AI can produce a clean summary, a confident recommendation, or a polished draft in seconds. The better it gets at sounding right, the easier it is to stop checking whether it actually is.
A well-written answer isn’t necessarily a correct one. The more capable AI becomes, the more important it is that we don’t stop thinking for ourselves.
1. Don’t confuse a good answer with the right answer
One of the biggest risks with AI is work that looks perfectly reasonable, even when something is wrong.
AI can produce convincing answers without knowing your company’s history, the people involved, or the constraints you’re working with. It might miss an important exception, rely on an outdated assumption, or recommend something that simply doesn’t make sense for your situation.
When reviewing AI-generated work, consider whether it makes sense for your situation, beyond simply checking for errors.
2. Know which decisions belong to people
AI can help with a lot of tasks, but some decisions still need to be made by people.
Decisions that affect people. AI can help organize notes, prepare for a conversation, or explore options. Decisions about someone’s career, well-being, or future still belong to the people who understand the circumstances and will be accountable for the outcome.
Outputs that depend on context the model doesn’t have. AI can draft a message or compare options, but it doesn’t know the history of a relationship, the risk tolerance of the organization, or the constraints that never appear in a document. Even a well-written message or a logical recommendation can miss the mark when important context is missing.
AI has a place in difficult work, as long as we’re clear about what it should and shouldn’t do. AI can support the work. The decision and the responsibility stay with the person.
3. Challenge the output
One of the simplest ways to get better results from AI is to stop treating its first response as the final answer. When we train teams to use AI, we encourage them to question what it produces the same way they would review work from a colleague.
A few questions can surface gaps quickly:
What assumptions are you making? This reveals gaps in the information you’ve provided.
What might be missing? Ask it to identify exceptions, risks, or perspectives it may have overlooked.
Can you show me the source? For factual claims, go back to the original material and verify.
What would someone who disagrees say? Use it to explore an opposing view instead of simply reinforcing your initial thinking.
If something sounds generic, misses an important detail, or doesn’t feel right for the situation, challenge it. You know things about your work, your customers, and your organization that may never appear in a prompt. That knowledge matters.
AI will continue to improve. Many tasks that require careful prompting and review today will become easier and more reliable. That does not eliminate the need for human judgment. As AI becomes part of everyday work, knowing when to trust it and when to question it becomes even more important.
Use AI to research, explore ideas, write, and work through problems. Let it handle some of the repetitive work so you can spend more time on what matters. Stay involved, question the results, and make the final decisions yourself.
