More than 80% of companies have adopted artificial intelligence (AI) in some way, and 83% of those companies consider AI a top priority in their business strategy. AI is becoming more integrated into business processes every day, and IT, security, and compliance professionals are on the front lines of managing this dramatic shift. But as AI usage grows, so do the risks—whether it’s data privacy concerns, potential bias, or navigating complex regulations.

That’s why having a clear, comprehensive AI policy is essential to stay ahead of these challenges. If you’re tasked with drafting an AI policy for your organization and don’t know where to begin, this guide will help you get started. We’ll break down what needs to be included, why it’s important, and how to tailor your policy to fit your organization’s unique needs.

What is an Artificial Intelligence policy and why do you need one?

A corporate AI policy is something every company should have in place, even if you don’t officially use or develop AI tools.

Why? Because chances are, your team is already using AI in some form — whether it’s tools like ChatGPT, automated decision-making systems, predictive analytics, or something else. Microsoft found that 75% of workers are using AI, yet 77% of them admit they’re unclear on how to use it effectively. AI is not just present in your workplace, it’s likely introducing potential risks that you may not be prepared to handle.

Think of a corporate AI policy as a roadmap that guides how your company adopts and uses AI technologies, making sure everything stays aligned with laws, ethical standards, and your organization’s core values. This policy does more than just set up guardrails — it actively helps you leverage the benefits of AI while avoiding pitfalls like bias, data breaches, or legal complications. It gives you a clear AI governance framework for making ethical decisions and proactively addressing challenges that AI brings to the table.

Let’s explore four key reasons why your business needs a formal AI policy:

1. Compliance with laws and regulations

AI isn’t a lawless frontier — there are increasing regulations surrounding its use, particularly when it comes to data privacy, intellectual property, and consumer protections. Without a clear AI policy in place, your company could inadvertently violate these laws, resulting in hefty penalties or potential lawsuits. A corporate AI policy helps ensure that your AI practices stay within legal boundaries, protecting your company from compliance risks as regulations like GDPR, HIPAA, or emerging AI-specific legislation come into play.

2. Protecting data privacy

AI systems, especially generative AI tools, often rely on vast amounts of data to function, and this data can include sensitive information. Without proper controls, employees may input proprietary or personal data into AI algorithms, exposing it to unauthorized access or data breaches. In fact, a 2024 study revealed that 38% of AI-using employees admit to sharing sensitive work data with AI tools.

A robust AI policy sets strict guidelines on how data is collected, stored, shared, and processed, ensuring that customer and employee privacy remains protected. This is a critical step in reducing the risk of accidental data exposure or breaches.

3. Mitigating bias and discrimination

AI models are only as good as the data they’re trained on. If the training data is biased, the AI's output may also be biased, leading to unintended discrimination based on characteristics like race, gender, or age. A corporate AI policy can enforce regular audits and bias reviews of AI-generated content, ensuring fairness and inclusivity. This helps your company avoid reputational damage and ensures that AI doesn’t unintentionally perpetuate harmful stereotypes or discriminatory practices.

4. Ensuring ethical and responsible use of AI

AI has immense potential, but it also comes with risks. Whether it’s producing inaccurate content or replacing human decision making inappropriately, AI can lead to ethical challenges. A corporate AI policy provides a clear framework for ethical AI use, guiding how AI is deployed and ensuring it enhances rather than harms your workforce and reputation. It sets boundaries for AI’s role in decision-making, protecting your organization from reputational harm or unethical practices.

What’s included in a corporate AI policy?

If you’re sitting down to write an AI policy for your organization, you might feel unsure of where to start or what exactly needs to be included. AI is evolving rapidly, and it can be challenging to know how to structure a policy that addresses the risks and responsibilities involved. Let’s dive into what should be included so you can create an effective framework for responsible AI use within your organization.

AI risk management

Promoting responsible AI usage starts with a solid risk management framework. Your policy should outline how your organization will identify, monitor, and mitigate risks associated with AI. This includes ensuring that AI systems are regularly tested for accuracy and reliability, and that any risks — including biases, algorithmic errors, or security vulnerabilities — are proactively addressed. By setting up a risk management plan, your organization can avoid unintended consequences and ensure AI remains safe and beneficial.

Data privacy and security

Given that AI often relies on vast amounts of data, it’s critical to establish clear measures for how data is collected, stored, and used. Your AI policy should ensure compliance with data protection laws such as GDPR and CCPA, which govern how personal data must be handled. It’s also essential to define security protocols that safeguard against unauthorized access and data breaches, such as encryption, access control, and data anonymization. These measures protect sensitive customer or employee information while maintaining AI system integrity.

Regulatory and security compliance

AI technologies are subject to various regulations, depending on your industry and location. Your AI policy should verify that AI-related activities comply with relevant laws and security standards. This might include adherence to frameworks like HIPAA, PCI DSS, or specific AI legislation (such as the upcoming EU Artificial Intelligence Act). By aligning your AI practices with these standards, you minimize the risk of legal penalties and ensure that your systems are operating within ethical and regulatory boundaries.

Transparency and ethics

Transparency is a cornerstone of ethical AI use. Your AI policy should promote clear guidelines on the acceptable and unacceptable use of artificial intelligence within your organization. This includes detailing how AI algorithms make decisions, especially in areas where AI directly impacts individuals, such as hiring decisions. The policy should also address your efforts to counteract AI bias and ensure that AI models are regularly reviewed for fairness and inclusivity.

Acceptable use of AI

To ensure responsible AI deployment, your policy should specify the acceptable use cases for AI within your organization. Clearly define the roles AI will play, whether it’s in customer service, data analysis, or automated decision-making, and provide examples of tasks AI should not perform. For example, AI augmenting rather than replacing human decisions in areas like legal matters or employee performance evaluations.

List of approved AI tools

To prevent unregulated AI usage, include a list of approved AI tools and technologies in your policy. This helps ensure that employees are using vetted, secure tools that comply with the organization’s data privacy and ethical standards. You should also work with stakeholders across your IT and security teams to define a process for evaluating and approving new AI tools, ensuring that they meet the organization's requirements for security, bias mitigation, and compliance.

Policy review timeline

AI technology evolves rapidly, and so should your AI policy. Define a clear timeline for reviewing and updating the policy — bi-annual reviews are a good starting point, especially if your organization is heavily adopting AI. Appoint a policy owner or committee responsible for ensuring the policy remains relevant and up to date with both technological advancements and regulatory changes. Regular reviews ensure that your AI practices adapt to and account for new risks, laws, and opportunities.

Tips for tailoring your AI policy to support your organization

When it comes to writing an AI policy for your company, there’s no one-size-fits-all approach. Your policy should reflect how your organization plans to use AI, ensure your systems and personnel are able to implement AI tools responsibly, and make sure AI use aligns with your specific business objectives.

Let’s examine how you can tailor your AI policy to support your company’s unique needs.

Align your AI policy with business objectives

It’s essential to start by making sure that your AI policy supports your company’s overall business strategy. AI isn’t just a tool for IT or data science — it can provide real value across departments, especially in cybersecurity, risk, and compliance.

To do this effectively, ensure there’s collaboration between departments like IT, cybersecurity, risk management, and compliance. This helps AI initiatives get integrated smoothly across the organization and ensures they serve a purpose beyond just automation. Look for areas where AI can add value, such as automating repetitive tasks, enhancing threat detection, or accelerating incident response times.

Define clear goals, such as improving threat detection rates or reducing manual effort for compliance reporting. Metrics like the number of incidents detected or hours saved on compliance tasks will help you track AI’s impact on your overall security and compliance operations.

Ensure your systems and personnel can successfully adopt AI

When writing your AI policy, it's essential to plan for both your systems and your personnel to adopt AI technologies successfully. A well-crafted AI policy should go beyond assessing readiness — it should actively set the stage for successful AI integration by addressing the infrastructure and human resources needed to use AI effectively.

Here’s how to shape your AI policy to ensure smooth adoption across the organization:

• Data readiness: AI’s success hinges on high-quality data, and your policy should establish clear guidelines for data preparation and maintenance. Define how data will be cleaned, organized, and continuously updated to ensure relevance and accuracy. This includes setting up processes for data audits and regulatory compliance. Incorporate practices that maintain data quality over time to ensure your AI models are always working with reliable, compliant data.
• Technical infrastructure: Your AI policy should outline how you’ll ensure your technical infrastructure is prepared for AI. AI tools often demand significant processing power, memory, and storage, so make sure your hardware and software are up to the task. Include provisions in your policy that define how to regularly upgrade hardware, ensure compatibility with AI tools, and optimize network performance to handle the increased data flows AI often requires. The policy should also address scalability to accommodate future AI growth without disrupting operations.
• Network architecture: AI can dramatically increase data traffic, so it’s crucial to ensure your network infrastructure can support these demands. Your policy should detail how bandwidth will be allocated to AI systems and how network architecture will be optimized to prevent slowdowns or disruptions. Include security measures to protect data as it moves through the network, ensuring that AI doesn’t introduce new vulnerabilities or bottlenecks.
• Security framework integration: AI should strengthen, not compromise, your existing security framework. Your AI policy should specify how AI tools will be integrated into your current security protocols, such as how AI will interact with firewalls, encryption, and intrusion detection systems. Establish how AI will complement your overall risk management strategy, ensuring any AI-driven processes align with your security objectives and enhance your organization’s defenses without creating new risks.

Train employees on responsible AI use

AI is only as powerful as the people behind it, yet fewer than half of AI users are properly trained on security and privacy risks. Your AI policy must include plans for training and upskilling your workforce.

Define how employees will be trained to use AI tools effectively and in compliance with your company’s policies. This training should emphasize not only the tools themselves but also the ethical and responsible use of AI in daily tasks.

Employees should also be trained on the potential risks associated with AI, such as bias in decision-making, new security vulnerabilities, or privacy issues. Training should include how to identify and mitigate these risks, especially when handling sensitive data. Lastly, employees need to know exactly what data they can and cannot input into AI systems and tools. Make sure they’re trained on data privacy regulations and understand under what circumstances data can be shared with AI tools without introducing unnecessary risks.

By including these elements in your AI policy, you'll not only ensure that your organization is ready for AI adoption but also actively prepare your systems and personnel to use the technology effectively.

3 real-world AI policy examples to use for inspiration

One of the best ways to get started writing your AI policy is by learning from real-world examples. These policy documents from Salesforce, WIRED, and Best Buy offer practical inspiration and takeaways, from how companies can ensure ethical AI deployment to the way they promote transparency around AI usage.

Salesforce’s AI Acceptable Use Policy

Salesforce’s AI Acceptable Use Policy is designed to ensure that their AI tools, including generative AI products, are used ethically and responsibly by their customers. The policy does an excellent job of setting clear boundaries around what Salesforce’s AI can and cannot be used for, such as automating legal decisions.

Organizations should similarly outline approved and prohibited AI use cases to prevent misuse. When writing your own policy, it’s important to establish where human oversight is necessary to mitigate AI risks, particularly in sensitive areas like hiring, healthcare, legal advice, or financial services.

WIRED’s Generative Artificial Intelligence Policy

WIRED’s AI policy is a great example of how policies can reinforce the organization’s mission and strategic objectives. Their policy highlights the importance of human oversight, transparency, and ethical use, setting clear boundaries for when AI can be used and ensuring that creative and editorial integrity are maintained.

For example, it clarifies that WIRED does not publish AI-generated text or use AI tools for writing or editing stories, except when the AI’s involvement is the focus of the article. It heavily emphasizes the company’s value of human creativity and critical thinking, explaining that editorial judgment, such as determining what’s relevant or original, is something only a human can perform effectively.

Best Buy’s Generative AI Policy

Best Buy’s approach is a useful model for organizations that want to integrate AI responsibly while maintaining trust and transparency. For example, their policy stipulates that all AI-generated content is clearly labeled. Blog posts created with AI assistance are credited as “Best Buy (assisted with AI)” to maintain transparency with customers about how content is produced. They also specify that human writers and editors review, fact-check, and revise all AI-generated content before it goes live, demonstrating a commitment to providing customers with reliable information.