What is an AI Policy?
An AI policy is a formalized set of principles, rules, and procedures that guide the responsible use of artificial intelligence technologies within an organization. It governs how AI systems, including generative AI models like ChatGPT, are developed, deployed, managed, and evaluated. The policy ensures that the use of AI aligns with the organization’s values, legal requirements, and societal expectations, safeguarding against potential risks such as inaccuracies, bias, security breaches, and misuse.
Beyond just internal documentation, a strong AI policy positions organizations to participate in broader societal discussions about the safe and ethical use of AI technology. It demonstrates a commitment to responsible AI development and responsible innovation.
Why is an AI Policy Important?
Organizations increasingly rely on AI tools and algorithms to drive innovation, enhance decision-making, and optimize operations. However, without a clear AI policy, the use of artificial intelligence can expose companies to significant risks, including:
- Data privacy violations
- Intellectual property theft
- Ethical breaches
- Non-compliance with applicable laws and executive orders
- Cybersecurity vulnerabilities
- Loss of public trust and reputational damage
- Financial penalties from regulatory bodies
An AI policy acts as a critical safeguard, ensuring that the organization’s adoption of AI technology is safe, ethical, and legally compliant. In sectors like healthcare, finance, and government contracting, adherence to strict security policy standards is particularly crucial.
Moreover, with increasing regulatory focus, such as the guidelines from the White House and states like New York, organizations are expected to not only comply but also foster transparency, accountability, and risk awareness in their use of AI.
How Does an AI Policy Relate to AI Governance?
AI governance encompasses the broader strategic framework that manages the risks and opportunities associated with AI development and deployment. An AI policy is a core operational element of AI governance, translating high-level governance principles into actionable guidelines. It supports broader goals like:
- Ensuring responsible AI practices
- Promoting national security interests
- Addressing civil society concerns
- Enhancing collaboration with academia, federal agencies, and policymakers
- Aligning internal operations with external technology policy initiatives
A strong governance framework, paired with a well-crafted AI policy, allows organizations to proactively manage AI risks, ensure effective risk management frameworks, and demonstrate leadership in responsible AI development.
What is Needed in an AI Policy?
A comprehensive AI policy should include the following components:
General Policies for AI Use
- Define acceptable use cases for AI systems, including language models, chatbots, and generative artificial intelligence applications.
- Establish standards for data protection, information security, and safeguarding intellectual property.
- Set protocols for human review of ai-generated content, including disclosures about the use of AI tools in creating outputs.
- Ensure that outputs are audited for inaccuracies, bias, and potential risks.
Prohibited Use Policies
- Prohibit any use of AI technology that infringes on privacy rights, promotes misinformation, or discriminates unlawfully.
- Restrict the use of AI models for unapproved surveillance or profiling activities.
- Ban unauthorized procurement or use of external generative AI tools without appropriate vetting.
- Prevent the deployment of AI in ways that could jeopardize national security or critical infrastructure.
Incident Reporting Policies
- Require immediate reporting of any breach, misuse, or malfunction involving AI systems.
- Outline reporting mechanisms and responsible parties for incident escalation.
- Include guidance for cooperation with regulatory agencies and relevant stakeholders.
- Define clear metrics for incident impact assessment and lessons learned protocols.
How to Develop an AI Policy
Creating a robust AI policy involves a methodical, collaborative process:
1. Establish Ownership
Assign a cross-functional team responsible for policy development and oversight, involving IT, legal, HR, risk management, cybersecurity, and relevant business units. Ownership structures should align with broader governance frameworks.
2. Define Policy Objectives
Clarify what the organization aims to achieve with the use of AI: innovation, operational efficiency, enhanced service delivery, risk mitigation, or regulatory compliance. Tailor objectives to the organization’s industry and specific operational needs.
3. Determine the Principles and Values
Ground the policy in ethical principles emphasizing:
- Fairness
- Accountability
- Transparency
- Respect for human autonomy and dignity
These principles should align with evolving standards from the National Institute of Standards and Technology (NIST) and global best practices.
4. Evaluate Legal and Regulatory Compliance
Ensure alignment with:
- U.S. Executive Orders on AI
- Local regulations such as those emerging in New York
- Global standards from GDPR, ISO, and OECD
- Emerging compliance frameworks tied to national security concerns
Ongoing monitoring of the legal landscape is crucial to maintain compliance.
5. Identify AI Uses and Risks
Create a comprehensive inventory of existing and planned AI applications. Conduct risk assessments focusing on:
- Bias and discrimination risks
- Model transparency and explainability challenges
- Intellectual property concerns
- Cybersecurity vulnerabilities
- Risks to public trust and organizational reputation
6. Determine Accountability and Governance Processes
Assign clear roles for:
- Data owners
- Model developers
- Product managers
- Risk and compliance officers
Define decision rights and responsibilities to ensure strong accountability.
7. Build in Continuous Monitoring and Evaluation of Policy
Implement mechanisms for regular policy audits and updates. Use KPIs to measure policy effectiveness and maturity. Stay informed about:
- Advances in generative artificial intelligence
- Regulatory updates
- New security threats
Continuous monitoring should integrate feedback loops for internal stakeholders and external partners.
8. Enable the Organization on the AI Policy
Conduct comprehensive enablement initiatives, including:
- Role-based training on responsible use of AI
- Awareness campaigns on data privacy and security policy
- Simulations and tabletop exercises on incident response
- Leadership briefings on the evolving AI landscape and roadmaps for policy evolution
This ensures that fostering a responsible AI culture is embedded across the enterprise.
Conclusion
In the era of generative artificial intelligence, establishing a comprehensive AI policy is no longer optional—it is a fundamental requirement for sustainable innovation. An effective policy protects company data, secures public trust, supports compliance with applicable laws, and builds resilience against potential risks.
Organizations that take a proactive approach to AI governance—incorporating insights from NIST, academia, industry, and civil society—will be best positioned to lead in an AI-driven future, balancing innovation with ethical responsibility.
About WitnessAI
WitnessAI enables safe and effective adoption of enterprise AI, through security and governance guardrails for public and private LLMs. The WitnessAI Secure AI Enablement Platform provides visibility of employee AI use, control of that use via AI-oriented policy, and protection of that use via data and topic security. Learn more at witness.ai.