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AI Governance Market worth $5,776.0 million by 2029- Exclusive Report by MarketsandMarkets™

350 – Tables 50 - Figures450 – Pages 350 – Tables50 - Figures 450 – Pages Download PDF Brochure @   https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=176187291 Scope of the Report Regulatory pressure and demands for compliance are driving the AI Governance Market as governments around the world roll out tougher regulations related to AI. For example, the European Union's AI Act had subjected risk assessments and compliance audits to AI systems, particularly in high-risk...
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Regulatory pressure and demands for compliance are driving the AI Governance Market as governments around the world roll out tougher regulations related to AI. For example, the European Union's AI Act had subjected risk assessments and compliance audits to AI systems, particularly in high-risk sectors like health and finance, thereby increasing demand for the governance framework. Organizations also run the risk of facing reputational damages linked with prejudiced or harmful AI output. A notable example is the controversy caused by OpenAI GPT models, which flagged misinformation and biased data concerns, making businesses adopt robust AI guard rails. On similar note, Amazon's discontinuation of its biased AI recruiting tool demonstrate the reputational and financial risks of ungoverned AI. Another major reason for market expansion is the uptick in AI adoption across highly regulated industries, especially BFSI and healthcare. Industries operating in these sectors are under immense regulatory pressure to comply with dynamic regulations, leading to increased affinity towards AI governance tools.

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Data governance tools are poised to account for the largest market share in the AI Governance Market, as these tools help an organization track data quality, provenance, and bias within AI development training data. This is important in order to prevent bias results being generated from AI systems. For example, data governance tools may apply profiling techniques to the dataset in order to ensure fairness, and also put in place data lineage to indicate potential problems with data sourcing. As an increasing number of AI regulations call for documentation, tracking and record keeping especially on the data that feeds AI systems, data governance has become paramount. Data governance also assists enterprises in compliance with regulations through robust AI data traceability and accuracy. Additionally, the metadata repository feature in data governance tools offer centralized catalogs and controls of metadata for data visibility across an organization to ensure trustworthy and responsible AI implementation.

Software & technology providers are poised to become the fastest growing end user segment in the AI Governance Market, buoyed by rapid adoption of AI governance tools to make their AI systems trustworthy and ethical. The rising regulatory scrutiny and the expanding reach of data privacy laws like GDPR and CCPA has also accelerated governance frameworks being adopted across such players. For instance, Microsoft has created an internal AI ethics working group to implement strong ethical guardrails across its AI offerings. On a similar note, Google has formed AI governance framework for developing fair, explainable, and ethical AI solutions. There are also expectations from stakeholders who demand that technology companies create AI responsibly. With AI regulations likely to disrupt every software vendor, incorporating ethical norms and regulation is now of extraordinary importance for technology businesses to maintain the brand's trust and growth.

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North America has emerged as the largest regional market for AI government adoption. Federal funding on AI governance in North America crossed USD 1 billion in 2023, indicating a growing interest in responsible AI research. Industries with strict regulations such as healthcare and banking are leading in the implementation of governance, with 45% of healthcare providers mentioning regulatory compliance as a key business requirement. Businesses are forced to implement governance frameworks due to rising regulatory requirements like NIST's AI Risk Management Framework and the California Consumer Privacy Act (CCPA). More than half of businesses expect more stringent AI rules in the next five years, with 62% citing data privacy compliance as a main factor for implementing governance. Also important is consumer confidence, as 78% of American consumers favor brands that utilize ethical AI. Businesses such as Google and Microsoft are implementing governance to guarantee transparency and establish trust. Additionally, organizations are prioritizing fairness in their AI systems and have turned to tools like IBM's AI Fairness 360 to address the need to mitigate AI bias, with 56% of businesses doing so. Moreover, financial institutions are particularly focused on risk management, giving priority to governance for addressing AI-related risks.

The major players in the AI Governance Market include Microsoft (US), IBM (US), SAS Institute (US), DataRobot (UK), and Dataiku (US), along with SMEs and startups such as Fiddler AI (US), 2021.AI ( Denmark ), Monitaur (US), Credo AI (US), and Fairly AI ( Canada ).

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