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June 27, 20242 min read

Starting Your AI Governance Journey: A Comprehensive Guide

In today’s rapidly evolving technology landscape, Artificial Intelligence (AI) is becoming increasingly prominent in helping companies solve problems across all industries. AI can decide which ads a consumer sees or determine the approval of mortgage applications. These decisions have real-world consequences, making AI governance essential to prevent misuse and negative impacts on clients and consumers.

What is AI Governance?

AI Governance is the practice of establishing oversight, guardrails, and policies to ensure that AI models and systems are used ethically and without bias.

The core principles of AI governance include:

  1. Transparency: Increase trust in AI decision-making by documenting model architecture, algorithms, and decision criteria.
  2. Fairness and Ethics: Ensure AI models are unbiased across age, gender, ethnicity, religion, and disability by choosing appropriate datasets.
  3. Accountability: Appoint individuals responsible for training and validating models to prevent negative or unethical outcomes.
  4. Privacy Protection: Implement safeguards like encryption and access control to protect sensitive data used by AI models.

As AI adoption increases, so will the regulations and laws governing its use. Compliance is essential to avoid regulatory fines and maintain customer trust.

Steps to Govern AI within Your Organization

Establishing an AI governance framework begins with forming a dedicated committee to oversee AI governance. Key steps include:

  • Centralized Repository of AI Use Cases and Models: Facilitate easy access by keeping all AI use cases and models in one location.

  • Document AI Use Cases and Models: Record the business context, purpose, intended outcomes, and ethical considerations.

  • Perform Impact Assessments: Evaluate AI projects and systems for potential ethical or compliance risks.

  • Implement Privacy Protection Measures: Ensure safeguards are in place to protect sensitive data used by AI systems.

  • Continuous Validation of AI Performance: Regularly validate AI model performance to ensure it meets intended outcomes and minimizes risk.


Governing AI use cases is crucial for businesses utilizing AI. A centralized inventory of AI use cases and models enhances collaboration and prevents duplication of efforts. Policies that assess AI models ensure ethical usage and compliance with regulations.

Collibra AI Governance offers an out-of-the-box solution to streamline and accelerate your company’s AI governance program. Collibra’s straightforward registration process stores all AI use cases and models in a centralized location, making it easy for users to discover and understand existing models.

The AI governance module in Collibra assesses four critical aspects of AI use cases:

  • Business Context: Details on how the AI use case is utilized by the business.
  • Data and AI Model: Information on models and data used.
  • Legal and Ethics: Identification of potential legal and ethical risks.
  • Risk and Safeguards: Safeguards in place to mitigate risks.

In the dynamic field of data security, staying informed is key. Explore our Data Governance section and contact us today for expert guidance tailored to your needs. Let’s start governing AI together!