Market Overview
The
Global AI Governance Market is projected to reach
USD 185.5 million in 2025 and grow at a compound annual
growth rate of 39.0% from there until 2033 to reach a
value of USD 3,594.8 million.
AI Governance includes regulations, policies, and practices that govern the development, deployment, and usage of AI technologies with an aim for societal impact, privacy, fairness, accountability, and safety. The framework is characterized by non-discrimination a transparency, and emphasizes the protection of personal data and privacy rights. AI governance, like certification processes, auditing, impact assessments, and public consultation, can be implemented through a collaborative effort including governments, regulatory bodies, and civil society organizations. As a result, it is applied in many sectors like healthcare, finance, and autonomous vehicles to ensure proper use of AI and maintain safety and reliability in AI-based systems.
The global AI governance market is experiencing significant growth, driven by the rising adoption of AI in high-risk sectors such as healthcare, finance, and government. Organizations are under mounting pressure to ensure transparency, fairness, and compliance in AI-driven decision-making, especially amid increasing regulatory scrutiny like the EU AI Act. One major trend is the integration of ethical AI frameworks into MLOps pipelines to enhance trust and accountability.
However, a key restraint lies in the lack of standardized regulations across regions, leading to inconsistent enforcement and implementation. Another barrier is the shortage of skilled professionals capable of designing and implementing governance frameworks tailored to complex AI models. The growing demand for explainable AI and responsible deployment across enterprises creates compelling opportunities for vendors offering end-to-end governance platforms and AI auditing tools.
The US AI Governance Market
The US AI Governance Market is projected to reach USD 53.9 million in 2025 at a compound annual growth rate of 36.5% over its forecast period.
The AI governance market in the US offers various growth opportunities due to higher AI adoption across industries, increased focus on data privacy, and evolving regulatory frameworks. Government initiatives, like AI ethics guidelines and cybersecurity measures, are driving the need for AI governance solutions. In addition, collaborations between tech companies and regulatory bodies are fostering innovation and responsible AI deployment, further expanding market potential.
Further, a key growth driver for the market is the large adoption of AI technologies across industries, along with rising concerns over data privacy and ethical AI practices. However, a major restraint is the high cost and complexity of implementing complete AI governance frameworks, which can be challenging for smaller organizations with limited resources.
The United States leads the AI governance market due to its early adoption of AI technologies across industries and its proactive stance on responsible AI development. The country benefits from a unique data advantage, with massive volumes of structured and unstructured data generated from enterprise systems, social platforms, and IoT networks. Additionally, its diverse demographic composition enhances AI model training but also necessitates robust bias mitigation strategies. U.S.-based tech giants such as IBM, Microsoft, and Google are driving innovations in AI governance through platforms that support explainability, transparency, and auditability.
The Biden administration’s push for a national AI strategy and increasing federal investments in ethical AI are further stimulating market growth. Despite regulatory fragmentation at the state level, private-sector initiatives and public-private partnerships are propelling the U.S. ahead in governance standardization. This positions the U.S. as a benchmark market for AI governance innovation, supported by its talent pool, R&D ecosystem, and mature digital infrastructure.
Global AI Governance Market:Key Takeaways
- Market Growth: The AI Governance Market size is expected to grow by 3,344.2 million, at a CAGR of 39.0% during the forecasted period of 2025 to 2034.
- By Offering: The software segment is anticipated to get the majority share of the AI Governance Market in 2025.
- By Size of Organization: Large Enterprise segment is expected to be leading the market in 2025
- By End Use Industry: The government & defense segment is expected to get the largest revenue share in 2025 in the AI Governance Market.
- Regional Insight: North America is expected to hold a 32.9% share of revenue in the Global AI Governance Market in 2025.
- Use Cases: Some of the use cases of AI Governance include risk management, regulatory compliance, and more.
Global AI Governance Market:Use Cases
- Ethical AI Development: Ensures AI systems are developed & deployed in a way that follows ethical standards, avoiding biases and discrimination in areas like hiring, law enforcement, and lending.
- Bias Detection in Hiring Platforms: Governance frameworks in AI-based recruitment systems identify and mitigate algorithmic bias, ensuring fair hiring practices and equal opportunity regardless of demographic or socio-economic status.
- Regulatory Compliance: Supports organizations that meet legal requirements related to data privacy, safety, and accountability, like GDPR or other data protection laws.
- Risk Management: Reduces risks linked with AI failures, live unintended behaviors, security vulnerabilities, or operational disruptions, ensuring reliable and safe AI deployment.
- Transparency and Accountability: Develop frameworks for explaining AI decisions, allowing users and stakeholders to understand how AI systems work and ensuring accountability for AI-driven actions.
Global AI Governance Market: Stats and Facts
- In 2024, the European Commission passed the long-awaited EU Artificial Intelligence Act into law, establishing the first comprehensive AI regulation, which, like the GDPR, is expected to shape similar legislative frameworks worldwide through its influential compliance structure.
- In 2024, the European Commission enacted the EU AI Act after prolonged debate, marking a historic regulatory milestone that, akin to GDPR’s legacy, is anticipated to inspire analogous AI governance laws across numerous international jurisdictions.
Market Dynamic
Global AI Governance Market: Driving Factors
Increasing Regulatory PressureGovernments and international organizations are implementing stricter regulations and guidelines (e.g., GDPR, AI Act) to ensure the responsible use of AI, which drives demand for AI governance solutions to support organizations' compliance with these changes in legal requirements. One of the strongest growth drivers for the global AI governance market is the rising wave of national and international regulatory frameworks focused on responsible AI.
Governments across Europe, North America, and Asia-Pacific are drafting and enacting AI-specific legislation to ensure fairness, accountability, privacy, and security in AI applications. For instance, the European Union’s AI Act sets a precedent by categorizing AI systems by risk level and assigning strict governance requirements to high-risk categories. In the U.S., the Algorithmic Accountability Act and state-level initiatives are also emphasizing ethical deployment and automated decision transparency. These regulatory developments are compelling organizations to invest in AI governance solutions to mitigate legal risks, avoid penalties, and ensure operational continuity.
Rapid Enterprise AI Adoption across High-Stakes Industries
The swift expansion of AI into mission-critical applications in finance, healthcare, legal, manufacturing, and public services is fueling the demand for robust AI governance systems. In high-stakes sectors, where AI is used for diagnosing diseases, underwriting loans, detecting fraud, or managing city infrastructure, errors or biases can lead to disastrous consequences, including litigation, financial loss, or even life-threatening outcomes.
As AI adoption grows, so does the need to build confidence among stakeholders by ensuring systems are accurate, fair, accountable, and secure. Enterprises are proactively seeking governance platforms that allow real-time monitoring, automated documentation, and performance benchmarking of models. This is especially important as AI systems move beyond experimental projects into production environments with real-world implications.
Global AI Governance Market: Restraints
Lack of Standardized Frameworks
One of the most pressing restraints in the AI governance market is the absence of universally accepted governance standards or regulatory consistency across different regions. While the EU is leading with the AI Act and the OECD has offered guiding principles, countries like the U.S., China, India, and others are taking divergent approaches to AI regulation.
This creates a fragmented landscape for multinational enterprises, which must navigate a maze of overlapping, inconsistent, or even conflicting rules. The lack of harmonization hinders the scalability of governance solutions, as organizations are forced to customize frameworks to fit each jurisdiction. This not only increases compliance costs but also complicates vendor offerings, as AI governance tools must be modular enough to address a spectrum of local norms and legal obligations.
Shortage of AI Governance Talent and Technical Expertise
Despite growing interest, one of the most significant bottlenecks facing the AI governance market is the shortage of professionals with the necessary blend of technical, legal, and ethical expertise. Implementing AI governance involves more than installing tools—it requires a multidisciplinary team capable of understanding machine learning architectures, identifying biases, evaluating legal risk, and aligning model behavior with organizational values.
Currently, few professionals have this hybrid skillset, creating a talent vacuum. Moreover, the rapid evolution of AI technologies means governance professionals must continuously update their knowledge, tools, and methodologies. The scarcity of trained experts slows down the deployment of governance frameworks, especially in mid-sized organizations or emerging markets. Training and certification programs for AI governance are still nascent, leaving enterprises to rely heavily on consultancy services, which may not be sustainable or scalable.
Global AI Governance Market: Opportunities
Emergence of LLM Governance and Generative AI Risk Management
The rise of large language models (LLMs) like ChatGPT, Claude, and Bard has created an entirely new set of governance challenges and opportunities. These generative AI models can produce human-like content but also pose substantial risks related to misinformation, hallucination, bias, copyright infringement, and data leakage. As enterprises begin integrating LLMs into customer service, content creation, legal analysis, and more, the need for specialized governance tools tailored to generative AI becomes critical.
This opens up a high-growth opportunity for vendors offering LLMOps (Large Language Model Operations) platforms and tools designed to monitor prompts, assess output quality, apply ethical filters, and implement access controls. Organizations are investing in responsible AI layers that sit on top of LLMs to manage risk and ensure regulatory alignment.
Growing Demand for Cross-Industry AI Governance Platforms
There is a significant opportunity in developing industry-agnostic AI governance platforms that offer modular, customizable governance frameworks applicable across verticals such as telecom, automotive, software, and retail. While early governance solutions were tailored to specific sectors like finance or healthcare, today’s multi-sector AI adoption calls for broader solutions that can handle diverse regulatory and business environments.
Vendors that can deliver governance capabilities such as bias detection, model monitoring, explainability, risk scoring, and compliance tracking in a scalable, plug-and-play format are likely to capture a larger market share. This is especially true for global enterprises operating in multiple jurisdictions, each with different regulatory expectations. Unified platforms that integrate seamlessly with existing AI workflows, cloud environments, and enterprise applications provide unmatched flexibility and ROI.
Global AI Governance Market: Trends
Integration of Responsible AI into MLOps Pipelines
A major trend shaping the AI governance market is the seamless integration of responsible AI practices into MLOps (Machine Learning Operations) pipelines. As organizations scale AI applications, ensuring transparency, traceability, and accountability throughout the model lifecycle is becoming crucial. This has led to a growing demand for tools and platforms that support model explainability, bias detection, audit trails, and compliance reporting natively within MLOps workflows.
AI governance solutions are increasingly being built to work with continuous integration/continuous deployment (CI/CD) processes to enforce ethical standards from data ingestion to model deployment. Vendors now offer capabilities that allow teams to monitor drift, enforce version control, and evaluate models across fairness, performance, and legal thresholds in real time. As regulatory frameworks like the EU AI Act and the U.S. Algorithmic Accountability Act gain traction, embedding governance directly into MLOps ensures that organizations remain agile while maintaining compliance.
Rise of AI Transparency and Explainability as Competitive Differentiators
Enterprises are increasingly treating transparency and explainability not just as compliance requirements but as brand and business differentiators. Customers, regulators, and stakeholders now demand to know how AI models make decisions, particularly in critical sectors like finance, healthcare, and hiring.
As a result, explainable AI (XAI) tools are gaining traction, and governance platforms are prioritizing the inclusion of interpretable model metrics, causal inference tools, and user-friendly dashboards that demonstrate how outcomes are derived. This is especially important in consumer-facing applications, where black-box models could result in reputational risk and regulatory penalties. Companies that adopt robust governance frameworks with clear explainability features are not only reducing legal liabilities but also building consumer trust and investor confidence.
Research Scope and Analysis
By Offering
The solution segment is projected to experience the highest growth during the forecast period, driven by the higher demand for AI governance solutions. These solutions include software tools, platforms, and technologies designed to tackle the ethical, legal, and societal challenges that come with AI development and deployment. Further, the main features of these solutions, like bias detection and mitigation, privacy protection, model governance, and transparency, are all focused on ensuring responsible and ethical AI use.
As organizations become more aware of the importance of strong AI governance frameworks, they are increasingly adopting these solutions to manage the risks linked with AI. The rising focus on ethical AI practices, integrated with the demand to comply with regulations and societal expectations, is driving the growth of this segment as companies look for comprehensive tools to guide their AI strategies.
By Deployment
In 2024, on-premises deployment is expected to dominate the AI governance market, as various organizations are opting for on-premise AI governance solutions to maintain complete control over data management, mainly with the growing complexity of AI operations. Ensuring security is a major factor driving this trend, mainly when handling sensitive or confidential information.
The demand for tight control over data transfers and the ability to manage AI systems directly is vital for many companies. In addition, regulatory demands in several industries mandate that data be stored and processed on-premise, further boosting the demand for these solutions. Further, cloud-based AI governance solutions are gaining traction due to their scalability and flexibility. These cloud-based options enable organizations to manage large volumes of data and AI models more efficiently.
Their simple accessibility also allows businesses to practice AI governance practices across many locations and devices, making monitoring more straightforward, which is creating significant growth opportunities for cloud-based deployments, appealing to companies that demand to handle large volumes of data while maintaining operational efficiency.
By Size of Organization
Based on enterprise size, large enterprises are expected to lead the AI governance market with a dominant share in 2024, driven by a growing focus on data privacy and security. As these organizations look into sensitive information, they are prioritizing the security of their AI systems to reduce the risks linked with cyberattacks and security breaches.
The integration of AI governance is becoming highly important as large businesses look to reduce these risks. To improve their capabilities, many large enterprises are collaborating with AI governance solution providers, while others are acquiring smaller startups in the field.
In addition, the small and medium-sized enterprise (SME) segment is expected to experience rapid growth in the AI governance market throughout the forecast period. SMEs are looking for scalable and affordable solutions that ensure the responsible, ethical, and transparent use of AI.
Since SMEs mostly lack the resources to develop and maintain their own AI governance frameworks, they highly depend on cloud-based solutions provided by AI Governance as a Service (AGaaS) providers. These services allow SMEs to implement best practices in AI governance without the requirement for significant infrastructure investments, driving growth in this segment.
By Technology
Augmented Reality (AR) technologies dominate the AI governance market within the technology segment due to their growing integration into government, defense, healthcare, and smart infrastructure environments, where decision accuracy, data privacy, and ethical usage are paramount. AR overlays digital intelligence onto real-world environments, offering immersive insights for surveillance, military training, urban planning, and crisis management. However, this rich visual and contextual data collection raises major concerns about surveillance ethics, citizen privacy, and real-time data misuse. As a result, AR deployments require strict governance frameworks to ensure transparency, consent-based data usage, and bias-free content delivery.
Moreover, AR often leverages computer vision and AI-driven analytics to process real-time scenarios, demanding robust oversight of algorithmic behavior. These systems are sensitive to environmental context and may amplify unintended consequences without proper regulation. With government and enterprise use of AR increasing globally, organizations are investing in governance solutions that ensure responsible AR deployment, from facial recognition compliance to content moderation. The combination of visual data, context awareness, and real-time feedback positions AR as both a high-potential and high-risk domain, thereby intensifying the need for AI governance and cementing its dominant position in the technology segment.
By Application
Fraud Detection & Risk Management leads the global AI governance market by application due to the critical need for fairness, accuracy, and compliance in financial and high-value decision environments. AI models used in fraud prevention are responsible for monitoring massive datasets to detect anomalies, suspicious transactions, identity theft, and systemic risks. However, these models often deal with sensitive personal and financial information, making them subject to intense scrutiny from regulatory bodies.
The dominance of this segment arises from the dual imperative of operational efficiency and ethical accountability. Without proper governance, these systems can inadvertently introduce bias, discriminate against certain demographics, or generate false positives that harm customer experience and violate privacy laws. Governance frameworks are essential for auditing algorithms, ensuring transparency in decision logic, validating fairness metrics, and complying with regulations such as GDPR, PCI DSS, and emerging AI laws.
Moreover, financial institutions face high regulatory pressure to maintain audit trails and explain AI-driven decisions to customers and compliance officers alike. As fraud tactics evolve, AI models must be continually updated and monitored for risk blind spots, making governance platforms indispensable. The financial and cybersecurity sensitivity involved in fraud detection ensures that it remains the top application in demand for robust, real-time AI governance.
By End User Industry
The government and defense sector is expected to lead the AI governance market in 2024 and is also set to experience the highest growth rate throughout the forecast period, which mostly requires AI systems that are transparent, accountable, and aligned with ethical standards, aiming on key issues such as fairness, minimizing biases, protecting privacy, and ensuring the integrity of AI technologies.
As organizations within this field prioritize responsible AI use, the need for governance solutions and services will rise. These solutions will support addressing the distinct ethical challenges experienced by government and defense entities, ensuring that AI adoption remains both effective and principled. A focus on ethical AI practices will drive the market forward as government and defense organizations look for ways to install AI responsibly and in line with their specific operational and regulatory needs.
Moreover, governments are often the first adopters or sponsors of national AI governance guidelines, such as the U.S. NIST AI Risk Management Framework or the European Commission’s Ethics Guidelines for Trustworthy AI, thus naturally becoming key customers and enforcers of these standards. Their procurement power and regulatory influence also set the pace for AI adoption across industries, further reinforcing their dominant market position.
In defense specifically, the need to avoid unintended military escalation through autonomous systems has prompted deep investment in AI transparency and chain-of-command control mechanisms. This, combined with growing smart city initiatives and national digital transformation programs, makes Government & Defense the most influential end-user vertical in AI governance globally.
The AI Governance Market Report is segmented on the basis of the following
By Offering
- Solution
- Risk & Compliance Management
- Audit Trail Management
- Policy Management
- Financial Forecasting
- Identity & Access Management
- Data Privacy Tools
- End-to-End AI Governance Platforms
- Data Governance Platforms
- MLOps Tools
- LLMOps Tools
- Services
- Professional Services
- Managed Services
- Support & Maintenance
- AI Governance Consulting Services
- AI Governance as a Service
By Deployment
By Size of Organization
By Technology
- Machine Learning (ML)
- Natural Language Processing (NLP)
- Computer Vision
- Robotic Process Automation (RPA)
- Context-aware Computing
By Application
- Regulatory Compliance
- Fraud Detection & Risk Management
- Citizen Engagement & Public Safety
- Policy Analysis & Decision Making
- Smart City & Infrastructure Monitoring
- Data Management & Record Keeping
- Budgeting & Financial Analytics
By End User Industry
- BFSI
- Telecommunication
- Government & Defense
- Healthcare & Life science
- Manufacturing
- Retail & Consumer Goods
- Software & Technology Providers
- Automotive
- Media & Entertainment
- Other End User
Regional Analysis
Region with the Highest Market Share
North America is set to lead the global AI governance market
with a 32.9% share in 2024, driven by the higher use of artificial intelligence (AI) across both commercial and governmental sectors, which is a key factor driving the market growth. Over the past few years, U.S. legislators and government bodies have been actively creating regulations and strategies for AI and automated systems. These policies focus on striking a balance between promoting innovation and competition while reducing the potential negative impacts of AI technology. In addition, countries like the U.S. and Canada, known for their early adoption of advanced technologies like machine learning, are expected to continue driving the growth of the AI market in the region.
Region with the Highest CAGR
Europe is also anticipated to play a significant role in AI regulation, focusing largely on data privacy and the ethical use of AI. Recent regulations, like the General Data Protection Regulation (GDPR) and the proposed AI Act, aim to tackle concerns like data privacy, discrimination, and transparency in AI algorithms. There is also a major push to establish ethical frameworks for AI development, led by organizations like the European Alliance and the High-Level Expert Group on AI. Further, individual countries, like the UK, have developed their own AI governance guidelines. The UK’s AI Code of Conduct, for example, promotes principles like accountability, fairness, and transparency in AI usage. These efforts highlight Europe's commitment to responsible AI governance and ethical standards.
Europe
- Germany
- The U.K.
- France
- Italy
- Russia
- Spain
- Benelux
- Nordic
- Rest of Europe
Asia-Pacific
- China
- Japan
- South Korea
- India
- ANZ
- ASEAN
- Rest of Asia-Pacific
Latin America
- Brazil
- Mexico
- Argentina
- Colombia
- Rest of Latin America
Middle East & Africa
- Saudi Arabia
- UAE
- South Africa
- Israel
- Egypt
- Rest of MEA
Competitive Landscape
The AI governance market is becoming highly competitive as various players focus on developing solutions that address ethical, legal, and regulatory challenges tied to AI. Companies are investing largely in advanced technologies like bias detection, transparency tools, and privacy protection features to meet the increased demand for responsible AI usage. In addition, strategic partnerships, acquisitions, and collaborations are common as firms focus on enhancing their offerings and expanding their market presence.
The competition is also intensifying as new startups emerge, providing innovative, affordable solutions to meet the needs of businesses of all sizes. Specialized firms such as Fiddler AI, Credo AI, Truera, and Arthur AI are carving out strong positions by offering dedicated responsible AI platforms and explainable AI tools, targeting sectors with high regulatory sensitivity, such as BFSI, healthcare, and government. Meanwhile, consulting giants like Deloitte, PwC, and EY provide AI governance advisory, auditing, and compliance services, enabling enterprises to align their AI workflows with ethical and legal standards.
Startups and mid-tier vendors are also entering the landscape with niche offerings such as contextual fairness testing, bias mitigation, and real-time model monitoring. Competitive dynamics are shaped by increasing regulatory scrutiny, demand for AI transparency, and the proliferation of generative AI systems, driving a continuous need for agile, compliant, and industry-specific governance solutions.
Some of the prominent players in the Global AI Governance are:
- IBM
- Microsoft
- Google
- AWS (Amazon Web Services)
- H2O.ai
- DataRobot
- Fiddler AI
- SAS Institute
- SAP
- Oracle
- Salesforce
- PwC
- Accenture
- Deloitte
- BCG (Boston Consulting Group)
- Meta (Facebook)
- Nvidia
- C3.ai
- Infosys
- Atos
- Other Key Players
Recent Developments
- In March 2025, Microsoft introduced a new AI Governance Toolkit for Azure OpenAI users, featuring integrated audit trails, risk management tools, and policy compliance frameworks to support responsible AI deployment and enterprise-level regulatory adherence.
- In March 2025, IBM and PwC formed a strategic alliance to co-develop AI Governance-as-a-Service for the financial sector, focusing on regulatory compliance, auditability, and risk controls aligned with global AI ethics and transparency standards.
- In January 2025, Fiddler AI secured $40 million in Series C funding to expand its platform capabilities, focusing on scalable explainability, bias detection, and real-time AI model validation for heavily regulated industries like banking and healthcare.
- In January 2025, Truera partnered with Google Cloud to offer seamless integration of its ethical AI monitoring tools, enabling real-time bias detection, model performance evaluation, and governance reporting within cloud-native AI development environments.
- In September 2024, the National Information Security Standardization Technical Committee unveiled that it had designed the first version of the 'Artificial Intelligence Security Governance Framework' and launched it to the public. The Framework focuses on upholding a people-centered approach and adhering to the principle of developing artificial intelligence (AI) for good.
- In September 2024, the UN and the OECD announced a collaboration on global AI governance, as the speed of technology development and the breadth of its impact require various policy ecosystems to work more cohesively. Further, the OECD & the UN would link their efforts to help governments enhance the quality and timeliness of their policy response to AI’s opportunities and its risks.
- In July 2024, China announced its plans to have mass production of AI-driven humanoid robots by 2025 and leadership in the sector by 2027. the country has published a set of governance guidelines & commitments for AI technology that it aspires to adopt globally.
- In March 2024, the Ministry of Communication and Information unveiled that the Government of Indonesia provides policies and governance to optimize the benefits and minimize the threats of artificial intelligence (AI) to society through horizontal and vertical approaches.
- In October 2023, the United Nations unveiled the creation of a new AI Advisory Body to help the international community’s efforts to govern artificial intelligence. As for developing economies, AI provides the possibility of leapfrogging outdated technologies and bringing services directly to people who need them most. The transformative potential of AI for good is difficult even to grasp.
Report Details
| Report Characteristics |
| Market Size (2025) |
USD 185.5 Mn |
| Forecast Value (2034) |
USD 3,594.8 Mn |
| CAGR (2024-2034) |
39.0% |
| Historical Data |
2019 – 2024 |
| The US Market Size (2025) |
USD 53.9 Mn |
| Forecast Data |
2025 – 2034 |
| Base Year |
2024 |
| Estimate Year |
2025 |
| Report Coverage |
Market Revenue Estimation, Market Dynamics, Competitive Landscape, Growth Factors and etc. |
| Segments Covered |
By Offering (Solution, Services), By Deployment (On-Premise, Cloud-based), By Size of Organization (Small and Medium-sized Enterprises (SMEs), Large Enterprises), By Technology (Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Robotic Process Automation (RPA), Context-aware Computing), By Application (Regulatory Compliance, Fraud Detection & Risk Management, Citizen Engagement & Public Safety, Policy Analysis & Decision Making, Smart City & Infrastructure Monitoring, Data Management & Record Keeping, Budgeting & Financial Analytics), By End User (BFSI, Telecommunication, Government & Defense, Healthcare & Life Sciences, Manufacturing, Retail & Consumer Goods, Software & Technology Providers, Automotive, Media & Entertainment, Other End Users) |
| Regional Coverage |
North America – The US and Canada; Europe – Germany, The UK, France, Russia, Spain, Italy, Benelux, Nordic, & Rest of Europe; Asia- Pacific– China, Japan, South Korea, India, ANZ, ASEAN, Rest of APAC; Latin America – Brazil, Mexico, Argentina, Colombia, Rest of Latin America; Middle East & Africa – Saudi Arabia, UAE, South Africa, Turkey, Egypt, Israel, & Rest of MEA
|
| Prominent Players |
IBM Corp, Alphabet Inc, Microsoft Corp, Amazon Web Services, SAS Institute, SAP SE, Facebook Inc, FICO Inc, H2O.ai., Salesforce, and Other Key Players |
| Purchase Options |
We have three licenses to opt for: Single User License (Limited to 1 user), Multi-User License (Up to 5 Users) and Corporate Use License (Unlimited User) along with free report customization equivalent to 0 analyst working days, 3 analysts working days and 5 analysts working days respectively. |
Frequently Asked Questions
The Global AI Governance Market size is expected to reach a value of USD 185.5 million in 2024 and is expected to reach USD 3,594.8 million by the end of 2033.
North America is expected to have the largest market share in the Global AI Governance Market with a share of about 32.9% in 2024.
The AI Governance Market in the US is expected to reach USD 53.9 million in 2024.
Some of the major key players in the Global AI Governance Market are IBM Corp, Alphabet Inc., Microsoft Corp, and others.
The market is growing at a CAGR of 39.0 percent over the forecasted period.