스크 관리 모델에 대한 책임에 대한 요구가 높아지면서 MLOps 툴의 성장에 힘을 실어주고 있습니다.

리스크 관리와 컴플라이언스는 AI 시스템의 복잡성이 증가하는 반면 규제가 계속 쌓여감에 따라 AI 거버넌스 시장에서 가장 빠른 시장 성장률을 기록할 것으로 예상됩니다. 특히 금융, 헬스케어, 보험 등 규제가 엄격한 분야에서는 AI 모델의 편향성, 공정성, 투명성 관련 리스크를 고려해야 한다는 것을 모든 산업 분야의 기업들이 인식하고 있습니다. 예를 들어, AI 기반 거버넌스 솔루션은 유럽연합의 GDPR 규제와 다양한 의사결정 과정에서 사용되는 데이터와 알고리즘의 사용을 엄격하게 감시하는 미국의 공정대출법(Fair Lending Act)을 준수하기 위해 금융회사에 의해 적용되고 있습니다. 헬스케어 조직은 HIPAA를 준수하면서 AI 기반 진단 도구를 통해 위험을 최소화하고 환자 안전을 향상시킬 목적으로 AI 거버넌스 프레임워크를 적용하고 있습니다.

북미는 상당한 수의 AI 관련 규제와 함께 견고하게 구축된 AI 생태계로 인해 2024년에도 시장을 선도할 것으로 예상됩니다. IBM, Microsoft, Google 등 미국을 기반으로 하는 주요 기업들이 AI 기술을 조기에 도입하여 컴플라이언스 및 리스크 관리를 위한 강력한 툴을 자사 제품에 통합함으로써 이 지역의 AI 거버넌스를 주도하고 있습니다. 또한, 미국 정부는 AI와 관련된 새로운 규제를 적극적으로 마련하고 있습니다. 예를 들어, 국가 AI 이니셔티브 법에 힘입어 기업들을 위한 거버넌스 프레임워크가 개발되고 있습니다.

세계의 AI 거버넌스 시장에 대해 조사했으며, 제품 유형별, 기능성별, 최종사용자별, 지역별 동향, 시장 진입 기업 프로파일 등의 정보를 정리하여 전해드립니다.

목차

제1장 소개

제2장 조사 방법

제3장 주요 요약

제4장 주요 인사이트

제5장 시장 개요와 업계 동향

• 소개
• 시장 역학
• 고객 비즈니스에 영향을 미치는 동향/혼란
• 가격 분석
• 공급망 분석
• 생태계
• 기술 분석
• 특허 분석
• 주요 회의와 이벤트(2025-2026년)
• 규제 상황
• Porter's Five Forces 분석
• 주요 이해관계자와 구입 기준
• 투자 상황과 자금 조달 시나리오
• 생성형 AI가 AI 거버넌스 시장에 미치는 영향
• AI 거버넌스 수명주기 프레임워크
• AI 거버넌스의 진화
• 사례 연구 분석

제6장 AI 거버넌스 시장, 제품 유형별

• 소개
• 데이터 프라이버시 툴
• 엔드 투 엔드 AI 거버넌스 플랫폼
• 데이터 거버넌스 플랫폼
• MLOPS 툴
• LLMOPS 툴
• 책임감 있는 AI 툴킷
• AI 거버넌스 컨설팅 서비스
• AI Governance as a Service

제7장 AI 거버넌스 시장, 기능성별

• 소개
• 모델 수명주기 관리
• 리스크 관리와 컴플라이언스
• 감시와 감사
• 투명성과 설명 가능성
• 데이터 거버넌스
• 윤리 및 책임감 있는 AI
• 기타

제8장 AI 거버넌스 시장, 최종사용자별

• 소개
• BFSI
• 통신
• 정부·방위
• 헬스케어·생명과학
• 제조
• 소매·소비재
• 소프트웨어·테크놀러지 프로바이더
• 자동차
• 미디어·엔터테인먼트
• 기타

제9장 AI 거버넌스 시장, 지역별

• 소개
• 북미
  • 북미 : AI 거버넌스 시장 성장 촉진요인
  • 북미 : 거시경제 전망
  • 미국
  • 캐나다
• 유럽
  • 유럽 : AI 거버넌스 시장 성장 촉진요인
  • 유럽 : 거시경제 전망
  • 영국
  • 독일
  • 프랑스
  • 이탈리아
  • 스페인
  • 네덜란드
  • 기타
• 아시아태평양
  • 아시아태평양 : AI 거버넌스 시장 성장 촉진요인
  • 아시아태평양 : 거시경제 전망
  • 중국
  • 인도
  • 일본
  • 한국
  • 싱가포르
  • 호주
  • 기타
• 중동 및 아프리카
  • 중동 및 아프리카 : AI 거버넌스 시장 성장 촉진요인
  • 중동 및 아프리카 : 거시경제 전망
  • 사우디아라비아
  • 아랍에미리트
  • 카타르
  • 터키
  • 기타
  • 아프리카
• 라틴아메리카
  • 라틴아메리카 : AI 거버넌스 시장 성장 촉진요인
  • 라틴아메리카 : 거시경제 전망
  • 브라질
  • 멕시코
  • 아르헨티나
  • 기타

제10장 경쟁 구도

• 개요
• 주요 진출 기업 전략/강점
• 매출 분석
• 시장 점유율 분석
• 제품/브랜드 비교
• 기업 가치 평가와 재무 지표
• 기업 평가 매트릭스 : 주요 진출 기업, 2023년
• 기업 평가 매트릭스 : 스타트업/중소기업, 2023년
• 경쟁 시나리오와 동향

제11장 기업 개요

• 소개
• 주요 진출 기업
  • IBM
  • MICROSOFT
  • GOOGLE
  • SALESFORCE
  • SAP
  • AWS
  • SAS INSTITUTE
  • FICO
  • ACCENTURE
• 기타 주요 기업
  • ONETRUST
  • QLIK
  • H20.AI
  • ALTERYX
  • DATAROBOT
  • DATAIKU
  • DOMINO DATA LABS
  • SPARKCOGNITION
  • COLLIBRA
  • QUEST SOFTWARE
  • SECURITI
• 스타트업/중소기업
  • MONITAUR
  • FIDDLER AI
  • UNTANGLE AI
  • 2021.AI
  • HOWSO
  • MIND FOUNDRY
  • CREDO AI
  • HOLISTIC AI
  • FAIRLY AI
  • ENZAI
  • VALIDMIND
  • FAIRNOW
  • MONA LABS
  • ARTHUR AI
  • TRUSTIBLE
  • ATLAN
  • MODELOP
  • NEPTUNE.AI
  • PATRONUS AI
  • DATATRON
  • MODOLUS
  • CALVIN RISK
  • SAIDOT
  • CENSIUS
  • BREEZEML
  • ANCH.AI
  • PRODAGO
  • QUANTPI
  • YOOI

제12장 인접 시장과 관련 시장

제13장 부록

ksm

영문 목차

영문목차

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.

Scope of the Report
Years Considered for the Study	2019-2029
Base Year	2023
Forecast Period	2024-2030
Units Considered	USD (Million)
Segments	Product Type, Functionality, End User, and Region
Regions covered	North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

"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

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