How to Create an AI Policy

Once you’ve appointed your AI Council, the second step in the framework is to create an AI policy.

Your AI policy, which is created by your AI Council, acts as a set of foundational guidelines, ensuring that all your AI initiatives are implemented ethically, transparently, and in alignment with your organization’s goals.

Each organization’s goals are going to be different, with some looking for efficiency gains, others looking for cost savings, and still others aiming for different outcomes altogether (like improved customer experience (CX) or even improved user experience (UX).

The important thing is that your goals are specific to your organizational needs—and mapped to your business’s objectives.

There needs to be a real business need to use AI in the first place, or else you’ll find yourself engaging in Random Acts of AI Adoption.

Additionally, each organization will use different AI tools, therefore, tool usage will be governed differently across businesses.

If you’re a large enterprise, your AI policy will be robust, involving significant input from your legal department and detailed decisions will need to be made around data governance and privacy.

(For enterprise-level adoption insights, see these examples from Moderna and PwC.)

If you’re a smaller organization, your AI policy might be leaner.

Regardless of where you fall, thouhg, here’s a basic overview of the twenty-two items that you should consider including in your AI Policy, with a description of what each item is for.

You may have more to add, or less—this isn’t meant to be an exhaustive list.

However, there’s lots of evidence at this point, both anecdotal and otherwise, that these items will get you moving in the right direction.

Simple AI Policy Framework

1. Purpose: Establishes the guidelines and best practices for the responsible and ethical use of AI within the organization.
2. Scope: Defines the application of the policy to all employees, contractors, and partners who interact with AI systems.
3. Responsible AI Use: Emphasizes the ethical use of AI systems, requiring actions that avoid harm and respect privacy and compliance.
4. Compliance with Laws and Regulations: Ensures AI systems are used in alignment with applicable data protection, privacy, and intellectual property laws.
5. Transparency: Requires clear communication when AI has been used in content creation, with transparency statements for stakeholders.
6. Tool Selection: Lists approved AI tools for use within the company and prohibits unauthorized tool usage without written approval.
7. Accountability: Holds humans responsible for AI outputs, maintaining that AI is an assistant and not a replacement for human judgment.
8. Restricted Use Cases: Specifies situations where AI is not to be used, such as legal document drafting or sensitive communications.
9. Addressing Bias: Ensures content created with AI is reviewed for bias and promotes inclusivity.
10. Privacy: Requires the protection of customer data and intellectual property, allowing only approved AI tools with reliable privacy policies.
11. Security: Emphasizes the importance of using secure AI tools to prevent cyber-attacks and data breaches.
12. Ethical Considerations: Outlines ethical standards to prevent misuse of AI, including impersonation, copyright risks, and manipulation.
13. Training Employees on AI Usage: Mandates regular training for employees on the technical and ethical use of AI.
14. Human-AI Collaboration: Reinforces the principle that AI should support human decision-making, not replace it, with human oversight.
15. 3rd-Party Services: Ensures that third-party AI providers adhere to the same ethical and legal standards as the organization.
16.  Implementation and Monitoring: Establishes an AI Lead or AI Council to oversee policy implementation and compliance.
17. Periodic Reviews: Calls for regular reviews of AI usage to update the policy and address new risks.
18. Incident Reporting: Provides a system for reporting violations or concerns about AI use within the organization.
19. Enforcement: Outlines potential disciplinary actions for policy violations, emphasizing the importance of responsible AI use.
20. Policy Review: Ensures the policy is reviewed and updated annually or as needed based on technological and regulatory changes.
21. Effective Date: States when the policy becomes effective.
22. Acceptance: Requires employees to acknowledge and comply with the policy, with non-compliance potentially leading to disciplinary action.

Continue the AI Journey

Implementing an AI policy is a fundamental next step towards harnessing the power of artificial intelligence responsibly and effectively.

By focusing on clear ethical guidelines, robust data governance, transparency, human oversight, and defined use cases, you can ensure that AI applications align with your organization’s values and strategic goals.

It’s also important to note that your AI policy is not meant to be a static document. Instead, it’s meant to be a dynamic one that should evolve along with your AI strategy.

Regularly review and update your policy to keep pace with new developments and insights you’re learning along the way.

If you’re interested in an AI policy template that you can put into place immediately, reach out to us today.