How do I use AI in my small business?
Guided by Otto, written by Something Clever Co., updated
Start with one repetitive task that eats time every week, like answering common emails, logging call notes or turning requests into tasks. Let AI draft the work while a person approves it, then connect it to the tools you already use, such as Slack, Gmail or your CRM. Expand only after that first workflow is reliable.
Where most small businesses get stuck
Plenty of owners have tried AI. They used ChatGPT to write a social post, maybe a job description, and thought “neat.” Then nothing changed about how the business actually runs. The inbox is still full, call notes still live in someone’s head, and the same questions still get answered by hand.
That gap exists because chatting with AI and putting AI to work are different things. The first is a tool you pick up. The second is a change to a workflow, which means picking the right task, connecting the right systems and deciding who checks the output.
Find the boring, repeated work
Spend a week noticing what your team does over and over. Good candidates usually look like this:
- The same type of email answered many times a week
- Information copied from one place to another (call notes into a CRM, form entries into a spreadsheet)
- Requests that arrive in Slack or email and need to become tasks
- Weekly or monthly reports someone pulls together by hand
- Follow ups that slip because nobody owns them
Write each one down with a rough sense of how often it happens and who does it.
Pick one, not ten
Choose a single task that is frequent, clearly defined and low risk if a draft is wrong. “Turn a Slack message into an assigned task in our project tool” is a great first project. “Have AI run sales” is not.
Start with drafts and approvals
Let the AI do the work, but have a person approve it before anything goes out or changes. It gives you speed without betting the business on a tool you just met. If a task is very sensitive, start one step lower, where AI only suggests and a person does the action.
Connect it to where the work already happens
AI is most useful when it lives inside your existing tools instead of in a separate chat window. That might mean connecting Slack to your task manager, Gmail to HubSpot, or Stripe to your bookkeeping. Tools like Zapier, Make and n8n can handle simple connections. More involved workflows need custom setup, and it is smart to give each one access to only what it needs.
Measure, then expand
Keep it simple. Is the task getting done faster? Are drafts usually right? Is anyone fixing the same mistake over and over? If the answers are good, give the workflow more room or move to the next task on your list. If not, adjust or stop. Dropping a workflow that is not helping is a success, not a failure.
A quick comparison of starting points
| Starting point | Effort to set up | Risk if it goes wrong | Who it suits |
|---|---|---|---|
| Using ChatGPT or Claude for drafts | Very low | Low, a person sends everything | Everyone, today |
| Simple automations (Zapier, Make, n8n) | Low to moderate | Moderate, can misfire quietly | Teams with clear, simple handoffs |
| Connected AI workflows with approvals | Moderate | Low, approvals catch mistakes | Businesses ready to change how work flows |
| Fully autonomous AI | Higher | Higher without strong limits | Only proven workflows with little at stake |
When not to use AI
AI is a poor fit when the task is rare, when every case is different, when a mistake would be expensive or embarrassing, or when the real problem is that nobody has agreed on how the work should be done. Fix the process first. AI will only make an unclear process run faster in the wrong direction.
It is also not a reason to stop talking to customers. If a relationship depends on a personal touch, keep a person in it.
Common mistakes
- Starting too big. One working workflow beats five half finished ones.
- Buying a tool before choosing a task. Decide the job, then pick the tool.
- No human check at the start. Approvals are how you learn whether AI can be trusted with the job.
- Pasting sensitive data into free chatbots. Use business accounts and know where data goes.
- Not telling the team. People need to know what AI is doing and who to ask when it is wrong.
- Never reviewing. A workflow that worked in spring may drift by fall.
