3 Ways to use AI in your business, ranked by effort

Most owners already have a mental list of places AI might help. What’s harder is knowing which item on that list to start with. Most advice on how to use AI in your business is a list of what the tools can do, presented as though they all cost the same to set up and manage, when in reality some take an afternoon and others require a month of planning.

A better approach is to decide based on the type of work you want handed off. Once you can describe the process and what good looks like, the setup and planning become a lot easier.

Here are three simple ways to start using AI in your business, listed from easiest to most advanced, followed by two steps to kick off your first project.

What you can do with AI in your business: easy to advanced

Getting started requires nothing more than an AI assistant like Claude or ChatGPT, and you could test it out before lunch. Each subsequent item requires more setup and suits a different type of work, and most businesses end up running more than one at a time, in no particular order.

As you read, look for work you already do rather than capabilities you might want. This will make it easier to get started and have an immediate impact.

1. Ask an AI assistant to draft, summarize, and answer

If you’ve asked an AI assistant a business question and got back something that reads like a brochure, the request was almost certainly the problem. A general-purpose assistant works with what you hand it, and a prompt like “write me a customer email” hands it nothing. It will draft, summarize, explain, and answer, but it stops. It won’t go into your systems and do anything, so a person still picks up the output and uses it.

Here’s the shape of a request that produces something you can actually send:

• Say what the business does and where it operates.
• Name the recurring situation, like the pricing question you answer five times a week.
• Ask for 2–3 reusable templates instead of a single reply.
• Set the tone and a length limit.
• Say what to leave out, such as discounts or delivery promises.

Fill that in, and you get templates the whole team can use. The work that suits this is business-level and reusable: first-response templates for your most common customer questions, a plain-language summary of a supplier contract before you get on the call, a first pass at a job description, or a chaotic quote turned into a formatted estimate.

You don’t need a full-blown AI strategy for any of that.

Best for: one-off or low-volume work where someone would read the output anyway.

Move up when: you notice you’re running the same request every week and pasting the result somewhere by hand.

2. Connect your apps so a routine job runs itself

The jobs most worth handing over are usually the dull ones that run the same way every week. Step-based automation follows logic you define, across apps the business already pays for.

When this happens, document the process, connect the tools, and define what good looks like. It’s dependable for structured, repeatable work that does the same thing every time.

Two examples at a genuinely small scale:

• A small e-commerce operation can run a daily trading snapshot that pulls orders, cash position, ad return, and stock cover into one message. It can also maintain a margin view and collect invoice paperwork from a linked email account.
• A fabrication business can check supplier portals on a schedule and consolidate orders and shipping statuses into a single list, so no one has to log in to each tool by hand. A second pass over that same inbox can surface messages that need the owner.

The only thing the above examples need is a documented process. No-code connectors are capable of handling lead management, customer support, document processing, and internal operations.

Proper documentation remains the primary obstacle for business leaders. Because step-driven automations strictly follow prescribed rules, they overlook edge cases that human oversight easily spots, such as a standard order placed by a client with multiple outstanding invoices. Addressing this blind spot is precisely why the third approach is necessary.

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3. Hand a full workflow to an AI agent

“Agent” is the word doing the most marketing work in this whole category, so it’s worth being precise about what changes. Where a step-based routine follows the path you laid out, an agentic workflow decides what to do at each turn. It reads the situation, picks an action, checks the result, and adjusts, which is what makes it useful for research, analysis, and the judgment-heavy work a connector chain could break on.

The strongest setups usually combine the two: step-based automation for the predictable parts of a process and an agentic layer for work that requires flexibility.

One real estate brokerage built an agent that scores every lead in its inbound database, sends the sales team a brief each morning, and manages a broker’s calendar (example via Zapier). That team isn’t ranking leads by hand, and it didn’t have to write a rule for every kind of lead that comes in.

Two costs to plan for:

• Review capacity. Producing more doesn’t help if nobody can check it. One practitioner who automated an entire production pipeline found that the bottleneck had simply moved: the agent could generate thousands of items, and a person could still review only a fraction of them in a day.
• Scope and oversight. Human intervention has to stay in the loop, especially in the first few weeks when you’re still learning where things go wrong. Give each agent one clear responsibility, or you spend your week managing agents instead of running the business.

This is worth building when you understand the process well, you have someone who can own the oversight, and the judgment calls are the expensive part of the job. If you’re still hand-carrying data between two systems every Monday, a connected routine will pay off faster.

If you’d rather build one properly than learn it through trial and error, our AI Automation course is five weeks of building real no-code workflows with an instructor reviewing everything you build.

How to start using AI in your business

Begin by analyzing the business itself to identify inefficiencies, financial leaks, customer bottlenecks, and manual tasks.

The two steps below will help you pinpoint a single, clearly defined job that can be evaluated and aligned with one of the AI options from earlier.

Step 1: Pick a recurring task you’re tired of doing

Don’t start by shopping for tools. Instead, choose one job you’re tired of doing, then describe it until it’s concrete enough to judge. Invoice chasing, vendor status checks, quote follow-ups, and the first reply to a contact form are all fair candidates.

Map one workflow before looking at tools. These dimensions make a usable checklist:

• Trigger: what starts this job?
• Information: what does it need, and where does that live?
• Owner: who does it today?
• Systems: what does it touch?
• Output: what exists at the end?
• Exceptions: how often does it go off-script, and what happens then?
• Success measure: how would you know it worked?

Be clear about which content AI is permitted to draft and which messages strictly require human authorization.

Automation succeeds only when applied to a clearly defined process. Introducing it into an unmapped workflow won’t solve anything, and automating poorly structured sales workflows or redundant records will only multiply existing errors. With this in mind, make sure to prioritize centralizing and cleaning your data prior to implementation.

When both the initiating trigger and expected outcome are clearly identified, you’re ready to automate.

Step 2: Test whether that work is a fit for AI

Judging the job you just described should take about ten minutes. Susan Morrow, an instructor in our AI Automation course, describes the underlying method as “a simple and repeatable five-step process”: define the problem, map the process, evaluate whether it is suitable for automation, decide where a person remains involved, and build a proposal.

Work that requires empathy, nuanced judgment, creativity, or handling an unpredictable and emotionally charged situation is a poor candidate, and the correct action is to leave it alone.

If the job clears those signals, match it to what you read earlier. A one-off question or draft is assistant work. A job that runs the same way every time across two or more systems is a connected routine. A job that needs a judgment call at each turn is agent territory. Ruling a job out at this stage is the cheapest decision available to you, and it counts as completing the step.

How to tell whether your AI is actually saving you work

Faster output can create more work. When the constraint moves from producing something to checking it, the hours you saved get spent supervising, and practitioners dismiss raw generation speed as a vanity metric for exactly that reason.

Two tests are worth running on anything already up and running.

• The cancel-it-tomorrow question. If you killed this tool tomorrow, would your week measurably get worse? This question can help separate the workflows carrying real load from the ones you’re managing out of habit.
• One value measure per workflow. Separate an activity metric, such as how many people use AI, from a value metric, meaning what changed in the business. Value can show up in revenue, cost, productivity, speed, or quality. Pick one measure per workflow before you switch it on: hours spent on invoice admin per week, days to get a quote out, or share of orders needing a correction. Seats in use and prompts run don’t answer that question.

When a workflow fails one of these tests, go back to Step 1. The job usually wasn’t described precisely enough for any tool to handle it, and it needs to be refined further.

When to keep a person in the loop

The core anxiety for most business owners is sending an automated message from their name to a customer who is already dissatisfied. While Step 2 filters out unsuitable processes beforehand, a firm boundary must also be maintained within related workflows.

Core human qualities like empathy, subtle judgment, and creativity must remain with people; placing automation in front of these key interactions risks undermining years of built-up trust.

Keep a person in the loop for:

• A complaint from a long-standing customer.
• A pricing exception or a goodwill decision.
• Anything touching someone’s employment: pay, performance, discipline, and hiring.
• The first conversation after something has gone wrong.

Then design for the handback. Build every workflow so a person can step in and take control when circumstances change. Decide what AI may draft and what only a person may send, and write it down before anything goes live.

This is also the honest answer to the question of whether automation costs people their jobs. What it takes off the table is task-level work, like data entry, routine report assembly, and the fifth identical status update of the day. Oversight becomes part of somebody’s actual job in return, most visibly during setup.

A workable rule of thumb: if a mistake in this job would cost you a relationship rather than an hour, keep a person on it.

FAQ: Using AI in your business

Do I need to be technical to use AI in my business?

No. A general-purpose AI assistant, a written request template, and a no-code connector are all built for people who don’t code. Technical comfort or outside help starts to matter once you’re building an agent, and even then the hard part is design judgment.

Will using AI in my business cost people their jobs?

Automation of this kind targets repetitive, task-level work rather than entire roles, and it creates oversight work that a person must perform. Plan for both: the tasks that disappear and the review time that appears in their place.

My data and processes are a mess. Should I fix that first?

You can put an assistant to work today either way, because it doesn’t touch your systems. A connected routine or an agent will keep failing until the process is written down and the records are clean, and that is the more common blocker.

How long before I see anything useful?

Sooner if you pick one workflow instead of three tools. Choose a single measure before you start, whether that’s time saved, errors avoided, or customer response time, and judge that one workflow on that one measure before expanding.

Where can I see how other businesses are actually doing this?

Look for owner-to-owner accounts focused on a specific workflow rather than tool roundups (YouTube is a good place to start). Weigh the accounts that say what broke more heavily than the ones that say what worked, and ask what the person had to fix before their automation held.