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IAPP AI Governance in Practice Report
webPublished by the International Association of Privacy Professionals (IAPP), this report is aimed at practitioners implementing AI governance and is useful for understanding industry-level governance trends rather than technical AI safety research.
Metadata
Importance: 52/100organizational reportreference
Summary
The IAPP AI Governance in Practice Report surveys how organizations are operationalizing AI governance frameworks, covering policy implementation, risk management, and compliance practices. It provides practical insights into how privacy and data professionals are addressing AI oversight challenges across industries. The report serves as a benchmark for understanding the current state of enterprise AI governance adoption.
Key Points
- •Surveys real-world implementation of AI governance policies across diverse organizations and sectors
- •Examines how privacy, legal, and compliance teams are structuring AI oversight roles and responsibilities
- •Highlights gaps between stated AI governance commitments and actual operational practices
- •Covers risk assessment frameworks, accountability mechanisms, and regulatory compliance strategies for AI deployment
- •Provides benchmarking data useful for organizations building or maturing their own AI governance programs
Cited by 2 pages
| Page | Type | Quality |
|---|---|---|
| AI Risk Critical Uncertainties Model | Crux | 71.0 |
| Institutional AI Adaptation Speed Model | Analysis | 59.0 |
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REPORT
Published3 June 2024
[View report](https://assets.contentstack.io/v3/assets/bltd4dd5b2d705252bc/blt99a18c62ab0b92a7/ai_governance_in_practice_report_2024.pdf)
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### Contributors:
Ashley Casovan
Managing Director, AI Governance Center
IAPP
Joe Jones
Research and Insights Director
IAPP
Uzma Chaudhry
CIPP/E
Former AI Governance Center Fellow
ATI
**Additional Insights**
- [At-a-Glance: AI Governance in Practice](https://iapp.org/resources/article/at-a-glance-ai-governance-in-practice-report) (Infographic)
#### Recent and rapidly advancing breakthroughs in machine learning technology have forever transformed the landscape of AI.
AI systems have become powerful engines capable of autonomous learning across vast swaths of information and generating entirely new data. As a result, society is in the midst of significant disruption with the surge in AI sophistication and the emergence of a new era of technological innovation.
As businesses grapple with a future in which the boundaries of AI only continue to expand, their leaders face the responsibility of managing the various risks and harms of AI, so its benefits can be realized in a safe and responsible manner.
Critically, these benefits are accompanied by serious considerations and concerns about the safety of this technology and the potential for it to disrupt the world and negatively impact individuals when left unchecked. Confusion about how the technology works, the introduction and proliferation of bias in algorithms, dissemination of misinformation, and privacy rights violations represent only a sliver of the potential risks.
The practice of AI governance is designed to tackle these issues. It encompasses the growing combination of principles, laws, policies, processes, standards, frameworks, industry best practices and other tools incorporated across the design, development, deployment and use of AI.
While relatively new, the field of AI governance is maturing, with government authorities around the world beginning to develop targeted regulatory requirements and governance experts supporting the creation of accepted principles, such as the Organisation for Economic Co-Operation and Development's [AI Principles](https://oecd.ai/en/ai-principles), emerging best practices and tools for various uses of AI in different domains.
There are many challenges and potential solutions for AI governance, each with unique proximity and significance based on an organization's role, footprint, broader risk- governance profile and maturity. This report aims to inform the growing, increasingly empowered and increasingly important community of AI governance professionals about the most common and significant challenges to be aware of when building and maturing an AI governance program. It offers actionable, real-world insights into applicable law and policy, a variety of governance approaches, and tools used to manage risk. Indeed, some of the challenges to AI governance overlap an
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