The Global AI Governance Market size is expected to reach $562.9 Million by 2028, rising at a market growth of 34.5% CAGR during the forecast period.
Artificial intelligence (AI) technology has practical uses in modern life. When AI technology is accepted and utilized well, it may benefit economies and society. However, concerns concerning public safety and security have been raised by the growing usage of AI across a range of sectors, including transportation, healthcare, education, and others, necessitating the need for AI governance. Therefore, a legislative framework should exist to ensure that Machine Learning (ML) technologies are correctly examined and systematically developed to support humanity's fair acceptance of AI technology, according to the philosophy underlying AI governance.
In the context of AI (Artificial Intelligence) governance, bias, ROI (return on investment) risk, and algorithm efficacy are assessed and tracked. AI governance's primary goal is to bridge the ethical responsibility and technical progress gaps. The expansion of the AI governance business is driven mainly by the increase in government initiatives to employ Al technology, rapid and simple access to historical datasets, and the convenience of data storage.
Therefore, a legislative framework should exist to ensure that Machine Learning (ML) technologies are adequately examined and systematically developed to support humanity's fair acceptance of AI technology, according to the philosophy underlying AI governance. AI (Artificial Intelligence) governance includes evaluation and monitoring of algorithm performance, ROI risk, and bias. AI governance's primary goal is to bridge the ethical responsibility and technical progress gaps.
The workforce will need a high level of trust in AI governance to close gaps and boost their confidence in automated systems while making routine, life-altering choices. Because of AI's rising advantages, organizations and governments from all over the globe are adopting a range of steps to embrace AI and machine learning technology and position themselves as market leaders. Councils, new norms and legislation, and AI governance solutions are now being developed by governments all around the globe. As a result, a better degree of adherence to technology regulation is anticipated to give profitable chances for the AI governance market projection. AI may also drastically eliminate gender-based discrimination.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The below illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Google LLC (Alphabet Inc.), IBM Corporation, SAP SE, Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce.com, Inc., Meta Platforms, Inc., SAS Institute, Inc., Tibco Software, Inc. (Vista Equity Partners), and QlikTech International AB.
Artificial intelligence (AI) technology has practical uses in modern life. When AI technology is accepted and utilized well, it may benefit economies and society. However, concerns concerning public safety and security have been raised by the growing usage of AI across a range of sectors, including transportation, healthcare, education, and others, necessitating the need for AI governance. Therefore, a legislative framework should exist to ensure that Machine Learning (ML) technologies are correctly examined and systematically developed to support humanity's fair acceptance of AI technology, according to the philosophy underlying AI governance.
In the context of AI (Artificial Intelligence) governance, bias, ROI (return on investment) risk, and algorithm efficacy are assessed and tracked. AI governance's primary goal is to bridge the ethical responsibility and technical progress gaps. The expansion of the AI governance business is driven mainly by the increase in government initiatives to employ Al technology, rapid and simple access to historical datasets, and the convenience of data storage.
Therefore, a legislative framework should exist to ensure that Machine Learning (ML) technologies are adequately examined and systematically developed to support humanity's fair acceptance of AI technology, according to the philosophy underlying AI governance. AI (Artificial Intelligence) governance includes evaluation and monitoring of algorithm performance, ROI risk, and bias. AI governance's primary goal is to bridge the ethical responsibility and technical progress gaps.
The workforce will need a high level of trust in AI governance to close gaps and boost their confidence in automated systems while making routine, life-altering choices. Because of AI's rising advantages, organizations and governments from all over the globe are adopting a range of steps to embrace AI and machine learning technology and position themselves as market leaders. Councils, new norms and legislation, and AI governance solutions are now being developed by governments all around the globe. As a result, a better degree of adherence to technology regulation is anticipated to give profitable chances for the AI governance market projection. AI may also drastically eliminate gender-based discrimination.
COVID-19 Impact Analysis
Chief risk officers and their teams have had to reevaluate outdated methods and assumptions used to manage and monitor risk due to the present pandemic crisis. The worldwide impact of COVID-19 has shown the significance of interconnection in international collaboration and the challenges posed by antiquated technology for efficient governance. Consequently, many governments have been hurrying to find, assess, and buy trustworthy AI-powered solutions. In addition, the necessity to operationalize ethical AI concepts has increased as a result of COVID-19. Taking all of this into account, the pandemic would have significantly helped the market for AI governance.Market Growth Factors
Fast and convenient access to the historical dataset and ease of data storage
An important aspect influencing AI advancement is the accessibility of previous datasets. Healthcare facilities and governmental organizations are creating unstructured data that is available to the research community now that data storage and recovery are more economical. As a result, researchers now have access to enormous databases covering anything from historical rainfall patterns to clinical imaging. By granting access to massive datasets, next-generation computer architectures let academics and information scientists develop more swiftly. These elements have fueled the market for AI governance.Growing government usage of the Al technology
Due to the growing advantages of Al, organizations, and governments throughout the globe are starting initiatives to embrace Al and ML technologies and position themselves as market leaders. Government entities from several countries establish councils, new laws and regulations, and frameworks to adopt Al governance solutions. Increasing public trust in Al technology and protecting civil liberties and private information are the key objectives of governments deploying Al governance solutions. In addition, to identify risk problems for Al technology, several companies have formed committees in collaboration with providers of Al solutions, academic institutions, and research centers.
Market Restraining Factors
Establishing comprehensive ai ethical standards.
Over the past few years, numerous principles and guidelines have been established by various governmental agencies, professional organizations, regulatory systems, and AI companies. These guidelines serve as a foundation for developing robust AI regulations and aid in identifying the most important ethical concerns that need to be addressed. However, there are no all-inclusive rules, even if some ideas have been widely accepted. For instance, if laws are created to safeguard one significant value protected by principles, another value may suffer, which might be detrimental to social ethics. Establishing comprehensive ethical standards for AI that consider all ethical principles might thus be a constraining factor for the state of AI governance solutions today.Component Outlook
Based on the component, the AI governance market is divided into solution and service categories. The solution segment dominated the AI governance market share with maximum revenue share in 2021. Many elements, including growing dependency, user desire for AI-based solutions, and others, bring this on. The platform and software tools that would provide end-to-end AI governance solutions to AI developers, business users, data scientists, and IT architects in several sectors are referred to as the AI governance solution. These facilitate the creation, management, and use of AI solutions and enable enterprises to use a variety of AI and associated skills.Deployment Mode Outlook
Based on the deployment mode, the AI governance market is divided into on-premise and cloud. In 2021, the cloud segment recorded a remarkable revenue share in the AI governance market. This is because AI services delivered through the cloud are the perfect option for many businesses. To access computation, they don't need to create a vast data center; instead, they may leverage the already established infrastructure. In reality, the availability of several plug-and-play AI cloud services from cloud providers, as well as access to sufficient computational capacity and pre-trained models to start AI applications, is one reason AI has grown so prevalent.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The below illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.
Organization Size Outlook
Based on the Organization size, the AI governance market is segmented into large enterprises and small and medium-sized enterprises (SMEs). The large enterprise segment projected the maximum revenue share in the AI governance market in 2021. As businesses want to ensure that their AI systems safeguard sensitive data, the emphasis on data privacy and security is growing. Furthermore, implementing AI governance to decrease risk is anticipated to increase as big organizations are increasingly vulnerable to cyberattacks and other security challenges. This would encourage market development in this niche.Vertical Outlook
Based on industry vertical, the AI governance market is divided into the BFSI, government & defense, healthcare & life sciences, media & entertainment, retail, IT & telecom, automotive, and others. The retail segment covered a considerable revenue share in the AI governance market in 2021. The retail industry is going through a substantial shift. Customers' channel choices and purchasing behaviors alter as they grow more digitally literate. Concerns concerning data have arisen as a result of the transition to digital. Proper AI governance is essential to improve overall retail performance, address common issues, and maintain an edge against more potent retail rivals and agile direct-to-consumer businesses.Regional Outlook
Based on the geography, the AI governance market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region led the AI governance market by generating maximum revenue share in 2021. This is due to the US having a significant industrial base, government programs to support research, and considerable purchasing power supporting the expansion of the AI governance market. Additionally, several significant AI governance solution vendors are launching new services & solutions.The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Google LLC (Alphabet Inc.), IBM Corporation, SAP SE, Amazon Web Services, Inc. (Amazon.com, Inc.), Salesforce.com, Inc., Meta Platforms, Inc., SAS Institute, Inc., Tibco Software, Inc. (Vista Equity Partners), and QlikTech International AB.
Strategies Deployed in AI Governance Market
Partnerships, Collaborations and Agreements:
- Oct-2022: Microsoft collaborated with Haleon, a UK-based healthcare company, engaged in oral health, respiratory, pain relief, supplements, etc. This collaboration involves working towards increasing the Microsoft Seeing AI app's functionality and providing users with more in-depth information regarding 1,500+ Haleon products.
- Sep-2022: Amazon Web Services teamed up with SK Telecom, a South Korea-based telecommunications company, primarily into digital infrastructure services, AI, mobile network operator, etc. The collaboration involves combining SK Telecom's experience in AI, with AWS's flexibility, and scalability, which would help advance innovation in AI, and would prove economical for the consumers to develop, use and scale computer vision applications, which strengthens productivity, and plant safety.
- Jul-2022: Meta platforms came into partnership with Oasis Labs, a company providing privacy-related software. This acquisition would bring fairness to AI models with the help of privacy technologies. This would benefit the users present worldwide and benefit the whole of society.
- May-2022: Amazon Web Services, Inc. teamed up with STMicroelectronics, a global company engaged in the development and creation of semiconductor technologies. In this Collaboration, both companies would securely connect Internet of Things devices to the AWS cloud.
- Dec-2021: Amazon Web Services, Inc. collaborated with Meta, an American multinational technology conglomerate to provide cloud services to AWS. Under this collaboration, both companies would work together to enhance the functioning of customers running PyTorch on AWS and boost how developers create, train, deploy and operate machine learning/artificial intelligence models.
- Nov-2021: Google Cloud teamed up with Qualcomm Technologies, Inc., a multinational corporation based in California. This collaboration would boost neural network development and differentiation for the Snapdragon Ride™ Platform, Snapdragon® mobile, ACPC, and XR platforms, and Qualcomm Technologies’ IoT platforms by using Google Cloud Vertex AI Neural Architecture Search (NAS) with the Qualcomm® Artificial Intelligence (AI) Engine.
- Sep-2020: Microsoft teamed up with AT&T, a telecommunication holding company. Through this collaboration, companies would aim to provide an integrated IoT solution to allow companies to smoothly connect machines to the cloud with highly protected network connectivity.
- Oct-2020: SAS formed a partnership with TMA Solutions, a privately owned software outsourcing company. This partnership aimed to provide analytics solutions in AI and Data Analytics to companies in Vietnam via its cloud-native analytics platform, which would offer business insights for decision-making.
- Jun-2020: Salesforce extended its partnership with Snowflake, a cloud computing-based data warehousing company. Following this partnership, the companies would introduce a data marketplace, new data integration tools, and other capabilities in order to assist organizations in migrating Salesforce data to the Snowflake platform for collaboration and analysis.
Product Launches and Product Expansions:
- Jun-2022: Google added new features to its previously launched product Vertex. The addition of new features in Vertex AI would boost the deployment of machine learning models in organizations and democratize AI so more people can distribute models in production, driving business impact and continuous monitoring with AI.
- Sep-2021: TIBCO unveiled TIBCO Cloud Composer, TIBCO Cloud Discover, and TIBCO LABS Gallery, additions in its TIBCO Cloud portfolio. The new product would enable partners and customers to bring innovations in connecting and developing new applications or defining data, digital strategies, and data management.
- Jun-2021: IBM introduced IBM Cloud Pak for Network Automation, a hybrid cloud AI-powered automation software intended to use by communications service providers (CSPs), and can run in varied environments. This product enables IBM to provide better services to its clients in the telco industry, by using AI-powered automation which solves the problem of limited automation and less real-time visibility.
Acquisition and Mergers:
- Oct-2022: Google completed the acquisition of Alter, an artificial intelligence (AI) avatar startup engaged in helping brands and creators express themselves. Through this acquisition, Google would improve both the quality and quantity of the content provided to consumers.
- Jul-2022: IBM took over Databand.ai, an Israel-based database software company, primarily into providing data observability platform. This acquisition reinforces IBM's data, automation, and AI software offerings, and enables IBM to offer an all-inclusive set of observability capabilities.
- Jul-2022: IBM took over Databand, a startup developing an observability platform. This acquisition aimed to deliver the customers and partners with the technology they require to offer trustworthy data and AI at scale.
- Mar-2022: Microsoft took over Nuance Communications, a leader in conversational AI and ambient intelligence across industries. This acquisition aimed to assist providers in providing more affordable, efficient, and accessible healthcare, and assist companies in every industry develop more customized and meaningful customer experiences.
- Sep-2021: SAP took over SwoopTalent's intellectual property. Following this acquisition, the company would embed data and machine learning technology of SwoopTalent across SAP SuccessFactors solutions.
- Apr-2021: IBM took over Turbonomic, a company engaged in offering tools to manage application performance. With this move, IBM would enhance its footprint by offering enterprises AI-based services to manage their workloads and networks.
- Mar-2021: Microsoft took over The Marsden Group, a global technology group, providing industrial technology. This acquisition strengthened Microsoft's potential to create customer value by experimenting and providing deep industry solutions formed on edge, Microsoft cloud, and AI.
Scope of the Study
By Component
- Solution
- Services
By Vertical
- BFSI
- Healthcare & Lifesciences
- Media & Entertainment
- IT & Telecom
- Retail
- Government
- Automotive
- Others
By Organization size
- Large Enterprises
- SMEs
By Deployment Mode
- On-premise
- Cloud
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
List of Companies Profiled in the Report:
- Microsoft Corporation
- Google LLC (Alphabet Inc.)
- IBM Corporation
- SAP SE
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Salesforce.com, Inc.
- Meta Platforms, Inc.
- SAS Institute, Inc.
- Tibco Software, Inc. (Vista Equity Partners)
- QlikTech International AB
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global AI Governance Market, by Component
1.4.2 Global AI Governance Market, by Vertical
1.4.3 Global AI Governance Market, by Organization size
1.4.4 Global AI Governance Market, by Deployment Mode
1.4.5 Global AI Governance Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Analyst's Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2018, Apr - 2022, Sep) Leading Players
Chapter 4. Global AI Governance Market by Component
4.1 Global Solution Market by Region
4.2 Global Services Market by Region
Chapter 5. Global AI Governance Market by Vertical
5.1 Global BFSI Market by Region
5.2 Global Healthcare & Lifesciences Market by Region
5.3 Global Media & Entertainment Market by Region
5.4 Global IT & Telecom Market by Region
5.5 Global Retail Market by Region
5.6 Global Government Market by Region
5.7 Global Automotive Market by Region
5.8 Global Other Vertical Market by Region
Chapter 6. Global AI Governance Market by Organization size
6.1 Global Large Enterprises Market by Region
6.2 Global SMEs Market by Region
Chapter 7. Global AI Governance Market by Deployment Mode
7.1 Global On-premise Market by Region
7.2 Global Cloud Market by Region
Chapter 8. Global AI Governance Market by Region
8.1 North America AI Governance Market
8.1.1 North America AI Governance Market by Component
8.1.1.1 North America Solution Market by Country
8.1.1.2 North America Services Market by Country
8.1.2 North America AI Governance Market by Vertical
8.1.2.1 North America BFSI Market by Country
8.1.2.2 North America Healthcare & Lifesciences Market by Country
8.1.2.3 North America Media & Entertainment Market by Country
8.1.2.4 North America IT & Telecom Market by Country
8.1.2.5 North America Retail Market by Country
8.1.2.6 North America Government Market by Country
8.1.2.7 North America Automotive Market by Country
8.1.2.8 North America Other Vertical Market by Country
8.1.3 North America AI Governance Market by Organization size
8.1.3.1 North America Large Enterprises Market by Country
8.1.3.2 North America SMEs Market by Country
8.1.4 North America AI Governance Market by Deployment Mode
8.1.4.1 North America On-premise Market by Country
8.1.4.2 North America Cloud Market by Country
8.1.5 North America AI Governance Market by Country
8.1.5.1 US AI Governance Market
8.1.5.1.1 US AI Governance Market by Component
8.1.5.1.2 US AI Governance Market by Vertical
8.1.5.1.3 US AI Governance Market by Organization size
8.1.5.1.4 US AI Governance Market by Deployment Mode
8.1.5.2 Canada AI Governance Market
8.1.5.2.1 Canada AI Governance Market by Component
8.1.5.2.2 Canada AI Governance Market by Vertical
8.1.5.2.3 Canada AI Governance Market by Organization size
8.1.5.2.4 Canada AI Governance Market by Deployment Mode
8.1.5.3 Mexico AI Governance Market
8.1.5.3.1 Mexico AI Governance Market by Component
8.1.5.3.2 Mexico AI Governance Market by Vertical
8.1.5.3.3 Mexico AI Governance Market by Organization size
8.1.5.3.4 Mexico AI Governance Market by Deployment Mode
8.1.5.4 Rest of North America AI Governance Market
8.1.5.4.1 Rest of North America AI Governance Market by Component
8.1.5.4.2 Rest of North America AI Governance Market by Vertical
8.1.5.4.3 Rest of North America AI Governance Market by Organization size
8.1.5.4.4 Rest of North America AI Governance Market by Deployment Mode
8.2 Europe AI Governance Market
8.2.1 Europe AI Governance Market by Component
8.2.1.1 Europe Solution Market by Country
8.2.1.2 Europe Services Market by Country
8.2.2 Europe AI Governance Market by Vertical
8.2.2.1 Europe BFSI Market by Country
8.2.2.2 Europe Healthcare & Lifesciences Market by Country
8.2.2.3 Europe Media & Entertainment Market by Country
8.2.2.4 Europe IT & Telecom Market by Country
8.2.2.5 Europe Retail Market by Country
8.2.2.6 Europe Government Market by Country
8.2.2.7 Europe Automotive Market by Country
8.2.2.8 Europe Other Vertical Market by Country
8.2.3 Europe AI Governance Market by Organization size
8.2.3.1 Europe Large Enterprises Market by Country
8.2.3.2 Europe SMEs Market by Country
8.2.4 Europe AI Governance Market by Deployment Mode
8.2.4.1 Europe On-premise Market by Country
8.2.4.2 Europe Cloud Market by Country
8.2.5 Europe AI Governance Market by Country
8.2.5.1 Germany AI Governance Market
8.2.5.1.1 Germany AI Governance Market by Component
8.2.5.1.2 Germany AI Governance Market by Vertical
8.2.5.1.3 Germany AI Governance Market by Organization size
8.2.5.1.4 Germany AI Governance Market by Deployment Mode
8.2.5.2 UK AI Governance Market
8.2.5.2.1 UK AI Governance Market by Component
8.2.5.2.2 UK AI Governance Market by Vertical
8.2.5.2.3 UK AI Governance Market by Organization size
8.2.5.2.4 UK AI Governance Market by Deployment Mode
8.2.5.3 France AI Governance Market
8.2.5.3.1 France AI Governance Market by Component
8.2.5.3.2 France AI Governance Market by Vertical
8.2.5.3.3 France AI Governance Market by Organization size
8.2.5.3.4 France AI Governance Market by Deployment Mode
8.2.5.4 Russia AI Governance Market
8.2.5.4.1 Russia AI Governance Market by Component
8.2.5.4.2 Russia AI Governance Market by Vertical
8.2.5.4.3 Russia AI Governance Market by Organization size
8.2.5.4.4 Russia AI Governance Market by Deployment Mode
8.2.5.5 Spain AI Governance Market
8.2.5.5.1 Spain AI Governance Market by Component
8.2.5.5.2 Spain AI Governance Market by Vertical
8.2.5.5.3 Spain AI Governance Market by Organization size
8.2.5.5.4 Spain AI Governance Market by Deployment Mode
8.2.5.6 Italy AI Governance Market
8.2.5.6.1 Italy AI Governance Market by Component
8.2.5.6.2 Italy AI Governance Market by Vertical
8.2.5.6.3 Italy AI Governance Market by Organization size
8.2.5.6.4 Italy AI Governance Market by Deployment Mode
8.2.5.7 Rest of Europe AI Governance Market
8.2.5.7.1 Rest of Europe AI Governance Market by Component
8.2.5.7.2 Rest of Europe AI Governance Market by Vertical
8.2.5.7.3 Rest of Europe AI Governance Market by Organization size
8.2.5.7.4 Rest of Europe AI Governance Market by Deployment Mode
8.3 Asia Pacific AI Governance Market
8.3.1 Asia Pacific AI Governance Market by Component
8.3.1.1 Asia Pacific Solution Market by Country
8.3.1.2 Asia Pacific Services Market by Country
8.3.2 Asia Pacific AI Governance Market by Vertical
8.3.2.1 Asia Pacific BFSI Market by Country
8.3.2.2 Asia Pacific Healthcare & Lifesciences Market by Country
8.3.2.3 Asia Pacific Media & Entertainment Market by Country
8.3.2.4 Asia Pacific IT & Telecom Market by Country
8.3.2.5 Asia Pacific Retail Market by Country
8.3.2.6 Asia Pacific Government Market by Country
8.3.2.7 Asia Pacific Automotive Market by Country
8.3.2.8 Asia Pacific Other Vertical Market by Country
8.3.3 Asia Pacific AI Governance Market by Organization size
8.3.3.1 Asia Pacific Large Enterprises Market by Country
8.3.3.2 Asia Pacific SMEs Market by Country
8.3.4 Asia Pacific AI Governance Market by Deployment Mode
8.3.4.1 Asia Pacific On-premise Market by Country
8.3.4.2 Asia Pacific Cloud Market by Country
8.3.5 Asia Pacific AI Governance Market by Country
8.3.5.1 China AI Governance Market
8.3.5.1.1 China AI Governance Market by Component
8.3.5.1.2 China AI Governance Market by Vertical
8.3.5.1.3 China AI Governance Market by Organization size
8.3.5.1.4 China AI Governance Market by Deployment Mode
8.3.5.2 Japan AI Governance Market
8.3.5.2.1 Japan AI Governance Market by Component
8.3.5.2.2 Japan AI Governance Market by Vertical
8.3.5.2.3 Japan AI Governance Market by Organization size
8.3.5.2.4 Japan AI Governance Market by Deployment Mode
8.3.5.3 India AI Governance Market
8.3.5.3.1 India AI Governance Market by Component
8.3.5.3.2 India AI Governance Market by Vertical
8.3.5.3.3 India AI Governance Market by Organization size
8.3.5.3.4 India AI Governance Market by Deployment Mode
8.3.5.4 South Korea AI Governance Market
8.3.5.4.1 South Korea AI Governance Market by Component
8.3.5.4.2 South Korea AI Governance Market by Vertical
8.3.5.4.3 South Korea AI Governance Market by Organization size
8.3.5.4.4 South Korea AI Governance Market by Deployment Mode
8.3.5.5 Singapore AI Governance Market
8.3.5.5.1 Singapore AI Governance Market by Component
8.3.5.5.2 Singapore AI Governance Market by Vertical
8.3.5.5.3 Singapore AI Governance Market by Organization size
8.3.5.5.4 Singapore AI Governance Market by Deployment Mode
8.3.5.6 Malaysia AI Governance Market
8.3.5.6.1 Malaysia AI Governance Market by Component
8.3.5.6.2 Malaysia AI Governance Market by Vertical
8.3.5.6.3 Malaysia AI Governance Market by Organization size
8.3.5.6.4 Malaysia AI Governance Market by Deployment Mode
8.3.5.7 Rest of Asia Pacific AI Governance Market
8.3.5.7.1 Rest of Asia Pacific AI Governance Market by Component
8.3.5.7.2 Rest of Asia Pacific AI Governance Market by Vertical
8.3.5.7.3 Rest of Asia Pacific AI Governance Market by Organization size
8.3.5.7.4 Rest of Asia Pacific AI Governance Market by Deployment Mode
8.4 LAMEA AI Governance Market
8.4.1 LAMEA AI Governance Market by Component
8.4.1.1 LAMEA Solution Market by Country
8.4.1.2 LAMEA Services Market by Country
8.4.2 LAMEA AI Governance Market by Vertical
8.4.2.1 LAMEA BFSI Market by Country
8.4.2.2 LAMEA Healthcare & Lifesciences Market by Country
8.4.2.3 LAMEA Media & Entertainment Market by Country
8.4.2.4 LAMEA IT & Telecom Market by Country
8.4.2.5 LAMEA Retail Market by Country
8.4.2.6 LAMEA Government Market by Country
8.4.2.7 LAMEA Automotive Market by Country
8.4.2.8 LAMEA Other Vertical Market by Country
8.4.3 LAMEA AI Governance Market by Organization size
8.4.3.1 LAMEA Large Enterprises Market by Country
8.4.3.2 LAMEA SMEs Market by Country
8.4.4 LAMEA AI Governance Market by Deployment Mode
8.4.4.1 LAMEA On-premise Market by Country
8.4.4.2 LAMEA Cloud Market by Country
8.4.5 LAMEA AI Governance Market by Country
8.4.5.1 Brazil AI Governance Market
8.4.5.1.1 Brazil AI Governance Market by Component
8.4.5.1.2 Brazil AI Governance Market by Vertical
8.4.5.1.3 Brazil AI Governance Market by Organization size
8.4.5.1.4 Brazil AI Governance Market by Deployment Mode
8.4.5.2 Argentina AI Governance Market
8.4.5.2.1 Argentina AI Governance Market by Component
8.4.5.2.2 Argentina AI Governance Market by Vertical
8.4.5.2.3 Argentina AI Governance Market by Organization size
8.4.5.2.4 Argentina AI Governance Market by Deployment Mode
8.4.5.3 UAE AI Governance Market
8.4.5.3.1 UAE AI Governance Market by Component
8.4.5.3.2 UAE AI Governance Market by Vertical
8.4.5.3.3 UAE AI Governance Market by Organization size
8.4.5.3.4 UAE AI Governance Market by Deployment Mode
8.4.5.4 Saudi Arabia AI Governance Market
8.4.5.4.1 Saudi Arabia AI Governance Market by Component
8.4.5.4.2 Saudi Arabia AI Governance Market by Vertical
8.4.5.4.3 Saudi Arabia AI Governance Market by Organization size
8.4.5.4.4 Saudi Arabia AI Governance Market by Deployment Mode
8.4.5.5 South Africa AI Governance Market
8.4.5.5.1 South Africa AI Governance Market by Component
8.4.5.5.2 South Africa AI Governance Market by Vertical
8.4.5.5.3 South Africa AI Governance Market by Organization size
8.4.5.5.4 South Africa AI Governance Market by Deployment Mode
8.4.5.6 Nigeria AI Governance Market
8.4.5.6.1 Nigeria AI Governance Market by Component
8.4.5.6.2 Nigeria AI Governance Market by Vertical
8.4.5.6.3 Nigeria AI Governance Market by Organization size
8.4.5.6.4 Nigeria AI Governance Market by Deployment Mode
8.4.5.7 Rest of LAMEA AI Governance Market
8.4.5.7.1 Rest of LAMEA AI Governance Market by Component
8.4.5.7.2 Rest of LAMEA AI Governance Market by Vertical
8.4.5.7.3 Rest of LAMEA AI Governance Market by Organization size
8.4.5.7.4 Rest of LAMEA AI Governance Market by Deployment Mode
Chapter 9. Company Profiles
9.1 Microsoft Corporation
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.3 Segmental and Regional Analysis
9.1.4 Research & Development Expenses
9.1.5 Recent strategies and developments:
9.1.5.1 Partnerships, Collaborations, and Agreements:
9.1.5.2 Acquisition and Mergers:
9.1.6 SWOT Analysis
9.2 Google LLC (Alphabet Inc.)
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Segmental and Regional Analysis
9.2.4 Research & Development Expense
9.2.5 Recent strategies and developments:
9.2.5.1 Partnerships, Collaborations, and Agreements:
9.2.5.2 Product Launches and Product Expansions:
9.2.5.3 Acquisition and Mergers:
9.2.6 SWOT Analysis
9.3 IBM Corporation
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Regional & Segmental Analysis
9.3.4 Research & Development Expenses
9.3.5 Recent strategies and developments:
9.3.5.1 Product Launches and Product Expansions:
9.3.5.2 Acquisition and Mergers:
9.3.5.3 Geographical Expansions:
9.3.6 SWOT Analysis
9.4 SAP SE
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Segmental and Regional Analysis
9.4.4 Research & Development Expense
9.4.5 Recent strategies and developments:
9.4.5.1 Acquisition and Mergers:
9.4.6 SWOT Analysis
9.5 Amazon Web Services, Inc. (Amazon.com, Inc.)
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Segmental Analysis
9.5.4 Recent strategies and developments:
9.5.4.1 Partnerships, Collaborations, and Agreements:
9.5.5 SWOT Analysis
9.6 Salesforce.com, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Regional Analysis
9.6.4 Research & Development Expense
9.6.5 Recent strategies and developments:
9.6.5.1 Partnerships, Collaborations, and Agreements:
9.6.6 SWOT Analysis
9.7 Meta Platforms, Inc.
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Segmental and Regional Analysis
9.7.4 Research & Development Expenses
9.7.5 Recent strategies and developments:
9.7.5.1 Partnerships, Collaborations, and Agreements:
9.8 SAS Institute, Inc.
9.8.1 Company Overview
9.8.2 Recent strategies and developments:
9.8.2.1 Partnerships, Collaborations, and Agreements:
9.9 Tibco Software, Inc. (Vista Equity Partners)
9.9.1 Company Overview
9.9.2 Recent strategies and developments:
9.9.2.1 Product Launches and Product Expansions:
9.10. QlikTech International AB
9.10.1 Company Overview
Companies Mentioned
- Microsoft Corporation
- Google LLC (Alphabet Inc.)
- IBM Corporation
- SAP SE
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Salesforce.com, Inc.
- Meta Platforms, Inc.
- SAS Institute, Inc.
- Tibco Software, Inc. (Vista Equity Partners)
- QlikTech International AB
Methodology
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