How do I know if AI is worth it for my company?
Guided by Otto, written by Something Clever Co., updated
AI is worth it when it takes real, repeated work off your team's plate and the time saved is worth more than the setup and running costs. The honest way to find out is to pick one specific workflow, run it with human approval for a few weeks, and compare it to how the work was done before. If you cannot name the task it would replace, it is probably not worth it yet.
Why this is hard to answer from the outside
Every AI vendor has a story about huge time savings. Some of those stories are true for someone. The problem is that “AI saves time” is meaningless until you know which work, done by whom, how often, and what it costs to set up and keep running. Your answer depends entirely on your business.
The good news is you do not need to guess. You can find out with a small, cheap test before committing to anything big.
Find the real cost of the work
Make a short list of repetitive tasks your team does every week. For each one, note roughly how often it happens, how long it takes, and who does it. Pay special attention to work that falls on your most expensive or most overloaded people. An hour of the owner’s week is usually worth more than an hour of anyone else’s.
Also note the cost of things not getting done. Leads that do not get a reply, invoices that go unchased, reports nobody has time to pull. Those costs are real even if they never show up on a timesheet.
Pick one workflow to test
Choose the task that is frequent, follows a clear pattern and would be low risk if a draft were wrong. Define what good output looks like before you start, so you can judge results fairly.
Run it with a person approving
Let the AI do the work, and have a person approve it before anything goes out or changes. This keeps customers safe during the test and gives you the most useful data, because every approval or correction tells you how reliable the AI actually is.
Measure honestly
Track a few simple things:
- How long the task takes now, including review time
- How often people approve the AI’s work without changes
- How often they have to fix or reject it
- What the tools and AI usage cost
- Whether anything slipped through that should not have
Be strict about review time. If someone spends as long checking AI output as they used to spend doing the work, you have not saved anything yet.
Decide
At the end of the test you will be in one of three places. Clearly worth it: keep it, and consider giving it more independence. Close: adjust instructions or inputs and test again. Not worth it: stop. That is a good outcome too, because you learned it cheaply.
A quick comparison of signals
| Signal | Points toward “worth it” | Points toward “not yet” |
|---|---|---|
| Task frequency | Daily or weekly | A few times a year |
| Pattern | Clear, repeatable steps | Every case is different |
| Review effort | Quick approvals, few edits | Heavy rewriting every time |
| Who it frees up | Owner or key staff | Nobody in particular |
| Cost of mistakes | Low and reversible | High or permanent |
| Process today | Agreed and documented | Unclear or disputed |
When AI is not worth it
Be skeptical if the main reason is that competitors are doing it, if you cannot name the specific task, if your team is small and the work is genuinely varied, or if the real problem is a process nobody has agreed on. In those cases, money is better spent elsewhere, and we will tell you that during a Free AI Check.
Common mistakes
- Starting with a tool instead of a task. Decide what work you want gone first.
- Ignoring review time. It is a real cost, especially early on.
- Testing too many things at once. You will not know what worked.
- Judging after a few days. Give it enough real use to see patterns.
- Counting only hours saved. Faster replies and fewer dropped balls matter too.
- Keeping a workflow that is not helping. Stopping is allowed.
