AI is a super intelligent, hyper-literal, eager, but inexperienced intern. It will produce exactly what you ask for — even when what you asked for is wrong.
That’s not a criticism of the technology. It’s a description of the relationship. A brilliant new intern doesn’t know your business yet. They don’t know that “pull last month’s numbers” means the fiscal month, not the calendar month, unless you tell them. They don’t know that “flag the outliers” means something different on your line than it does in a textbook. They’ll do exactly what you said, fast and confidently, and be completely wrong if you weren’t precise.
Most people don’t manage AI that way. They treat the output like it came from someone who already knows the job — and then get surprised when a hyper-literal, eager intern took the instruction exactly as written and produced something technically correct and practically useless.
The fix isn’t “trust it less.” It’s “manage it like the smartest inexperienced person you’ve ever hired.” You’d review a new intern’s first few reports closely. You’d correct the specific gap, not just the output. You’d expect them to get faster and more accurate as they learn your context — and you wouldn’t hand them something high-stakes on day one without checking their work.
Give AI that same onboarding discipline, and the inexperience stops being a liability and starts being manageable. Skip it, and you’re just handing an eager intern the keys and hoping they read your mind.
So what — where in your workflow are you treating AI output like it came from a 10-year veteran instead of a brilliant new hire? Now what — pick one recurring AI task and write the instruction as precisely as you would for someone’s very first day.
#ArtificialIntelligence #Leadership #ManufacturingIndustry #AIStrategy #OperationalExcellence
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