What is AI Governance?

Artificial intelligence (AI) and large language models (LLMs) can transform the way that organizations operate. However, AI and LLMs are advancing far too quickly to leave your organization’s AI usage up to chance. You can harness AI and LLMs securely and responsibly without sacrificing velocity through an AI governance framework.

AI governance refers to the frameworks, policies, and practices that ensure that AI systems are developed, trained, and deployed in responsible, secure, and ethical ways. Through clear guidelines and mechanisms, your company can govern various aspects of AI in a clear and policy-driven way, with guard rails in place for access management, data governance, auditability, observability, data loss protection, algorithm accountability, and fairness and equity.

Components of an AI Governance Framework

The key components to an AI governance framework are:

  • Access Management: Granular access controls over AI vendors and models at a fine-grained level, all the way down to specific employees, services, and environments.
  • Data Governance: Protocols for data collection, storage, sharing, and usage to ensure the responsible and ethical handling of data used to train and operate AI systems.
  • Auditability: Logs of all interactions with AI vendors, letting you track, audit, and query as questions arise.
  • Observability: Metrics on your AI and LLM inputs and outputs, so that anomalies can be spotted in real time.
  • Data Loss Prevention: Define and block sensitive data for your organization from getting leaked to AI vendors.
  • Compliance: Simplify the compliance with the relevant requirements and regulations within your field as they apply to AI, including GDPR and HIPPA.
  • Algorithm Accountability: Identify and adopt transparent and explainable AI algorithms, enabling stakeholders to understand how recommendations are made and bias is prevented.

The Benefits of AI Governance

With a rigorous approach to AI governance defined upfront, your organization can benefit in many ways. You will foster trust with users, regulators, and stakeholders. You will mitigate the risks of potential data breaches. Finally, you will differentiate yourself as a secure, ethical leader in the space of AI.

On this website, we will seek to define this framework in a clear, data-driven way. We will identify the processes and mechanisms to drive these outcomes, and the vendors who can simplify the journey.