What is an AI Policy (and Top Considerations)

Artificial intelligence (AI) is transforming how businesses operate from automating tasks to enhancing customer experiences and improving decision-making. This push comes with new risks: data misuse, compliance violations, algorithmic bias, and even reputational damage.

That’s where an AI policy comes in.

An AI policy is a formal framework that defines how your organization adopts, manages, and governs AI. It sets the rules of the road, ensuring AI initiatives align with business goals, comply with regulations, and operate responsibly. For mid-market organizations, developing an AI policy isn’t optional, it’s an essential step to unlocking AI’s potential without exposing the business to unnecessary risk.

Why Your Business Needs an AI Policy

AI adoption is growing rapidly, but many companies are moving faster than their policies. Without usage guardrails in place, AI projects can:

• Introduce hidden bias into decisions
• Create compliance or legal liabilities
• Expose sensitive data
• Reduce trust with customers, employees, and partners

An AI policy establishes clarity and confidence, so leadership teams can innovate without fear of unintended consequences.

Top Considerations When Developing an AI Policy

1. Align AI Use with Business Objectives
Your AI policy should connect directly to strategic priorities. Whether your focus is operational efficiency, customer experience, or risk management, the policy should define acceptable use cases and ensure they support measurable business outcomes.

2. Define Governance and Accountability
AI isn’t a “set and forget” solution. Assign ownership across IT, compliance, and business units for overseeing your organization’s AI systems. Policies should define:

• Who is accountable for AI decision-making
• How performance is monitored and validated
• Escalation processes if issues arise

3. Prioritize Data Protection and Security
AI depends on data, and mishandling that data is one of the biggest risks. Your AI policy should align with existing data governance frameworks and cover:

• Data collection, storage, and retention practices
• Access controls and usage permissions
• Compliance with industry regulations (GDPR, HIPAA, GLBA, etc.)

4. Address Ethics and Bias
Fairness and transparency are critical to building trust. Your AI policy should outline standards for testing algorithms, monitoring for potential bias, and providing explanations for automated outcomes when possible.

5. Support Training and Adoption
Employees will likely interact with AI day to day. Include guidance on training, awareness, and expectations to ensure AI is used consistently and responsibly across the organization.

6. Plan for Continuous Review
AI technologies change quickly. Policies must be dynamic, with regular review cycles to update guidelines as new tools, risks, and regulations are released.

Lay the Groundwork for Responsible AI

An AI policy is more than a compliance checklist. It’s a foundation for responsible innovation. By defining governance, security, ethical standards, and alignment with business goals, organizations can leverage AI with confidence.

At Thrive, we help businesses build AI strategies and policies that balance innovation with governance, so you can achieve growth while minimizing risk. Contact Thrive today if your organization is ready to take its first step in AI governance, our team can guide you through it.