A step-by-step guide for middle-market businesses to create an effective AI policy
It’s easy to be dismayed by headlines about expensive Fortune 500 AI projects and think, “That’s out of reach for us” or “We don’t have the budget for that, so does that mean AI is out of reach for us?”
The good news: The answer is no—AI isn’t just for giants! The key is to start small and focus on quick wins. Getting a formal AI policy off the ground before you go all-in is often the biggest challenge, but it’s critical to manage risks and maximize benefits. This guide will help your business craft a policy and implement it (plus a sample policy template to get you started).
AI is the future, and innovation should be rewarded
First and foremost: an AI policy should encourage innovation (instead of creating fear around it). Employees who leverage AI for efficiency often hesitate to share success for fear of making themselves obsolete. 70% of workers using AI at work aren’t telling their boss—so even if you think your business is AI-free, it’s probably not.
- Create a culture of curiosity: Your team needs to know that you want to hear how they’re using AI—even in small use cases—and they’ll be rewarded for it, not punished.
- Establish guardrails, not roadblocks: Yes, you need a policy. But let’s not stifle creativity. “I have an AI idea, can we try it?” should be met with enthusiasm, not suspicion.
Technology capabilities separate high performing companies from their competitors, so innovation is critical for your growth. Encourage responsible use and make it clear that AI is about creating a better workplace instead of replacing jobs. This approach is key to an effective policy.
Step 1: Planning for a Corporate AI Policy
Before you get started, you need to get a lay of the land. Start by identifying repetitive, manual processes across your organization. You’ll be surprised at the AI opportunities hiding in plain sight. Next, you should:
- Inventory current and potential AI applications such as predictive analytics, LLMs, or customer service chatbots.
- Build a diverse AI steering committee. Don’t limit your AI team to executives and department heads. A successful committee includes people that are in the trenches, working with these processes every day. This group can explore and experiment with AI tools in a controlled setting.
Use the information you gather to guide your AI policy goals and objectives.
Step 2: The Key Components of an AI Policy
An effective AI policy needs to encourage responsible development while allowing for exploration and creativity. Let’s dive into the six key components you need to include.
Key #1: Objectives and Scope
The most important thing is to help your employees understand that AI is more than just ChatGPT. This section should define what is in scope for the policy, demonstrate the many ways they may encounter AI in the workplace, and set the foundation for the entire policy.
What it should include:
- Who this applies to: This often includes both internal teams and third parties. Monitoring data privacy compliance with your suppliers and vendors is critical to avoid data breaches.
- List of applicable AI tools and processes in scope
Key #2: Responsible Use
Establish ethical principles for how your team uses AI to ensure accuracy and prevent biased outputs. A staggering 74% of businesses using AI haven’t taken steps to reduce bias in their systems, putting their reputation and customers at risk—so take the extra steps to protect your business.
What it should include:
- Ethical responsibility expectations, including fairness, transparency, and accountability
- Data privacy and protection guidelines that outline what can and cannot be used in AI prompts to protect sensitive information
- Copyright and legal compliance with applicable laws and intellectual property rights.
Key #3: Acceptable Use
Define appropriate applications of AI systems, including suggested use cases that encourage employees to use the technology in new ways. Be sure to allow room for experimentation—excessively strict policies may hinder innovation and limit the potential benefits of AI technologies.
What it should include:
- Authorized use cases such as project management, administrative tasks, and data analysis.
- Authorized tools and platforms to demonstrate that the organization has vetted specific technologies and tools, and ways that AI can be used within the organization.
Key #4: Unacceptable Use
Use this section to define your business’s risk boundary and outline prohibited behaviors or use cases that could compromise your business.
What it should include:
- Examples of prohibited activities to provide clarity for employees, such as intellectual property infringement or personal use of company resources
- Industry-specific risks tailored to your company, such as overuse of LLMs in contract management
- Use plain language to ensure that staff understand the dos and don’ts.
Key #5: Security Guidelines
Provide rules and restrictions for using AI systems, including data usage, access controls, and compliance requirements.
What it should include:
- Data security measures, including encryption, access controls, and data retention policies.
- AI tool evaluation processes. This is especially important for organizations where departments can pilot and implement tools without IT’s approval. That’s common, but the policy needs to govern the decisions. Define clear questions and processes to evaluate every tool and vendor, such as:
- What processes will this tool be used for?
- How is our data being used as it incorporated into a shared model?
- Can this vendor contractually guarantee security and protection?
- System security protocols such as vulnerability assessments and incident response plans
- Data retention processes to outline how information is stored, where it’s stored, and for how long.
- For example, AI can save you time by recording, transcribing, and summarizing meetings –but that also means your every word is immortalized. So, do you want to save those recordings forever? 30 days? 90 days? An AI policy can help decide how long to keep these recordings and how they impact your meeting style.
Key #6: Policy Compliance
Policy compliance mechanisms ensure adherence to the AI policy, monitoring and enforcing compliance with established guidelines and requirements.
What it should include:
- Monitoring and auditing procedures to ensure compliance with policy guidelines.
- Reporting mechanisms: Establish channels for reporting policy violations, incidents, or concerns related to AI use.
- Enforcement measures and consequences for non-compliance with the AI policy, including disciplinary actions or termination.
Download Our AI Policy Template
We’ve created a sample AI policy template to make the process easier. Simply plug in your organization’s information and distribute it to your team to strengthen security.
Step 3: How to Enforce an AI Policy
Enforcing an AI policy requires thoughtful measures that balance oversight and collaboration. It involves a multi-pronged approach that combines education, technical controls, and accountability measures.
- Know what’s going on in your organization: With the right back-end security controls in place, IT can see who’s using AI tools like ChatGPT or CoPilot. The specific questions fed into AI remain private, but you can identify who’s using what and how often to monitor responsible practices.
- Leverage the people using AI: Don’t use the knowledge of who’s using AI as a big-brother discipline system. Those early adopters are your secret weapons to maximizing AI, and should be amplified. Reach out and say “hey, we see you’re using this. Do you want to be part of the committee that actually helps guide organizational strategy around this?”
- Enforce appropriately and reward creativity: Celebrate those who think outside the box to prioritize innovation over fear. When appropriate, disciplinary action should be tailored to the severity of the policy violation.
- Over-communicate (within reason): Don’t just blast your team’s inbox with policy emails that won’t get read. Bring AI discussions into multiple channels, most importantly, face-to-face. Keeping AI top-of-mind encourages individuals to assess their own AI usage.
Don’t stop at writing a policy! That’s just the first step. Effective implementation requires resources for employee training, tool optimization, and monitoring practices. Our IT experts build successful, easy-to-implement AI roadmaps for mid-market businesses. Contact us to discuss your AI goals and gain an edge over your competition.
