There is a phone ringing right now at a dental office in suburban Phoenix. It is 6:47 PM. The office closed at 5. The caller is a new patient who just chipped a tooth at dinner and found the practice through a Google search 90 seconds ago. No one is going to answer.
That patient will call the next result. And the next. Until someone picks up.
This is not an edge case. This is the default experience for millions of consumers interacting with local businesses every day. And it is the reason we built Podium.
The gap no one was solving
When Dennis Steele and I started Podium in 2014, we were not thinking about AI. We were thinking about a tire shop owner in Provo, Utah, who could not figure out why his Google reviews were disappearing. That problem led us into customer communication, and customer communication led us into something much larger: the realization that local businesses, the backbone of the American economy, were running their entire customer relationship through a patchwork of missed calls, voicemails, and sticky notes.
Enterprise companies had been investing in CRM platforms and omnichannel communication tools for a decade. Local businesses had a front desk phone and maybe a Facebook page. The technology gap between a 5-person plumbing company and a Fortune 500 was not shrinking. It was widening.
We set out to close that gap. First with review management, then with messaging, then with payments. By 2021, we had built a unified platform that let local businesses handle every customer interaction, from first text to final invoice, in a single inbox. Over 100,000 businesses signed on. We raised 400 million dollars. We were growing fast.
But we were also watching something shift.
What changed in 2023
Large language models went from a research curiosity to a practical tool in roughly 18 months. For most enterprise software companies, the response was predictable: bolt a chatbot onto the existing product and call it AI-powered. We took a different approach.
We had spent 9 years accumulating something no foundation model company had: millions of real conversations between local businesses and their customers. Appointment requests. Service inquiries. Price negotiations. Complaint resolutions. Follow-up messages that actually converted. We knew what a strong conversation looked like at a tire shop in Texas versus a medspa in Miami versus an HVAC company in Michigan.
So instead of building a chatbot, we built an AI employee. We called it Jerry.
What Jerry actually does
Jerry is not a chat widget that deflects questions until a human can take over. Jerry answers the phone. Jerry responds to text messages. Jerry books appointments. Jerry follows up with leads who went quiet. Jerry handles after-hours inquiries, and it does all of this in a way that sounds like the business, not like a robot.
When we launched Jerry in early 2024, we gave it to a few hundred businesses and watched closely. The results moved faster than our projections.
Businesses using Jerry saw a 30 percent increase in revenue. Appointment show rates climbed 56 percent. After-hours bookings, the calls that used to go to voicemail, jumped 80 percent. Lead-to-sale conversion rose 50 percent.
Those are not incremental improvements. For a local business running on tight margins, that is the difference between hiring another receptionist and not needing one.
Scale revealed the real insight
Today, tens of thousands of businesses run Jerry. And the most interesting thing we have learned is not about the technology. It is about the businesses themselves.
Local business owners do not want AI tools. They want employees who show up every day, do not quit, and do not need training. The framing matters. When we describe Jerry as software, adoption stalls. When we describe Jerry as a new team member who handles the phone and the inbox, businesses activate it the same day.
This tells us something important about where AI adoption is really heading. The narrative around AI in business has been dominated by enterprise use cases: coding assistants for developers, analytics tools for data teams, content generators for marketing departments. Those are real applications. But they are not where the largest volume of unmet demand sits.
The customization layer
One of the earliest lessons we learned is that local businesses are not generic. A car dealership in Dallas and a yoga studio in Portland have completely different conversational norms, pricing structures, and customer expectations. An AI agent that treats them the same will fail at both.
Our latest version of Jerry lets business owners customize the agent using natural language. A medspa owner can type "say injectable instead of filler" and the agent updates across every channel immediately. No engineering required. No support ticket. The owner speaks, the agent adapts.
This sounds simple, but it solves one of the hardest problems in enterprise AI: the last mile of customization. Large companies spend months on prompt engineering and fine-tuning. Local businesses do not have months. They need the tool to work the way they work, starting now.
What comes next
We are seeing AI revenue grow 300 percent year over year at Podium. That trajectory tells us the demand is real and accelerating. But the number I watch most closely is not revenue. It is the number of conversations Jerry handles that a human never needs to touch.
Right now, that number keeps climbing. Every month, more interactions resolve fully within the AI agent. Not because we are hiding the human option, but because the AI is getting good enough that customers do not ask for one.
The phone at that dental office in Phoenix is still going to ring at 6:47 PM. The difference now is that someone answers. It just happens to be an AI agent that knows the practice, knows the schedule, and can book the emergency appointment before the patient calls anyone else.
Local businesses have been underserved by technology for decades. That era is ending. And the companies that figured out how to serve them, not the ones chasing enterprise contracts, are going to define the next chapter of AI in business.