How to Build AI Agents for Small Businesses

If you own a small business, you’re probably drowning in repetitive tasks like answering the same customer questions, chasing down invoices, and managing your schedule. 

You’ve heard that AI agents might be able to help… but most guides on how to build AI agents for small businesses assume that: 

1. You have a team of developers on hand, and 
2. You’ve got a six-figure budget to support them. 

This guide doesn’t.

At Upwork, we see thousands of small businesses every week looking for ways to use AI agents to save time and scale, and (at least from what we’ve seen so far), you definitely don’t need to be a tech giant to get in on the AI action.

So in this guide, we’re sharing all the secrets on how AI agents work for small businesses, the costs involved, and how you can start integrating them into your workflows ASAP.  

What is an AI agent?

But first: even if you’ve already read a lot about AI agents, you might still be a little confused about what they actually are and what they’re actually meant to do. 

So before we get to the specific use cases and approaches, here’s a quick definition: 

An AI agent is a piece of software (powered by AI) that can observe information, make decisions based on rules or goals, and take actions automatically. Unlike an AI chatbot (like ChatGPT), an agent can actually connect to the tools you’re already using and perform tasks on your behalf.

Of course, that doesn’t mean AI agents would (or even could) replace you as the owner of the business. Instead, experts in the space suggest thinking of your AI agents more as a “co-founder” or “partner” that can help with things like ideation and scaling. 

What can an AI agent actually do for your small business?

So, what does this look like for small businesses? In general, it’s all about automating workflows and freeing up time that would otherwise be spent on administrative tasks. 

Below are some of the most practical ways small businesses are already using AI agents today, along with estimates for time saved, setup difficulty, and cost.

Why Build an AI Agent for Your Small Business: Popular Use Cases and Costs

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To put that into perspective: if an AI agent saves just 10 hours per week, that’s more than 500 hours per year; essentially giving a small business owner the equivalent of three extra months of productivity without hiring another employee.

Building your first AI agent: The DIY, no-code approach

Now for the fun part: how to actually build an AI agent for your small businesses. 

If you enjoy setting up business systems, no-code platforms like Zapier and n8n make it surprisingly easy to connect different apps and services. From there, you can create automated workflows that can take care of things like qualifying leads or posting to social media. 

Let’s walk through a simple example of how to build a lead qualification agent using a no-code platform like Zapier.

Step #1: Set up the trigger 

Every automation starts with a trigger, which is the event that kicks off the workflow.

In this case, the trigger might be “New Form Submission” from a tool like Typeform or Google Forms. That simply means that every time someone fills out your contact form, the workflow automatically starts running.

From there, the data from the form can move through the rest of your automation.

Step #2: Connect to an LLM

Next, you’ll connect the workflow to a large language model (LLM) like GPT-4.

To do this, you’ll first need an API key from OpenAI. Once you have that, you simply add an OpenAI action to your workflow in Zapier and paste in your API key.

At that point, your automation can send the form data to the AI and ask it to analyze or process the information.

Step #3: Craft the prompt

This is arguably the most important step. Your prompt is what tells the AI how to evaluate the lead and what output you want it to generate.

The following table outlines the four key elements of a strong AI prompt and how to structure them to get the best results.

How to Build AI Agents for Small Business: 4 Elements of a Good AI Prompt

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Step #4: Test the prompt

Once your prompt is ready, test the workflow by submitting a sample form entry.

The AI will process the form data, apply your scoring criteria, and return a lead score along with any notes or explanations you asked it to generate. If the results aren’t quite what you’re looking for, that’s completely normal. Just tweak the prompt, run the test again, and continue tweaking until you’re happy with the results. 

Step #5: Add the lead to your CRM

Once everything is working smoothly, the final step is to add the lead and their score to your CRM, like HubSpot or Pipedrive. You can also set up a filter so that high-scoring leads are automatically assigned to a salesperson for follow-up. For example, you could create a rule that says, “If the score is 8 or higher, send an email to the sales team.”

When you might need a more advanced approach for building an AI agent for your small business

No-code tools are great for getting started. But if you want to build something more sophisticated (like an AI agent that pulls from multiple data sources or makes more complex decisions), you’ll likely need a more advanced approach.

That usually means either building the agent with developer tools or working with an expert who can build it for you.

Here’s how both approaches work. 

The developer-assisted approach

No-code tools are great for simple automations. But if you want to build a more advanced AI agent with custom logic and deeper integrations, you’ll usually need to build the agent directly. This can be done with LLM APIs, frameworks, and custom code. This gives you far more control over how the agent works and allows it to integrate deeply with your internal tools and databases. 

In general, the process looks something like this:

1. Choose an LLM: First, select the language model your agent will use. Popular options include GPT-4 from OpenAI, Claude from Anthropic, or Gemini from Google. To use these models, you’ll typically sign up for an API key.
2. Choose a framework: Frameworks like LangChain and LlamaIndex make it easier to build AI-powered applications. They handle common infrastructure tasks so you can focus on designing the logic and capabilities of your agent.
3. Write the code: Next comes the development work. Usually, this means writing Python code that connects the LLM to your tools, data sources, and APIs. This is where you define things like the agent’s goals and what tools it can access. 
4. Deploy the agent: Finally, the agent needs somewhere to run. Most teams deploy their agents on cloud platforms like Amazon Web Services, Google Cloud, or Microsoft Azure so the system can run continuously in the background.

This approach is far more powerful than no-code automation, but it also requires significantly more technical expertise. If you’re not comfortable working with APIs and code, you may need to bring in a developer to help build and maintain the system.

Hire an AI expert

Building AI agents involves a lot of moving parts, and the learning curve for non-experts can take weeks or even months. 

That’s why a lot of small businesses choose to work with experienced developers instead (typically on a freelance basis), so they can get a system built quickly without having to commit to a full-time hire.

For example, on platforms like Upwork, you can find thousands of freelance AI engineers and automation specialists who already have experience building custom AI agents. Many of them specialize in tools and frameworks like LangChain, LlamaIndex, and integrations with models like GPT-4 or Claude, which means they can often build and deploy an agent a lot faster than someone starting from scratch.

While hiring a developer is typically more expensive upfront than no-code approaches, it can often save a huge amount of time (and money) in the long run. 

Where to start with AI automation in your small business

A few years ago, building an AI agent for your small business might have sounded unrealistic. Today, with no-code tools, affordable AI models, and access to developers worldwide, it’s becoming a practical option for businesses of all sizes.

The key is not trying to automate everything at once.

Instead, start by looking for the biggest bottleneck in your business. What repetitive task keeps eating up your time each week? Maybe it’s answering the same customer questions, qualifying leads, scheduling appointments, or following up on invoices.

Once you’ve identified that bottleneck, choose a task that offers a big impact but is relatively simple to automate. For many businesses, something like a customer support chatbot or lead qualification workflow is a great place to start.

It’s also helpful to think about the potential return. If an AI agent costs $50 per month but saves you 10 hours of work (and your time is worth $50 an hour), that’s a significant return for a relatively small investment.

Finally, start with one use case, test it, and refine it. Once you see the time savings and efficiency gains for yourself, you’ll likely start spotting other parts of your business that could benefit from automation, too. 

Frequently asked questions about how to build AI agents for small businesses

How much does it cost to build an AI agent?

The cost can range from $20 per month for a simple no-code agent to over $10,000 for a complex, custom-built agent. The cost depends on the complexity of the task, the tools you use, and whether you choose to build it yourself or hire an expert.

Do I need to know how to code to build an AI agent?

No. With no-code platforms like Zapier, you can build simple AI agents without writing a single line of code. However, if you want to build more complex or customized agents, you will need some coding knowledge (or you can hire a developer to help you).

What is the difference between an AI agent and a chatbot?

An AI agent is a piece of software that can analyze information, make decisions, and take actions across different tools or systems. A chatbot is a specific type of AI agent designed mainly to communicate with users through conversation.

How can I hire an AI developer to build an agent for me?

One of the easiest ways to hire an AI developer is to use platforms like Upwork, where you can find freelance developers from around the world.

All you have to do is post a short description of what you’re looking to build, and developers can send proposals explaining how they’d approach the project. From there, you can take a look at their past projects and client reviews to find someone who has experience with the tools you want to use. Once you’ve found a good match, you can then discuss the scope, timeline, and budget before starting the project.

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.