SMB owners are the ultimate beneficiaries of AI. In large companies, job functions are filled by full-time employees, and recruiting teams, paired with strong brands, continuously keep those roles filled. Small business owners, on the other hand, are the catch-all for the entire organization. Customer service rep is out sick one day? You might have to be hands-on customer support. Hiring a new sales rep? Half your day may be spent interviewing. This is where AI Agents can actually make a significant difference.
What Is an AI Agent?
When most people hear “AI,” they think of ChatGPT or Gemini. These are tools you talk to that give you answers. Those are useful, but they’re not what I’m talking about here.
AI Agents actually do things for you. The “Agent” part means the AI actually does something (also known as a “side effect”) in the real world on your behalf. For example, an AI Agent can launch a website, book appointments, call customers, and even email prospects.
The difference between a chatbot and an Agent is the difference between a consultant who writes you a memo of how to do the work, and an employee who actually gets the work done.
Here are four types of AI Agents that are delivering real value for SMBs:
1. AI Receptionists: Never Miss a Call Again
The businesses seeing the most impact from AI Receptionists are those that rely on phone calls as their primary source of leads: HVAC shops, roofers, and small plumbing companies. Every call is an opportunity, and every second matters.
Here’s the reality for most trades businesses: when the phone rings and nobody picks up, that’s a lost job. It might be a $500 service call or a $15,000 system install, gone because the customer was on hold for just a couple of minutes.
AI receptionists answer every inbound call 24/7 and can perform the task at human-level accuracy. They qualify the customer, collect the details, and book the appointment directly on your calendar.
Use an AI receptionist if:
- You miss calls after hours or during peak times
- A missed call equals a lost customer or revenue
- A meaningful percentage of your customers speak another language, and you cannot consistently staff for it
- You operate in a market where customers call multiple providers and book whoever answers first
- Answering the call doesn’t have regulatory or legal requirements (e.g. attorney-client privilege, insurance license requirements)
2. AI for Customer Support
If you’ve ever looked at your support inbox, you already know the truth: 60–80% of the requests are the same 10 questions asked slightly differently with slightly different context.
AI Support Agents not only handle inbound emails and web chat but also take action. Should a return label be generated? Done. Do the account details need to be sent again? Sent. Is the customer asking for an exception? Granted, but only if the customer has not been abusing the system.
These Support Agents are also trained using your support manual and previous interactions with your customers. Like other Agents, you can flag what it got wrong, and the AI will get it right in the future.
Use AI for support if:
- You have a backlog of repetitive tickets
- 60–80% of inquiries follow predictable patterns
- You can document clear rules for handling requests
- Resolution usually involves structured actions (refunds, account updates, resending documents, order status checks)
- The support task does not require creative judgment, like designing a custom kitchen layout
3. Coding Agents: Supercharge Your Engineers
If your business does any software development, Coding Agents are the most mature AI Agents today.
The Software Engineer job is shifting. Engineers are becoming AI managers, directing Agents rather than writing code (or even reading it). The best engineers get the most leverage, and a new archetype is emerging: the AI manager who is strong enough to code but smart enough to delegate all the work in manageable components to the AI.
What this means for you: that one engineer you hired can now do the work of a small team. If you feel you were limited by your engineering output, the economics just changed.
Use coding agents if:
- You build software internally
- You want to ship features faster without immediately expanding headcount
- You want to experiment!
4. Agent-First Computing: The Wild Card
Agent-First Computing is the AI frontier, and the entire world is just starting to experiment with it.
Agent-first computing means giving an AI its own computer. It can browse the web, manage files, send messages, chain tasks together, and operate autonomously. Platforms like OpenClaw let you set one up on an isolated virtual machine and invite it to a private Slack channel where you and your employees interact with it like a coworker.
This is a brand-new paradigm. There’s a famous quote that computers were “a bicycle for the brain.” Agent-first computing is giving that bicycle to the AI itself.
The downside is real, too. There are genuine security considerations when you give an AI autonomous access to systems. It can randomly email coupons to your customers to drive growth; it can get tricked into letting someone else access its computer. This is why isolation matters. Dedicated hardware or a virtual machine, limited permissions, a private channel. Start contained.
Only experiment here if you’re technically adventurous and want to see where this is all heading. Not for everyone yet, but the SMB owners who figure it out early will have an unfair advantage.
How to Start Growing Your Business With AI This Week
Here’s the practical playbook. Think about doing twice as much work as you do every day and getting your employees to do the same.
First, pick the low-hanging fruit. If any of the first two categories apply to your business (AI Receptionist, AI Customer Support), these are off-the-shelf today. You can be up and running this week.
Then, let your developers use Coding Agents. Codex by OpenAI and Claude Code by Anthropic are the two most frequently used ones. Start with something simple—a script or a small feature that you’d like to be made. Then let your engineers simply direct the Coding Agents to do the work. Once they see it work the first time, they’ll be hooked. Gradually increase the complexity of the tasks until you can build fully fleshed-out features for your product or service.
Finally, try Agent-First Computing. Once you see the value, consider setting up an Agent on an isolated machine and inviting it to a team channel. Let your employees try it. You’ll see which tasks it can handle perfectly, which need a bit of help, and which are total non-starters. The ones who figure out how to work with Agent-first will be your most valuable people because they will get the most done.
We are on an exponential curve, with AI getting 2x better every six months. There are many metrics that track this: the amount of time it can run without making a mistake, the number of tasks it can do, the complexity of the task, etc. It’s giving resourceful small business owners superpowers. And resourcefulness is what got you here in the first place.
Jeff Chen is the CEO of Redcar AI, a San Francisco-based company that builds Voice AI Agents for HVAC, plumbing, and electrical companies. Previously, he led product development at Google, where he helped launch the Google Voice Assistant. Jeff studied computer science at Berkeley and Stanford University and is passionate about bringing enterprise-grade AI to every business on planet Earth.
