We want to train an internal AI chatbot on our core business processes so our team can get instant answers on how we run operations, but our documented processes are scattered across old PDFs, Google Docs, and half-finished intranet pages. How do we clean up our operational documentation before feeding it into an AI tool?

Question

Tyler Smith · Accepted Answer

Before you feed any operational document into an AI model, you must realize that automated tools do not filter for accuracy; they simply predict the next logical word based on whatever data they receive. If your standard operating procedures are fragmented, contradictory, or outdated, your new AI tool will simply deliver bad answers at a much faster rate. To prepare for this transition without paying a steep dumb tax, you need to treat your core process documentation as an operational Rock. Begin by assigning one owner on your Accountability Chart to run a content inventory. This owner must gather all scattered documentation, old PDFs, and emails, then consolidate them into your documented core processes as defined by the EOS Process Component. Use Keith Cunningham's Thinking Time process to focus on the cleanup. Dedicate forty five minutes to answer this question: How might we simplify our core processes so that an untrained human could execute them without assistance? If a human cannot follow your current documentation, an AI model will struggle even more. Once you have a single, clean source of truth, run a test phase. Feed a small, high value section of your clean procedures into the tool and have your team test it. Only when the output is consistently accurate should you open up the rest of the database. This methodical approach ensures your AI behaves as an efficient assistant rather than an unpredictable liability.