Responsible AI Use

Guiding Principles for Organisations

While individual responsibility is essential, organisations must establish proper frameworks and practices to govern the use of AI technologies across the enterprise. Effective AI governance at the organisational level helps mitigate risks and ensures alignment with company values.

This document outlines practical principles for responsible AI adoption at the organisational level, focusing on actionable steps rather than abstract concepts. Remember that AI tools are designed to meet the objectives of the companies that create them—not necessarily your organisation's specific needs and values.

Principle 01

Know Who Owns Your AI

  • Remember cloud AI reflects its creator's values.
  • Assess alignment with your organisation's needs.
  • Consider in-house solutions for sensitive tasks.
  • Create policies for approved tools.
  • Maintain a register of approved systems.
Principle 02

Implement Transparency

  • Document AI use in business processes.
  • Create disclaimers for AI content.
  • Disclose AI usage to stakeholders.
  • Maintain logs of AI decisions.
  • Ensure staff can explain AI assistance.
Principle 03

Clear Accountability

  • Designate roles for AI oversight.
  • Create reporting lines for incidents.
  • Include AI management in reviews.
  • Develop protocols for errors.
  • Maintain appropriate insurance.
Principle 04

Build Fairness

  • Require diversity impact assessments.
  • Test on diverse datasets first.
  • Regularly audit for bias.
  • Create feedback loops for bias reporting.
  • Include fairness metrics in evaluations.
Principle 05

Risk Management

  • Create a tiered risk system.
  • Develop protocols for high-risk apps.
  • Run scenario planning for failures.
  • Maintain backup systems.
  • Implement circuit breakers.
Principle 06

Require Auditability

  • Deploy systems with audit trails.
  • Establish regular audit intervals.
  • Document bases for decisions.
  • Maintain version control for models.
  • Create plain-language explanations.
Principle 07

Human Oversight

  • Define approval points for decisions.
  • Train staff in oversight techniques.
  • Rotate reviewers to prevent bias.
  • Evaluate quality of oversight.
  • Develop escalation procedures.
Principle 08

Train Your People

  • Provide role-specific AI literacy training.
  • Create communities of practice.
  • Develop career paths with AI skills.
  • Support ongoing education.
  • Reward responsible innovation.

Resources & Guides

Explore more materials for your AI journey.

Main Page Workshop Materials Individual Guide

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