How to Create an AI Policy

In “How to Create an AI Council,” I outlined a three-step framework that any organization, regardless of size, can use to figure out their AI roadmap.

To review, here it is:

Three-Step Framework

1. Create an AI Council
2. Create an AI Policy
3. Create an AI Use Case

It’s deceptively simple, but that’s the point. Developing your AI roadmap doesn’t need to be complicated.

It just needs to be structured.

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.

The important thing is that your goals are specific to your organizational needs.

Additionally, each organization will use different AI tools. If you’re an enterprise creating enterprise AI solutions and workflows, your AI policy will be robust, involving significant input from your legal department and detailed decisions around data governance.

For the purposes of these suggestions, though, I’m going to assume that your business isn’t using enterprise-level AI solutions like those from Moderna or PwC.

Instead, you might be using a combination of LLMs like ChatGPT, Claude, or Gemini, along with third-party AI tools like Jasper.ai, MarketMuse, or Drift.

Simple AI Policy Framework

1. Ethical Guidelines

Establish clear principles to ensure AI is used responsibly.

Guidelines:

• Fairness: AI should treat everyone equally and avoid biases.
• Transparency: Be open about when and how AI is used.
• Privacy: Protect personal data and respect user privacy.

Examples:

• Regularly check AI systems for biases.
• Inform users when they are interacting with AI.
• Anonymize personal data used by AI.

2. Data Governance and Compliance

Set rules for handling data securely and legally.

Guidelines:

• Data Collection: Only collect data you need.
• Data Storage: Store data securely.
• Compliance: Follow relevant data protection laws (e.g., GDPR, CCPA).

Examples:

• Encrypt data shared with third-party AI solutions.
• Implement a data retention policy to securely delete old data.
• Ensure data practices comply with international laws.

3. Transparency and Explainability

Make AI operations clear and understandable.

Guidelines:

• Transparency: Clearly explain AI use to users.
• Explainability: Make AI decisions understandable.

Examples:

• Provide documentation that explains AI decisions.
• Create transparency reports on AI usage within the organization.
• Use simple language to describe how AI works to stakeholders.

4. Human Oversight

Ensure human review of AI decisions.

Guidelines:

• Review: Regularly evaluate AI decisions with human oversight.
• Accountability: Allow users to request human review of AI outcomes.

Examples:

• Set up a review committee to oversee critical AI decisions.
• Allow users to flag AI decisions for human review.
• Ensure human experts check AI outcomes in sensitive areas like hiring and finance.

5. Permitted Use Cases

Define where and how AI can be used.

Guidelines:

• Scope: Specify areas where AI can be applied.
• Restrictions: Identify tasks AI should not handle.

Examples:

• Use AI for customer service but not for making final hiring decisions.
• Employ AI for routine maintenance predictions but restrict its use in critical safety decisions.
• Allow AI to assist in drafting emails but prohibit its use in creating legal documents.

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.

Remember, though, that creating an AI policy is not a static document. Instead, it’s a living document that should evolve as your organization and technology landscape change.

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