Teams fear AI mistakes more than unclear human judgment—and that’s the real risk. AI assistants can draft faster than any team can review. The language is polished, confident, and sometimes wrong. When that happens, most organizations don’t have a simple answer to the most important question: who owns the outcome? The AI Boundary Problem is a practical guide for managers, team leads, and cross-functional teams adopting AI in messy real life. It doesn’t teach prompts. It doesn’t argue about whether AI is “good” or “bad.” It gives you a workable system for trust, review, and responsibility —so AI can speed up drafting without breaking trust. Inside you’ll learn how to: Close the “anxiety gap” that turns AI drafts into endless review threads - Make ownership explicit so accountability doesn’t dissolve into “everyone reviewed it” - Use three boundary zones to separate low-risk drafting from high-stakes work - Turn “trust” into a workflow with lightweight checks that actually catch errors - Treat prompts as briefs so the assistant stops guessing and inventing details - Set data boundaries without drama—clear handling rules, not security theater - Recover from mistakes without blame, using small repairs that prevent repeats - Keep the system current with a monthly boundary review that takes minutes, not meetings The result is not perfect prevention. It’s predictable handling: clear roles, faster decisions, and review that’s specific enough to matter—but small enough to survive a busy week. Work gets lighter when ownership, decisions, and communication are explicit. Clarity beats theater.