
Every office has a person everyone asks. If you are not sure who yours is, look at whose chair gets the most visitors.
That person is usually your most capable employee. They know where the file is, which customer needs special handling, and how the approval really works. Colleagues love them and managers praise them. They are also quietly losing a day each week to questions that have been answered before.
This is not a compliment problem. It is a process problem, and it costs more than most companies realize.
What one helpful person really costs
Picture a senior coordinator on a team of twenty. These numbers are illustrative, so replace them with your own.
• 12 repeat questions a day, such as “Where is the latest price list?” and “Who approves this?”
• About 6 minutes each: 72 minutes a day
• Five working days: 6 hours a week
Over 50 weeks, that is 300 hours, or about seven and a half working weeks. One person spends that time every year answering questions the company could have answered once, in writing.
The six hours is only the visible part. Each question also interrupts the work the person was doing, and the person asking pauses their own work while they wait. The real cost is larger than the arithmetic shows.
Why the answers live in one head
Nobody planned it. The person was helpful once, then again, and soon the team learned that asking was easier than looking. Writing the answer down was never anyone’s job, so it never happened.
The result is a company whose knowledge walks around on two legs. When that person goes on leave, gets promoted, or resigns, the team discovers how much of the process was kept in their memory.
That is why this is a risk and not only a cost. A process that depends on one person’s memory has no backup.
You can spot the signs quickly. People say “just ask Maria.” New hires are told who to ask before they are told where to look. The same person is copied on every thread. Projects slow down the week that one person takes leave.
Why AI cannot fix this by itself
Many teams hear this and reach for a chatbot. Put an AI assistant on top of the company’s files and let it answer the questions.
It sounds right, but an assistant can only answer from what has been written down. If the real answer to “Who approves this?” lives in one person’s head, the tool will guess, or it will repeat an outdated policy with great confidence.
A tool that answers from old documents does not remove the interruptions. It only changes who gets blamed for them.
Written answers come first. AI comes second.
Three steps, in this order
1. Collect. For two weeks, the helpful person keeps a simple tally of the questions they answer. One line in a notebook for each question. Do not ask them to write anything else yet.
2. Write the top ten once. At the end of two weeks, pick the ten most common questions. Write each answer in two or three plain sentences, with the link or form attached. Put them in one shared place that everyone can reach.
3. Add AI. Once the answers exist and are current, an AI assistant can search them and reply to the routine questions. The helpful person reviews what it gets wrong and corrects the source.
Notice the order. Counting comes before writing, and writing comes before the tool. Skip the first two steps and the tool has nothing true to say.
The tally matters more than it looks. It replaces opinions about what people ask with a count, and the count often surprises everyone, including the helpful person.
Do not aim for a complete handbook either. A short list that is accurate and easy to find will do more than a long one that nobody trusts.
What belongs in the top ten
Good first entries are practical. Where to find the current price list. Who approves what, and up to what amount. How to request an exception for a customer. Which form to use for a refund.
Skip opinions, and skip anything that changes every week. If an answer needs a long explanation, write the short version first and link to the details. Ten good answers that people actually use beat a hundred pages that nobody opens.
What the numbers look like after
Suppose the written answers and the assistant handle two out of three of the repeat questions. That is an estimate, so measure your own.
• 4 questions a day still reach the person: 4 × 6 minutes = 24 minutes
• Updating and correcting the written answers: about 10 minutes a day
That is 34 minutes a day instead of 72. About 3 hours a week come back, or roughly 160 hours a year.
The hours are only part of the gain. New hires get answers without waiting for a busy colleague. The company gets a written record that survives vacations and resignations. And the helpful person gets their focus back, which is the thing they were short of all along.
Why the assistant still needs a human
Even a good assistant will sometimes answer wrongly, or answer a question that needed a judgment call. Policies change, and a written answer can go stale without anyone noticing.
Keep a person responsible for the answer library. Give them a simple routine: review the questions the assistant could not answer, fix any wrong replies, and update anything that changed. Ten minutes a day keeps the whole system honest.
Also make it easy to reach a real person. When someone is not satisfied with the written answer, they should be able to ask directly. The goal is to remove repeat questions, not to wall off the people who know things.
Protect the person, not just the process
Handle this with care. The helpful person may feel that being the one who knows is what makes them valuable. If you announce that you are replacing that with a document, they will resist, and their worry would be fair.
Be honest with them. Their knowledge is valuable, which is exactly why you want it written down and used well. Moving from answering the same questions to owning the answers is a step up in the kind of work they do. Say so in public, and give them ownership of the answer library.
People who feel respected share what they know. People who feel threatened start guarding it.
Try it this month
1. Ask the person your team asks most to keep a two-week tally.
2. Write the top ten answers together, in plain words, in one shared place.
3. Tell the team where the answers live, and ask them to look there first.
4. Only then test an AI assistant on those ten answers, and check its replies against the source.
After a month, count the questions again. If the number has dropped, you have your result. If it has not, find out why people still ask. Often the written version is hard to find, and that is a fixable problem.
Your most helpful person should not be your search engine. Write the answer once, and let everyone find it.
Who in your company gets asked the same questions every day, and what would they do with the time if they did not?
If you want to talk through how to start in your team, I’d be glad to hear your thoughts.
ADDITIONAL READING
• Your Company Isn’t Slow—Your Decisions Are Trapped in Manual Processes — https://jordanimutan.com/2025/12/19/your-company-isnt-slow/
• Would I Automate Meeting Minutes? Yes, After Fixing the Meeting — https://jordanimutan.com/2026/10/27/would-i-automate-meeting-minutes-yes-after-fixing-the-meeting/
• The 20% of Any Job That’s Actually Worth Giving to AI — https://jordanimutan.com/2026/10/06/the-20-of-any-job-thats-actually-worth-giving-to-ai/
• AI Was Supposed to Save Your Managers Time. It Didn’t. — https://jordanimutan.com/2026/09/03/ai-was-supposed-to-save-your-managers-time-it-didnt/
• You Trained Your Team on AI. Their Output Didn’t Change. — https://jordanimutan.com/2026/09/15/you-trained-your-team-on-ai-their-output-didnt-change/








