If your team spends half its days searching for documents and filling out spreadsheets you built years ago, how long will it be before your competitors automate you out of business?
Agility requires turning busywork into bandwidth so people can collaborate and think strategically instead of shuffling pixels. Today we’re exploring how no-code platforms and AI-driven automation make that possible.
To help me discuss this topic, I’m joined by Aytekin Tank, Founder and CEO of Jotform, and author of the book Automate Your Busywork.
About Aytekin Tank
I’m Aytekin Tank, founder and CEO of Jotform, host of the AI Agents Podcast, bestselling author, and automation enthusiast. When I was starting out as a software developer in the early 2000s, I worked for a media company in New York that constantly tasked me with coding web forms — like payment or contact forms. Tired of creating the same forms day after day, I was inspired to find a way to automate the process. So I created a tool that could do it for you.
In 2006, Jotform was born, and just a year after launch I was able to hire my first employee. Since then, Jotform has grown into a powerful automation solution trusted by over 30 million users around the world. As a team, we’ve expanded our product offerings with more useful tools, like Jotform Sign for creating e-sign documents and Jotform Apps for building mobile apps without coding. We’ve also introduced Jotform AI Agents — intelligent, real-time agents that help users complete forms, answer questions, and get the support they need instantly, all while staying aligned with their brand.
All of our products are made with one main goal in mind — making people’s lives easier and freeing up time for them to spend where it matters most.
Resources
Jotform: https://www.jotform.com https://www.jotform.com
The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow
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Don’t Miss MAICON 2025, October 14-16 in Cleveland – the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150“
Get a copy of Automate Your Busywork, the book by Aytekin Tank here: https://aytekintank.com/
Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom
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Transcript
Greg Kihlström (00:00)
Agentic AI has a number of potential applications, but what if it could not only save your customers time while solving their questions more easily, all the while elevating the roles of the humans on your team? To help me discuss this topic, I’d like to welcome Aytekin Tank founder and CEO of JotForm and author of the book, Automate Your Busy Work. Aytekin, welcome to the show.
Aytekin Tank (00:20)
Hi Greg, thank you for having me on your show.
Greg Kihlström (00:22)
Yeah, I’m looking forward to talking about all this with you. Why don’t we start, though, with you giving a little background on yourself and your role at JotForm.
Aytekin Tank (00:29)
So yeah, mean, for me, I was this developer, like a programmer two decades ago. Then I started, I bootstrapped my company and that I called it JotForm. And today JotForm is a pretty big company with over 700 employees and 30 million users. yeah, so we have grown as a bootstrap startup and
I learned a lot about business, marketing, customer service, all kinds of things. And happy to share my experiences.
Greg Kihlström (01:05)
Yeah, yeah, looking forward to this. So we’re to talk about a few things today, but I wanted to start with relatively new development here. JotForm AI agents, agentic AI, you know, top of many people’s minds. If not, if not ever, it feels like everybody, but I run in certain circles. So, you know, top of mind for for a lot of people now. Can you talk a little bit? You know, what what what does agentic AI mean for a company like JotForm?
Aytekin Tank (01:29)
Yeah, definitely. But let me first start with how we actually came up with this product. About two years ago, we were doing this hackathon within the company. And some of our people actually came up with this idea that because we are a form business and we serve over 50 million forms for our customers, what if we could actually fill out forms on the phone, like over voice or by just talking to a chat bot? Because forms are boring. We all know that.
People would prefer having a conversation over filling out the form. So we started working on this product. And we released it as a beta to some of our users. And we discovered something. Most of the people were actually using this as a customer service product. And only a number of users were actually really using it for forms. And we thought that, maybe we need to pivot this as a customer support product, customer service product.
And in February, we released JotForm AI agents to the world as a customer service agent, AI agent. So one of the things that we did was we started using it for our own support. So because JotForm is a large brand and we serve so many people, we always have this 200 strong support team. And most of our support is like ticket based, like emails or tickets.
And we also have like phone or Zoom support, but that’s mostly like enterprise level customer success. most of our business, most of our customers are like self-service and they just use ticket system. So we thought like, you know, why don’t we put our chat bots? Why don’t we offer our AI agents as a customer support option? And once we did that, like we started getting like, you know, 2000 conversations daily between AI and our support AI agent and our customers. And here’s the thing, we actually switched 20 of our support people to become these like overseer of AI. So they became like, know, they started reviewing AI. And their job was instead of answering customers, they actually started reviewing AI conversations and then between our customers and our AI. And then like grading them and finding the bugs and things like that. And we started with this low 25 % resolution rate. AI was sometimes good, but most of the time, we would cringe, like just give wrong answers, hallucinations, just couldn’t solve the problems, all kinds of things. during these three months, every day, we actually reviewed every single conversation between
AI agents and our customers. like, we, took all those learnings from them and then we started implementing solutions. I think one of the biggest problems with our product in the beginning was our, like the rack system, the knowledge base wasn’t really being utilized correctly. So we actually made it much better and that made a big difference. And we are, our users were also like getting all these benefits because we were improving the product, our users who were using these AI agents were also getting the benefits of these improvements. And then the next thing was we discovered that most of the time, tools were needed. The AI agent needed to do an API call to check something. If someone says, hey, someone submitted my form and I didn’t receive an email, then the AI agent would actually use the
API tool to make a connection and just query that email address. Just make sure that email was actually sent so that it can say, hey, this email was actually returned to us because your inbox was full or you should have received this. Can you check your spam? Because our records show that this email was sent. So in the past, our support team would do that manually. They would go to the tool and do that. And the AI started doing that. then all these things just started making a difference. And that 25 % rate gradually moved up to 75%. Right now, we are over 75 % resolution rate with our AI agent. And we keep improving it. But it’s getting harder and harder to find all those patterns, all these different things that’s all this. It’s not easy to find these big wins.
low hanging freets are already sold. our expectation is that we are probably not going to be able to go farther than 80%. But I think that’s good because one of the results of using AI agents for our support was for our customers, the support is very quick. they don’t have to wait. Our average response time before the AI was like one and a half hours. So people had to wait like one and a half hours on average to get an answer to their problem. And then if their problem is not resolved, they need to wait again another hour. So with the AI, what’s happening is that most of the people are actually solving their problems instantly by talking to the AI. And if they cannot solve it, they can actually connect to a live agent because we were able to reduce the support load on our system. Actually, our average response time was reduced to 45 minutes.
And also we were able to put more people on the live chat support. So this meant that if you have a problem, you talk to the chatbot and if chatbot cannot solve the problem, it actually transfer transfers you to the live human and then the live human solves your question and then you get much faster response. So I think this is a great example to how AI and human can come together to build a great solution. Auto automate many things, but also use that human touch to make sure that everything is taken care of. And so far, it’s going well. And with our users, we are now reached to around 5,000 conversations daily. Our customers are using the chatbots on their websites. They are buying phone numbers from us so that they can actually provide phone support. We provide all kinds of different like WhatsApp or Messenger, different platforms to provide these AI support. And that’s been growing as well. And today we are getting around 5,000 conversations on our user site, and their ratings are also increasing. And since we cannot review those, we can only review our own support, we kind of rely on our ratings and the AI-based reviews on that support system.
We are also seeing increase on that end as well because we are improving the product. And we are providing more tools. So there’s a reason that we didn’t call our product a chat bot or something like that. We use the name AI agents because we knew that the solution was actually really like the AI is not just giving answers, just like add-a-dance. We should use tools make decisions and that’s why we called it JotForm AI Agents.
Greg Kihlström (08:24)
there’s a couple of things I want to dive into a little bit more. And the first is that really is my experience, many people’s experience with chat bots are that, mean, you frankly, they’re, often dumb for lack of a better word. You know, they, can give simple responses, but they kind of end where, you know, someone hasn’t already thought through the potential response or whatever. And I know, you know, there’s some more like conversational AI that, that gets a little better and is trained. But I think, you know, the potential here with agents, it kind of goes back to what you were saying earlier, which is they’re able to do multiple tasks. They’re able to look beyond, you know, whatever database or whatever limited set of information that they’re they’re able to access. And they’re actually able to look things up or perform actions. So I would imagine and let me know what your thoughts are here. But like, I would imagine that also speaks to the resolution rate is just the fact that they’re able to do so much more and take additional multiple additional steps means that things can actually get solved versus just maybe there some answer is given or some link to some other website for more information. Is that is that accurate?
Aytekin Tank (09:27)
Exactly. That’s actually one of the solutions we did. So one of the problems was our user guides. we made our AI just rely on our user guides. And we discovered that many of the things at Jotron has so many features. It’s a product that’s two decades old. We added so many features. And many of the things are our support team knows on their mind, but they are not actually visible on the user guides.
In the beginning, what we did was we kind of improved our user guides. We kept adding more and more information to our user guides every time. So because our support team was reviewing every single conversation AI has, and if AI doesn’t give a good answer, then we would mark that, and then we would improve the user guides to make sure that the next time if that question is asked, it can be answered correctly.
We started with improving the user guides, but that wasn’t enough. We also started implementing this feature so that the AI agent can start doing some reasoning as well, like just like the reasoning AI LLMs agents, like the models, like 03, 04, mini. Those models can actually do some reasoning, and then they can do a web search. So we actually started, later in AI, to kind of go back to the old support tickets and read them if it cannot find the answer. Just like what a support agent would do, it will tell the user that doing some reasoning and then going to the ticket system, doing a search, and trying to find a solution. And this also helps our users as well, because we found that many users actually didn’t take the time to train their agents. But because we knew their websites, we could always go to their website and just
find something on their website and crawl it and find the answers and sometimes just try to find the answer by using the LLM can also do web searches. that just using that, you can just say, because we are using OpenAI and Jminai in the backend, these models can also do web searches. So we can actually say, here’s this website try to find this information. So it’s just like AI agent is kind of like a human. It’s just going to different places and searching for stuff to learn stuff. And all those knowledge, when it learns something, it can actually record that for future usage. But also, we started also building all these additional tools. So one of the most commonly used tools is appointment taking. It can integrate with your Google Calendar, Calendly.
so that you can actually, during the conversation, can take appointments. It can also fill out forms. That was actually the original idea, but that’s also used a lot by our users. If someone needs to apply for something, they can ask for questions, get their answers, and then when they’re ready, we can just take those answers in a conversation on the phone or on audio on their computer.
Greg Kihlström (12:22)
Yeah, so one one other thing I want to talk about here as well as going back to what you were talking about earlier is the idea that, you know, I know there’s lots of talk about AI, you know, completely replacing humans in the workforce. I don’t believe that I don’t buy into that. I mean, I think there is some some there are many things that AI does better than humans and vice versa. But, you know, you’re talking about, you know, the the AI being able to.
to deliver at speed and at scale in my mind and based on your description kind of elevates the role of the human in the, to not just be one-on-one with an individual customer, but to be kind of looking meta at overall and improving systems processes, responses, all of those things overall. Is that the kind of the future of customer service and agentic even is this role of almost like human managers of AI, but again, that elevation of humans in the roles from less like order taker to manager, I guess.
Aytekin Tank (13:21)
JotForm is a no-code SaaS service product. So it’s also free. So we have a huge number of small businesses. And small businesses don’t have the resources to actually hire people. So the decision is not between firing someone or anything like that. It’s usually not providing that service, not providing that support 24-7, or even just putting a form on their website. But with AI agents, now they are able to provide like
24-7 support. if you have, like in our case, we were able to utilize our support team better. Instead of answering the same questions, like I forgot my password. I didn’t receive my form submission. I lost my form. Instead of answering these very simple questions, that they are actually able to spend more time on more difficult questions and give better answers.
And we are actually seeing the results of that. They are able to respond much faster, and they’re able to provide much better answers to our users. And with AI, we are able to handle more of those easy tasks and then leave humans for more difficult things. It’s also like when you’re always dealing with all these busy work, it’s just like you forget to be nice to people, right? You forget to smile or just you try to like…
rush to make sure that you give them an answer quickly. So it just made our human support people their job much easier. And we are able to utilize the live chat more. Like we couldn’t put more people on the live chat. So it’s always, there’s always this like problem with resources. Like you don’t have enough resources to provide the kind of service you want to provide. But with AI, like you can provide a great service but also keep that human touch in the back end so that if you cannot resolve the problems quickly, humans can also take over and solve them. I think this applies to anything. I’m seeing every part of our company, marketing, growth, development, products, wherever I look, people are using AI and they are much more productive. And instead of doing all this busy work,
Instead of wasting their time doing these manual boring stuff, they’re able to like give those stuff to AI and be able to spend more of their time in things that actually makes a difference. And feel like the power of skyrocketed since people started using AI more and more within our company.
Greg Kihlström (15:45)
Yeah, no, I completely agree. Well, I took in thanks so much for joining today. One last question for you. Before we wrap up, I’d to ask everybody here, what do you do to stay agile in your role and how do you find a way to do it consistently?
Aytekin Tank (15:59)
I became this person that’s constantly using LLM’s AI to do deep research. In the past, when I had some free time, I would actually launch my Kindle and start reading some book. Today, I’m usually talking to a reasoning model or talking to deep research and just asking for something.
And then while I’m waiting for those deep research to end, and I’m just reading those stuff and I’m triggering this stuff. So I feel like I became much more productive because in the past, when I needed to research about something like about the market, for example, about different competitive landscape, about different options for solving a problem, in the past, I had to do research. I had to go to G2 to read all these reviews. But today I can just ask AI to give me the answers and just find the right products, use the right products. And this is so much more fun because you get those answers quickly. You become more agile because you can make decisions much faster. Like whenever I need to make a decision, I can go to ChetShip BT and start having a conversation with it. Even in the car, I can just start talking on voice, voice chat with the voice mode and having this like ask my questions, get my answers, like think about all these different options and just become more agile that way. So I feel like this, we’re living in great times.
