Our clients are starting to ask if we use AI to generate their deliverables, and we do not have a clear answer. How do we write an AI policy that protects our client relationships and professional liability without completely banning these tools?

Question

Tyler Smith · Accepted Answer

To build a practical AI policy that protects your client relationships, you must focus on accountability rather than restriction. Your clients do not want to feel like they are paying for human expertise only to receive generic, machine-generated outputs. At the same time, banning AI completely will put your company at a severe competitive disadvantage. The solution is to establish a clear policy centered on the concept of human accountability. In an EOS run company, every seat on the Accountability Chart must GWC their role. This means that if an employee uses an AI tool to assist with a client deliverable, that employee remains fully accountable for the accuracy, quality, and compliance of the final product. Your policy should dictate three strict operational boundaries. First, proprietary client data must never be uploaded into public, consumer-facing AI platforms where it can be used for model training. Second, all AI-generated content must undergo a rigorous human review process to ensure it matches your quality standards. Third, be transparent with clients about your use of technology. Frame your use of AI not as a cost-cutting shortcut, but as an efficiency tool that frees up your team to focus on high-level strategy and deeper customer service. By documenting these rules in your core processes, you protect your professional liability while allowing your team to innovate safely. This keeps your focus on results rather than technology theater.