Report Scope & Overview:

The AI Governance Market size was valued at USD 185.48 Million in 2022 and is expected to reach USD 5949 Million by 2030, and grow at a CAGR of 54.26% over the forecast period 2023-2030.

AI governance is predicated on the premise that a legal framework should be in place to enable appropriate research and development of machine learning technologies to assist humanity in navigating AI systems properly. In addressing issues surrounding the right to be informed and potential breaches, AI governance seeks to bridge the accountability-ethics gap that has emerged in technological innovations. As artificial intelligence becomes more widely used in fields such as transportation, economics, healthcare, business, education, and public safety, the necessity of AI governance grows.

AI Governance Market Revenue Analysis

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These businesses may employ AI governance to enhance online and offline capabilities such as real-time offer management, automated checkout systems, and improved behavior analytics. The key factor driving the growth of the global AI governance market is an increase in government attempts to harness AI technology. With the expanding benefits of AI, enterprises and governments all over the world are launching various programs to use AI and ML technology.



  • Increased government attempts to use AI technology.

  • The growing need to develop confidence in AI systems, as well as the growing desire for openness in AI choices.

  • Increase in regulatory compliances related to technology.


  • Establishment of broad ethical norms for AI.


  • AI-assisted reduction of gender prejudice and discrimination.


  • Inadequate AI knowledge and skills.

  • Clean and relevant data is essential to train machine learning algorithms.


With persistent geopolitical tensions, worldwide trade battles, and hurricanes and earthquakes, managing and monitoring credit, market, liquidity, and operational risk across financial markets was difficult enough. The present pandemic crisis has compelled chief risk officers and their teams to reevaluate past assumptions and risk management methodologies. The worldwide impact of COVID-19 has demonstrated the importance of interconnection in international collaboration, as well as how obsolete technology impedes effective governance. As a result, several governments began hurrying to locate, evaluate, and procure viable AI-powered solutions.

Healthcare institutions throughout the world are turning to AI systems to detect illnesses via people's voices or chest x-rays. Several countries have suggested monitoring systems to trace the virus's transmission from person to person. Several governmental and business sector institutions from Asia to Europe have partnered to use AI-based technologies to track the virus's spread. COVID-19 has heightened the urgency of implementing Ethical AI standards. The World Economic Forum's AI and ML platform developed the Procurement in a Box package to assist practitioners in navigating these difficulties. This package intends to unleash public sector use of AI through government procurement.


The Global AI Governance Market has been divided into two components: solutions and services. In 2021, Solutions will account for the biggest market share. The solutions section is predicted to increase throughout the estimated timeline due to a variety of causes such as rising reliance, user demand for AI-based systems, and so on. The AI governance solution refers to the platform and software tools that give end-to-end AI governance solutions to AI developers, data scientists, business users, and IT architects in a variety of industries. These aid in the collaboration, development, and operation of AI solutions, and allow businesses to combine various AI and associated capabilities for their application.

The automotive industry has the highest market share, followed by government and defense. One of the areas where AI governance solutions are likely to play a significant role is autonomous vehicles. A significant element driving this industry is the presence of several projects underway in the development of self-driving automobiles. Similarly, the introduction of AI-enabled hardware has sparked a significant spike in the ability to allow and improve self-driving technologies and AI algorithms via specialized AI-enabled GPUs. Furthermore, essential AI properties like increased self-control, self-regulation and self-actuation have boosted the use of AI in the defense, military, and government sectors due to improved processing and decision-making skills. Some advantages of AI approaches include their development to improve the accuracy of target detection in complicated battle scenarios.


On The Basis of Component

  • Solution

  • Services

On The Basis of Deployment Mode

  • Cloud

  • On-premises

On The Basis of Organization Size

  • Large enterprises

  • Small and medium-sized enterprises

On The Basis of Vertical

  • BFSI

  • Government and Defense

  • Healthcare and Life Sciences

  • Media and Entertainment

  • Retail

  • IT and Telecom

  • Automotive

  • Other Verticals

AI Governance Market Segmentation Analysis

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North America dominates the artificial intelligence (AI) governance market and will maintain its dominance during the projected period owing to an increase in partnerships, well-established economies, and the presence of large IT businesses in this area. The US government is also proactively implementing AI Governance initiatives. The government announced the adoption of AI ethical guidelines in accordance with the Department of Defense AI strategic goal, supporting the ethical and lawful use of AI systems by the US military and allied companies. Due to the use of artificial intelligence (AI) driven services, Europe will have the greatest CAGR during this time.


  • North America

    • USA

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

    • Italy

    • Spain

    • The Netherlands

    • Rest of Europe

  • Asia-Pacific

    • Japan

    • south Korea

    • China

    • India

    • Australia

    • Rest of Asia-Pacific

  • The Middle East & Africa

    • Israel

    • UAE

    • South Africa

    • Rest of Middle East & Africa

  • Latin America

    • Brazil

    • Argentina

    • Rest of Latin America


The major key players are Alphabet Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Inc., QlikTech International AB, TIBCO Software Inc., SAS Institute Inc., Facebook, Inc., SAP SE,, Inc. & Other Players

SAS Institute Inc - Company Financial Analysis

AI Governance Market Report Scope:
Report Attributes Details
Market Size in 2022  USD 185.48 Million
Market Size by 2030  USD 5949 Million
CAGR  CAGR 54.26% From 2023 to 2030
Base Year  2022
Forecast Period  2023-2030
Historical Data  2020-2021
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • by Component (Solution and Services)
• by Deployment Mode (Cloud and On-premises)
• by Organization Size (Large Enterprises, and Small and medium-sized enterprises)
• by Vertical (BFSI, Government and Defense, Healthcare and Life Sciences, Media and Entertainment, Retail, IT and Telecom, Automotive, and Other Verticals)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, +D11UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
Company Profiles Alphabet Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Inc., QlikTech International AB, TIBCO Software Inc., SAS Institute Inc., Facebook, Inc., SAP SE,, Inc.
Key Drivers •The growing need to develop confidence in AI systems, as well as the growing desire for openness in AI choices.
•Increase in regulatory compliances related to technology.
Market Restraints •Establishment of broad ethical norms for AI.

Frequently Asked Questions

Ans: - The estimated market size for the AI Governance market for the year 2030 is USD 5949 Million.

Ans: - Inadequate AI knowledge and skills and clean and relevant data is essential to train machine learning algorithms.

Ans: - North America dominates the artificial intelligence (AI) governance market and will maintain its dominance during the projected period.

Ans: - The major key players are Alphabet Inc., Microsoft Corporation, IBM Corporation, Amazon Web Services, Inc., QlikTech International AB, TIBCO Software Inc., SAS Institute Inc., Facebook, Inc., SAP SE,, Inc.

Ans: - Key Stakeholders Considered in the study are Raw material vendors, Regulatory authorities, including government agencies and NGOs, Commercial research, and development (R&D) institutions, Importers and exporters, etc.

Table of Contents

1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions

2. Research Methodology

3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges

4. Impact Analysis

4.1 COVID-19 Impact Analysis

4.2 Impact of Ukraine- Russia war

4.3 Impact of ongoing Recession

4.3.1 Introduction

4.3.2 Impact on major economies US Canada Germany France United Kingdom China Japan South Korea Rest of the World


5. Value Chain Analysis


6. Porter’s 5 forces model


7.  PEST Analysis

8. AI Governance Market Segmentation, by Component

8.1 Solution

8.2 Services

9. AI Governance Market Segmentation, by Deployment Mode

9.1 Cloud

9.2 On-premises

10. AI Governance Market Segmentation, by Organization Size

10.1 Large enterprises

10.2 Small and medium-sized enterprises

11. AI Governance Market Segmentation, by Vertical

11.1 BFSI

11.2 Government and Defense

11.3 Healthcare and Life Sciences

11.4 Media and Entertainment

11.5 Retail

11.6 IT and Telecom

11.7 Automotive

11.8 Other Verticals

12. AI Governance  Market Segmentation, by End-user

12.1 BFSI

12.2 Healthcare

12.3 IT and Telecom

12.4 Retail and eCommerce

12.5 Education

12.6 Media and Entertainment

12.7 Automotive

12.8 Others

13. Regional Analysis

13.1 Introduction

13.2 North America

13.2.1 USA

13.2.2 Canada

13.2.3 Mexico

13.3 Europe

13.3.1 Germany

13.3.2 UK

13.3.3 France

13.3.4 Italy

13.3.5 Spain

13.3.6 The Netherlands

13.3.7 Rest of Europe

13.4 Asia-Pacific

13.4.1 Japan

13.4.2 South Korea

13.4.3 China

13.4.4 India

13.4.5 Australia

13.4.6 Rest of Asia-Pacific

13.5 The Middle East & Africa

13.5.1 Israel

13.5.2 UAE

13.5.3 South Africa

13.5.4 Rest

13.6 Latin America

13.6.1 Brazil

13.6.2 Argentina

13.6.3 Rest of Latin America

14. Company Profiles

14.1 Alphabet Inc.

14.1.1 Financial

14.1.2 Products/ Services Offered

14.1.3 SWOT Analysis

14.1.4 The SNS view

14.2 Microsoft Corporation

14.3 IBM Corporation

14.4 Amazon Web Services, Inc.

14.5 QlikTech International AB

14.6 TIBCO Software Inc.

14.7 SAS Institute Inc.

14.8 Facebook, Inc.

14.9 SAP SE

14.10, Inc

15. Competitive Landscape

15.1 Competitive Benchmarking

15.2 Market Share Analysis

15.3 Recent Developments

16. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Primary Research

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

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Data Bank Validation

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