Implementing Data Governance in the Age of AI and Machine Learning

How organizations can implement responsible data governance for AI and machine learning models.

Artificial Intelligence (AI) and Machine learning (ML) are reshaping business decision-making across industry domains. However, industry concerns around factors like accountability and transparency are top of mind.


Recent findings have revealed hidden biases and insufficient oversight in the development of AI models and ML architectures. A responsible data/model governance framework can provide sufficient oversight and promote accountability to shift the existing paradigm.


This eBook highlights the costs of biased AI models – and how organizations can design and implement a responsible data governance framework.

In downloading this eBook, you will learn more about:
  • The business costs of using biased data and inaccurate AI models
  • How organizations can implement a responsible data governance framework
  • How government agencies can incentivize accountability through proper policies
  • How Onix can help you implement a robust data/model governance framework

Did you know?

65% of Business and IT professionals believe their organizations have data bias in their AI models.

Between 40-80% of mortgage applicants of color are more likely to be disapproved due to biased AI algorithms.

80% of survey respondents are prioritizing data security and governance for 2024.

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