AI Governance Market Is Estimated To Witness High Growth Owing To Growing Need to Ensure AI Systems Are Trustworthy And Beneficial

The AI Governance Market is estimated to be valued at US$ 131.9 Mn in 2024 and is expected to exhibit a CAGR of 46.60% over the forecast period 2022- 2030, as highlighted in a new report published by Coherent Market Insights.

Key Market Dynamics:

The AI ​​governance market is driven by the increasing need of organizations to develop and use AI systems in a reliable, fair, and profitable way around model ambiguity. Data bias and undesirable behavior as AI becomes more advanced and integrated into various applications. Theme emerges This is encouraging companies and governments to it sets principles and best practices for AI development and application. Regulatory pressures on privacy and data security are also driving increased investment in AI solutions and governance to ensure compliance with the law and ethics.

Key Market Trends:

Trend of multi-stakeholder participation

• A key trend in AI governance is an increased emphasis on engaging multiple stakeholders in responsible AI decision-making. This includes integrating the perspectives of civil society, researchers, and communities influenced by AI in addition to technical and business stakeholders. Its aim is to build trust and AI -Ensure it takes into account diverse development approaches and all human values, is respectful model certification trend.

• Another notable trend is the rise of model certification frameworks to validate that AI systems meet standards of robustness, safety, privacy and security. For example, initiatives like theIEEE’s Certified Model Mark aims to standardize how models are tested and certified. This helps organizations benchmark and communicate how their AI conforms to technical and ethical benchmarks.

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AI Governance Market Opportunities

Solution & Services Segment

The solution and services segment is anticipated to hold the largest market share over the forecast period. Rapid adoption of AI technologies across various industries is driving the need for effective AI governance solutions and services. Key solution types include platform, software tools and modeling tools while major services include training, consulting, and integration & implementation. Many organizations are implementing dedicated AI governance platforms and tools to monitor AI systems, ensure accountability and address potential risks. This is expected to propel the growth of this segment during the analysis period.

Data Management Segment

With the growing volumes of data being used to train AI models, effective data management has become critical for AI governance. The data management segment is projected to witness significant growth going forward. Major challenges include data privacy, quality, access and labeling. Vendors are focusing on developing data management solutions to address these challenges. Solutions help organizations in collecting, preparing, annotating and monitoring data in accordance with governance policies. This is fueling the adoption of data management solutions and driving the growth of this promising segment.

Key Market Takeaways

• The global AI governance market size is anticipated to reach USD 131.9 Billion by 2030, expanding at a compound annual growth rate (CAGR) of 46.60% during the forecast period. Rapid digital transformation across industries and increasing complexity of AI systems are propelling the need for improved accountability and governance of AI technologies.

• By component, the solution segment is expected to dominate the market. Wide availability of dedicated platforms, tools and software for functions including model monitoring, impact assessment and policy management is driving higher adoption of solutions.

• In terms of development, the cloud segment is projected to witness faster growth over the forecast period. Cloud-based AI governance solutions offer advantages like scalability, on-demand access and lower upfront costs. This is making cloud apreferred option for many organizations.

• Regionally, North America is anticipated to dominate the global market owing to early adoption of advanced technologies and presence of numerous AI governance vendors in the region.

Competitor Insights:

IBM Corporation

Anthropic

H2O.ai

SAP

FICO

ZestFinance

Pymetrics

AIBrain

Trace3

Tractable

Paige.ai

Anthropic

Recent Developments in AI Governance Market

New Funding and Investments Pour Into AI Safety Startups

In June 2023, Anthropic raised $225 million in a Series C funding round led by Coatue and D1 Capital. This round valued the AI safety startup at $3.2 billion, reflecting growing interest from investors in addressing risks from advanced artificial intelligence. Anthropic plans to use the new capital to expand its team of AI safety researchers and accelerate development of techniques like Constitutional AI aimed at ensuring AI systems behave helpfully, harmlessly, and honestly.

Other AI safety startups also saw significant investments over the summer. In July, Orbital raised $100 million led by Andreessen Horowitz to develop new approaches for integrating human values into advanced AI. July also saw OpenAI spin out as an independent company with $1 billion in funding, allowing it to expand its AI safety work separately from Microsoft. These large funding rounds show that AI governance has become a major focus area for investors as capabilities in AI continue advancing rapidly.

New Government Initiatives Focus on AI Accountability and Impact Assessment

Several governments rolled out new policies and initiatives around AI governance over the last year. In June 2023, the US announced a National AI Initiative aimed at coordinating federal AI R&D spending and developing new techniques for ensuring the technology is developed and applied responsibly. A key part of the initiative involves standards for impact assessments to understand how AI systems might affect jobs, income inequality, and other societal issues.

The UK also launched a new AI auditing framework in July 2023 requiring public sector AI systems above a certain risk threshold to undergo annual audits examining issues like data quality, system documentation, bias testing results, and incident reporting processes. The audits are designed to ensure accountability and increase oversight of high-risk AI uses. Canada followed up in August with plans to propose legislation for AI system “safety ratings” meant to provide transparency into a system’s capabilities and limitations.

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