Ep51. Maddie Bell: The Rise of A.I. Agents

Maddie: I hope that helps for people that are trying to figure out what is really coming and what is really happening. And really the focus right now is agents that can complete workflows in a human like manner that have the ability to move across platforms and actually get you from, okay, this was a prospect and they went into my CRM to, wow, they showed up and we had a great conversation in a meeting.

Maddie: All while I sleep and do absolutely nothing.

Helen: From building billion dollar brands to pioneering the world of AI agents, meet Maddie Bell. Headquartered in Cincinnati, Ohio, Maddie is the CEO and founder of Scheduler AI. A patented, fully autonomous AI agent that instantly connects businesses with their best prospects and customers.

Helen: Maddie has over a decade of experience leading organizations and designing, developing, and launching breakthrough innovations at scale. She’s been responsible for billion dollar businesses, launched award winning advertising campaigns, earned P&G’s Lifetime Achievement Award in digital innovation, and actively developed patented AI technology.

Helen: While juggling her thriving career and building her family with three young daughters, Maddie saw an opportunity for AI to solve a universal pain point. The time consuming and revenue leaking task of scheduling meetings. She co-founded Scheduler AI with her husband, to create an AI powered assistant that engages clients when they’re most interested, coordinates meetings in seconds, and ensures they stay on the calendar.

Helen: I first met Maddie at an IBM Elevate conference where we both spoke on stage, and I was impressed with her presentation and enthusiasm. Maddie and her co-founder are both part of Cincy AI, the largest AI meetup in the region I co-host, and we’re so proud to have her in our community and at the forefront of this next wave of AI that goes beyond simple chat bots to intelligent agents that can execute complex workflows across platforms.

Helen: Today, you’ll hear how Maddie thinks about the different waves of AI we’re experiencing from the initial Chat GPT moment to the current phase of AI integration into existing software and the upcoming rise of AI agents. You’ll learn why buying technology tools will feel a lot more like hiring people in the future.

Helen: We also discuss the implications and opportunities of this technology, how to evaluate AI tools, how to automate processes and grow businesses, and the importance of responsible AI development. Join the conversation to learn more about the next evolution of artificial intelligence with AI agents. Enjoy.

Helen: Welcome to Creativity Squared. Discover how creatives are collaborating with artificial intelligence in your inbox, on YouTube, and on your preferred podcast platform. Hi, I’m Helen Todd, your host, and I’m so excited to have you join the weekly conversations I’m having with amazing pioneers in the space.

Helen: The intention of these conversations is to ignite our collective imagination at the intersection of AI and creativity, to envision a world where artists thrive.

Helen: Maddie, welcome to Creativity Squared.

Maddie: Thank you so much.

Helen: Oh, I’m so excited to have you on the show. Maddie and I actually were both speakers at the same conference last year at the IBM Elevate conference here in Cincinnati. She beamed in and was talking about AI agents which we’re going to dive into today.

Helen: We’re also part of the AI community here in Cincinnati, and it’s always great to have another AI female founder in the city and on the show. But for people who are meeting you for the first time, can you introduce yourself and tell us a bit about your origin story.

Maddie: Yeah, happy to. So hey everybody, my name is Maddie Bell.

Maddie: As Helen mentioned, I am the CEO and co founder of an AI startup called Scheduler AI. We help businesses instantly connect with their best customers and prospects through an AI agent that helps manage meetings at scale. And no, I did not wake up one morning long ago and say, “Gosh, you know what I want to be? The CEO of an AI startup that helps people coordinate meetings.”

Maddie: Obviously that was something that came along through the journey. So before this, I spent over a decade actually in brand management. So I worked at P&G and helped run some of our billion dollar businesses there and billion dollar brands.

Maddie: And it was awesome. I loved it. And I actually think a lot of, you know, what I learned there comes to life in what I do today. So it’s been pretty cool.

Helen: And since you left P&G to start Scheduler AI, what was the like aha moment? Or it’s like, I’m going to quit this job and like, jump in and take this leap of faith with Scheduler.

Helen: Can you tell us a little bit about that story?

Maddie: You know, it’s funny. Folks ask about that story a lot. I’m always happy to tell it. And it’s, you know, when you tell a story, you always pick highlights, right? And it almost sounds like those things happen, like step one, step two, step three, step four, step five.

Maddie: And like, that was it. But the reality is, the truth of the matter, right? Is [that] both my co-founder and I became entrepreneurs by accident. And the cool part about it was the reason we did, again, like I said, wasn’t actually as much of a shift from what I did as a brand builder, but more of a continuation of it.

Maddie: So let me explain.You know, at P&G, we learned to discover and value big ideas. And mind and heart opening insights that change the way people think about things, right? If it’s not insightful, it’s obvious and that’s not helpful, but [what] we would always look for is like what is that thing just under the surface that hasn’t been solved?

Maddie: And so I always, for a long time, have had a deep, deep reverence for that type of work and those type of ideas. And so the idea for Scheduler actually found my co-founder, who’s my husband as well, and I on the way home from church one day. At the time he was the vice president of data engineering and machine learning at Nielsen IQ, and I was running the Oral B business for P&G.

Maddie: So we had two big jobs, we had three kids, and we also had a dog. And the reality is finding time was a nightmare for us. And so we’d run into our friends and we wouldn’t be able to create time to have meaningful connections.

Maddie: And so one day in frustration, I looked at Mike and I said, “This is ridiculous. You should just be able to add your people to a chat, describe what you want to schedule and something somewhere should just do the work and say, this is when you’re all free.” And, you know, that was the human insight, right? That wasn’t a business. That wasn’t a software that, I mean, honestly, it was a conversation in a car.

Maddie: But what happened was, like most insights and ideas, it took root. And it didn’t actually take root in me first. I was perfectly fine. I have a hundred ideas a day. I figured I’d have a hundred more. And it was really my co-founder and husband, Mike who, you know, few days went by, weeks went by and he kept seeing the problem and he kept feeling like there should be a better solution.

Maddie: And the more we got into it, right, and we were like, wait a minute, scheduling doesn’t start with a calendar. It starts with context. It starts with a conversation, right? And eventually it got to the point where, you know, he came up to me and said, look, I know I can go build this and I want to take this shot.

Maddie: And so, you know, for those wondering, I wasn’t the first one to jump. It was really him. And, you know, at that point, we now we had an insight. We had an idea. He was able to inspire another engineer to come with him and build an MVP. And it started to really take off.

Maddie: And people were like, “Wait a minute. No, this is a new way of doing this. This could be a better way of doing this.” But even in those early days, we didn’t have a business, right? We had again an idea and an MVP and we realized that for this to become a true business we would need to bring the commercial side to life. Someone would need to come and bring this to market and obviously that’s where my skills were and you know, we had the conversation and of course we could have hired someone We could have brought someone else in; I still loved what I did at P&G, every single one of my brands are still so close to my heart.

Maddie: But when it came down to it, even though, you know, we talked about certain elements of the risk and we, you know, we knew kind of what that meant. It really came down to the fact that this was the one path that if I hadn’t walked with him, I would have looked back and said, “Yeah, but what could have happened?”

Maddie: And so I can’t say that it was necessarily on the timing that I would have liked, or I had all the answers I would have liked to have before making a jump like that or I knew it is, you know, I knew what I was doing. I had no idea what I was doing. I was terrified. But I knew that one piece, which was, I know there’s a real insight here.

Maddie: I know there’s a real idea here. I know from these conversations we’ve had people that there’s value in the market here. And I know that this is the one thing that if I don’t do it, I’m going to wish I’d known what would have happened. And luckily, the people and my people at P&G were phenomenal in every way.

Maddie: They were behind me in all the ways you could hope and even sent me off feeling braver than I think I would have felt otherwise. And so I’m forever thankful to all of them for that, for getting behind me and saying, you know, go show the world what P&Gers can do in the startup space.

Maddie: So it was a very cool story.

Helen: Oh, I love that. I love how it goes from a car conversation to a meaningful connection product. So that’s very cool. And at the time, did your husband who has spoken at our Cincy AI meetups, which is just a quick plug for Cincy AI, the largest AI meetup in the region.

Helen: So we’ve got to hear about Scheduler AI at our meetings, which is so wonderful. At the time when he was working on launching Scheduler AI, was this before the big gen AI phase? And is it all just, I guess, what is it, programmatic AI or like, where were you at in the AI hype cycle buzz and like product development embracing AI.

Maddie: Yeah no, we were pre. We like to make the joke we thought, you know, we thought AI was cool before AI was cool. We were original. So we, you know, he started working about a year before the large scale LLMs hit the scene. And it was really interesting to see how people responded because it very much so changed, right?

Maddie: In the very beginning, before, you know, OpenAI; the meteor had hit, you know, we were sitting in meetings being like, “All right, picture this, you talk to it. It reads what you say, and then it says something back, right?” And you know, we’d be sitting there and people would be like “Yes, yes, no, no, no, I don’t know what you’re talking about,” right?

Maddie: And so, obviously when OpenAI came, it was a huge tailwind in that suddenly everybody had an awareness. Now, the interesting shift in that was suddenly they would come talk to me and they would say, “Hey, so I heard you had a genie. I have three wishes,” right? And so their expectations, you know, shifted, right?

Maddie: I would argue that there’s still a spectrum, right? And we’re still finding awareness in that spectrum. But it has been really fun to be on that spectrum, right? To go from the days of no one had ever heard of this to now people are hearing about it for the first time to now everybody knows, but they’re really trying to figure it out.

Maddie: That’s been a thrilling journey. And what’s been really interesting is while that has been occurring, our own business has gone through similar metamorphosis, right? So, we started out as gosh, this is going to be that the little EA in your pocket that can schedule everyone’s meetings but as the technology evolved and as we explored the market and as we searched for where this technology is uniquely positioned to deliver business value, that path as well, you know, ended up in a completely different space than what we ever had talked about in the car that day, right? So, you know, our AI, we started integrating into marketing and sales pipelines to actually move leads into prospects, into customers, into, you know, ongoing customer success and actually start to manage meeting workflows at scale.

Maddie: And that took it from, hey, you know, I saved you 10 minutes of time to I delivered millions of dollars in business value to you and that metamorphosis for us was equally as dramatic.

Helen: I know on LinkedIn that you shared like a, almost one of those hockey stick curves of growth. So that was really great to see, especially, you know, Cincinnati pride, seeing another company here really grow.

Maddie: You know, it’s funny. We, you always want to create that hockey stick chart. No matter who you are and no matter what business you run. But what’s really cool is what’s behind that, right? Because a lot of people like to look to the right and see, Oh, look, it went up into the right, right?

Maddie: That’s the story. But the reality is the story is always on the left. And each of those hockey sticks are all relative at every stage of startup and they all have the left and they all have the right and so it’s definitely been a journey where we’ve had to see like gosh, are we gonna really understand the consumer enough?

Maddie: Are we gonna really get what we need out of the tech? Are we you know in all those days of… almost watching water boil. It is what creates the up and to the right, but it’s not as linear of a journey as again, the stories make it sound.

Helen: There’s a great little chart that circles around the internet of like the expectation of point A to point B, a straight line on the entrepreneurial journey, but like the actual, the reality is like, it’s this messy, like spin ball of disaster in the inside.
Helen: From point A to point B. So, I definitely can relate to that regard. Well, I wanted to really dive into AI agents. But before we do that, you’ve kind of talked a little bit about Scheduler AI, but I would want to give you the opportunity to do your elevator pitch, to let people know how it works and stuff.

Helen: And, cause I think one thing that’s really fascinating, not only did you jump into AI before all the hype but you’re even now, I think kind of at the cutting edge of the next wave of the gen AI craze. And that’s moving into the AI agents which we haven’t really talked about on the show. So that’s why I’m super excited to kind of talk about this next wave of AI agents that are coming.

Helen: But let’s start with Scheduler AI [and] what your agent does for people.

Maddie: Yeah, no worries. And I always, I like to cater the conversation to those listening. Right? If you need certain products, you know how to go look those up and get them. So instead, I’ll talk about it through the lens of; the nice thing about the use case that we have is if you breathe oxygen and connect with people, you probably have a scheduling problem.

Maddie: So sometimes it’s nice to talk about these technologies in a use case or a circumstance that a lot of people understand just because it almost acts like, you know, something that can help you walk through how to think about, you know, AI and what it is and how it can perform. And so, the way, you know, I would start to explain it and I’ll actually start to talk about, it’s probably, you know, I’ll probably not even, I’ll talk about my company, but I’ll talk about it through the lens of when Helen says, AI agents, like what are we talking about?

Maddie: So perhaps if you don’t mind, I’d actually start at the beginning of that. And then I promise I’ll use our use case so that people can ground themselves, but it probably is easier to understand what we do once you understand the category a bit more fully, would that be okay, Helen?

Helen: That sounds perfect, but the mic is yours. Yes, run with it.

Maddie: So first of all, I talk to a lot of people about AI. All the time. And I made the joke at the beginning that, you know, what people have thought about AI has rapidly evolved, right? Because the technology has rapidly evolved. And what we see when we talk to people is a wide variety of emotions behind this.

Maddie: You know, some people think it’s great. They get really excited. They think it’s like a magic genie. They think it’s magic, right? Some people think it’s extremely helpful, right? Like it’s a little helper robot that does all your stuff for you, and some people are like this is not a good thing, right? Like we are giving way too much autonomy to bips and bops and boops and we should not be involved in this right? Like they’re getting those vibes of those robot movies that you’ve probably seen and I think, you know, part of that just comes with it is very new and we are all kind of, you know, lots of things are moving and evolving as we go.

Maddie: And one of my friends that I did a podcast with said, the best thing for AI will be when it gets boring again. Right? Some of the elements of this technology are no more complicated than a car engine, right? We use car engines and go to work every day. But we don’t give much thought to our car engines because they’re boring.

Maddie: So who knows? I don’t know. I can’t pretend to say what I know about whether it’s boring or not complex or not, but the way I like to start to kind of walk people through an understanding of AI, where we are and where we’re going is in three phases. So, the first phase that we’ve seen with AI is the one that we all experienced together.

Maddie: And that was, the meteor hits the earth and we’ve got Open AI releases GPT. There was a lot of AI before that, to be clear, right? There was AI in factories, there was AI in but this was the real event that made everybody have access to a true artificial intelligence experience.

Maddie: And that experience was me and this chatbot. So think about it as like, I have this cool chatbot, it’s helping me write poems about, I always say poems about flamingos in iambic pentameter. And that was the first wave. That was before now. The second wave that we’ve seen is we’ve taken that experience, that me and my chatbot experience, and all of these technology platforms have integrated it into their software.

Maddie: So we call the current phase that we’re in, the integrated AI phase. You will have noticed this if you get on LinkedIn and see, “Write this post with AI,” or you get in Google and it says, “I’ll do this for you in AI” or Facebook, you know, so you see all of this generative AI popping up within platforms that you largely already use.

Maddie: So when people say, well, what is the next phase? What they’re typically asking about, and what most people are now saying is the next phase will be agentive AI. So again, remember, some people are going straight to Terminator. They’re like, there’s going to be a robot at my Christmas party. I don’t know that’s the case, right? So let me explain.

Helen: Well, humanoid robots are on the rise.

Maddie: They are on the rise.

Helen: We might get the robot sooner than we expect.

Maddie: We very much could. I just, I don’t know, right? Like you, you’re going to get to choose if it’s at your Christmas party. Let’s put it that way. But truly, truly the one that is happening is the next phase now is agentive AI, which is this idea that no longer is it contained to just me and my chatbot.

Maddie: No longer is it my chatbot implemented into my tools, but now it is an AI that is able to transcend those tools and move across workflows to achieve very specific objectives. And so, rather than it being a co pilot, right, you and me going to achieve something and you’re making me more productive, you will see and continue to see the rise of autopilots, right, specific agents trained to execute workflows across platforms, on behalf of humans by taking their coaching and criteria to go get that stuff done.

Maddie: And so we talk about, right, like very soon buying technology will feel a lot less like picking up a piece of software and a lot more like hiring, you know, an entry level person to do some of these workflows and to do them consistently and to do them fast and to do them 24/7. And so, when I say all that, it really allows me to then explain what we do.

Maddie: So, when you think about scheduling, you are immediately talking about lots of platforms, right? Because we’re, scheduling doesn’t start with a calendar, it starts with context, it starts with communication. So people are having conversations across messaging platforms. They’re booking things across different calendars.

Maddie: They are needing to move people from point A to point B, right? So what our AI does is it integrates directly into business systems that people use. So if you’re in a B2B company, you use a CRM. If you’re in a recruiting company, you use an applicant tracking system. So it integrates and it takes triggers from those systems that say, “Okay, yep, this person needs to get into a meeting,” and then it executes AI workflows.

Maddie: So it engages that person in a conversation to say, “Hey, here’s why I’m reaching out. Here’s why I think you need to be in a meeting.” It might ask them some questions like, “Hey, to make sure this is a good fit, do you, you know, do you live in Ohio? Do you have this many people in your company? What got you interested in us? I noticed you were interested. What was that interest?”

Maddie: So it engages them. It qualifies them based on what they say. It routes them to different people inside the organization. Like who does this person need to actually go to? Then it books them, right? By picking curated time proposals and having a conversation about when they’re free.

Maddie: Then it reminds them. Then it rebooks them if they need something to change. It captures the meeting notes. It makes sure that the follow ups happen, right? So, all of a sudden, you go really far beyond scheduling, and yet you don’t. Because all of that is what humans do to schedule and that to me has been one of the most interesting aspects of building a product like this, because when we went into it, we had the traditional view of scheduling in the back of our minds.

Maddie: I say, “Are you free on Tuesday?” You say yes or no, and then we eventually get to a time or you fill out a link and then you pick, right? Those were the ways we did it. But what we weren’t very aware of, was all of the decisions that were happening in our brains and in our actions to create a human like scheduling experience, we were having a conversation.

Maddie: We knew the intent of our meeting. We knew there were all these details that were happening in our autopilots. And so the reason these AI agents are most likely going to be very customized and very focused is because the people building them are working to bring in those nuances into those experiences because creating human like workflows is a lot harder than people think because most of the workflows they do every day, they’re doing on autopilot.

Maddie: And so those of us building are having to kind of figure out, okay, what is the true and authentic autopilot here? So that is why when people are super concerned that, you know, we’re all going to be replaced by robots, I’m like, guys, we are still human. We are still irrational. We are, you know, like bottling that up is hard enough.

Maddie: And then we, you know, we’re still crazy. So I’m less concerned about those things just because of how hard it has been. But yeah, I hope that helps for people that are trying to figure out like what is really coming and what is really happening. And really the focus right now is agents that can complete workflows in a human like manner that have the ability to move across platforms and actually get you from, okay, this was a prospect and they went into my CRM to, wow, they showed up and we had a great conversation in a meeting all while I sleep and do absolutely nothing.

Helen: It definitely sounds like a magic genie to me and maybe our listeners, cause anyone, whether you’re a creator or an artist or, you know, one of the builders who listens to the show, we all have calendar issues, no matter what.

Helen: So, this is definitely, hopefully exciting. So what are the implications because, you know, I think one of the, in terms of AI first devices that have come out, we’ve seen like the rabbit and that seems to have some of the agent capabilities. But what are some of the implications?

Helen: And if you could speak to like the good and the bad, I’d love to kind of explore both sides of the coin as we’re entering this next wave of AI agents.

Maddie: Yeah, I mean, I think anyone who is building AI, using AI, anything, I mean, responsible AI always needs to be part of the discussion. And honestly, I don’t know that’s a change, right?

Maddie: Because when we think about technology, when we think about innovation, it always comes with responsibility, and it always has, because these tools can be used for tremendous good. Right? You think about, I remember I was fortunate enough to be, you know, I worked and was, you know, traveled out to the Googleplex in the very, very early years.

Maddie: And I remember hearing their leadership talk about freeing the world’s information, you know, to people all over the world that had never had access to that, right? Like the amount of good that can do is, I mean, you can’t quantify it.

Maddie: And when I see the fact that these AI tools allow small businesses to act like big businesses, they allow people like women and minorities who would never describe themselves as technical because they don’t write Python, but those women and minorities might be more relational. They might know how to prompt better and they might actually deliver better technical outcomes through their experiences than someone who has been technical, right? Who we would define as technical.

Maddie: And so I think the access that AI can provide to people, to businesses, is on that same level of some of those innovations we saw years ago, right? When Google was trying to unleash the world’s information, you know, across the globe.

Maddie: That said, since that same moment in time, you can also point at great evils done by technology, right? By technology in the hands of people that want to misuse it and abuse it.

Helen: I guess like when it comes to like the AI agents, I did not read the article. This is more headlines as full disclaimer; that, you know, one of the potential implications, which, you know, I really don’t have a strong opinion about it yet, but I’d love to get yours is like, that these AI agents to potentially complete a task might mean hiring humans, like the gig worker economy might have the AI agents potentially hiring people to execute some of the tasks.

Helen: And I and I’m really not sure like how to think about that. So I’m curious, like your thoughts, since you’re more in the AI agent world than I am.

Maddie: I want to make sure I ground myself in kind of what you’re remembering. I think cause I’m not as familiar with it, but I definitely think, you know, there’s conversations about AI and recruiting and even like, you know, I remember one where it was like scanning resumes, right?

Maddie: And are we protecting ourselves from bias? And like I said, I mean, I think those are areas where at the end of the day, it is up to the humans in charge to become very aware of what tasks we are assigning. But what’s really interesting, and this was something that helped me a little bit, it is trying to bottle up a human experience..

Maddie: So oftentimes, like when we go to build, the first question we will always ask, what would the humans do? What would the humans think are right? And what’s really interesting, right, because all of these are still rules and requirements and prompts and guidances, is again, it’s a little bit different than “if then” code where it’s like, I literally get to say, “if then” right, it’s very, you know, like that was true code.

Maddie: It is now more like training someone to be an employee, which when you think about, oh my gosh, like AI could have bias. If we’re being honest, humans do too, right? Like if we’re being honest, AI can make mistakes. Humans can and do too. And so you say, “Well, okay, so then it’s absolved of everything?”

Maddie: Absolutely not. You know, you should fire AI just as quickly as you should fire the humans that do the wrong things and you need to have, you know, exactly, like we have governance in place for our own humans. If you do these things, you are fired. And so, but the [difference] is we’ve had a lot of time as companies and organizations and leaders to determine what are the rules for our humans.

Maddie: We need to invest that same time in developing what are the rules for our AI agents. And so that’s where, you know, you 100% need to think about, you know, for example, if you had a highly secure data set, would you allow your new hire to go in, read it all and talk to anybody about it? Even if they were a human? Of course you would not.

Maddie: You should not do that. That was a terrible idea. Or if you had someone that wasn’t trained well and properly and hadn’t demonstrated a certain level of skill, you wouldn’t put them on a specific project. And so that’s where I think, you know, all of these things of thinking about it, they should all start with this question: How would we solve this with humans?

Maddie: Okay, that’s what’s gonna get us to really, really good solutions for how [we would] solve this with AI. You know, humans go through bias training. We, you know, we need, “Okay, great. What’s the bias training on this model or what are you use, what’s the use case,” right? It’s very hard to show bias on, you know, you’re in a CRM and I’m supposed to spend time with you and schedule a meeting?

Maddie: Like, that’s not really a biased experience, right? Versus, well, if you’re having your AI decide the safety conditions [etc.], so it also depends on where it’s applied. Which again, can feel so overwhelming because the road has not been traveled yet. But what we find really helpful is being like, there’s actually more thinking there in most organizations than people realize, because you have had to manage variable, volatile, unpredictable beings for a long time.

Maddie: They’ve just been humans, right? So, now I will say the nice thing about AI is it listens really well, right? So it’s, you know, it still needs that correction, but it takes correction pretty well.

Helen: Oh, one question for you too. Cause I know you know, from a consumer standpoint, and I use that as a very broad term that it can be very overwhelming with how many AI tools are like popping up left and right.

Helen: And you’re building one of these tools and from the seat that you sit, you know, it’s like, how do you, cause any of them, even though, you know, some of them are super easy to, you know, to start using, some, it’s more, you know, a bigger digital transformation of layering it into your operations. But from the seat that you sit, how would you advise people to evaluate, you know, the responsible AI of these tools?

Helen: Because I don’t think that those are always as obvious. And then also, how do you guys set yourself apart in all the noise with all these tools popping up left and right? Because, you know, AI can be so overwhelming for so many reasons, but even like figuring out which toys to play with I think is one of the things too.

Maddie: Yeah, so I’ll take the question in a few parts. In terms of tool proliferation, a hundred percent. We have seen, I mean, again, I came from a world where we were the only AI tool on the block for a long ways, right? There were others, but it wasn’t something that was every day to, you know, every six seconds, there’s something new.

Maddie: I make the joke that, and I can make the joke because I was at P&G. It’s like walking into the hair care aisle, right, trying to find shampoo, you know, you know, you need a specific shampoo and you know, you need a specific hair care regimen, but lord bless; it is like “What do I pick?” And I think the reality is one of the biggest challenges of this next phase of using technology and using tools is, in a world where the tool is designed to deliver the outcome, right?

Maddie: You don’t do anything. It’s designed to deliver an outcome. What makes it hard is lots of people can claim the same things. Right? “So I do this. Well, I do this. Well, I do this.” But we all know those models could have been built very differently. They could have been trained very differently.

Maddie: And so that’s why I go back to, fortunately, unfortunately, I don’t know how people take it; buying technology tools is going to feel a lot more like hiring people in the future because they’ll all come in and say, “Yes, I will do this for you.” And on that same theme of what we just talked about, well, how would humans handle this? Well, you would ask them about their experiences. Their capabilities.

Maddie: How much time have you spent on this? What results have you delivered to date? How, you know, how do you think about these specific scenarios, right? Are you someone that’s thinking deeply about these specific scenarios? Are you someone that’s just trying to, you know, give you the top line answer, right?

Maddie: And I think that’s where you quickly will kind of be able to start figuring out, right, who’s there? And, you know, that doesn’t mean, “Oh gosh, Maddie, now you’re telling me every one of my tools, I got to go do a personal interview on,” like, no. We guarantee the results of our product to our customers because we stand by it, right?

Maddie: So you want to be looking for companies that can say like, “This is how we’ve thought about these use cases. This is how we thought about these problems. This is how many of these problems that we’ve solved.” And some of it’s going to be trial and error, right? You’re going to use tools you like and use tools you don’t.

Maddie: That is the case today already. So net, I would say, how do you figure out a good tool? Part of it is thinking about it more as how am I hired? How would I hire a person through this? If they all said they could do the same things, what would be the real proof that I would be looking for or the conditions in which I could generate proof, right?

Maddie: So, you know, they’re going to guarantee their product or they’re going to give me a trial. The second thing that you mentioned, which is a little bit different is how do you actually go about choosing? Like, how do you know what you need? And to me, that one is like, if I go up to a business leader or a person and they’re like, “Hey, I know I should use AI. Like, I understand that.”

Helen: I get these questions all the time. People are coming to me for AI consulting, and this is like the starting place where I think a lot of people are right now.

Maddie: Yeah. They’re like, “I know I should use this. Like I’ve already, I got it. Like, but where do I start?” And what I always tell them is the technology and the expectations of what it can do have changed, but the fundamentals of how you win in marketing, or sales, or customer success, or design… those haven’t changed.

Maddie: Because people haven’t changed. And so what I like to have people do is start with workflows that you already know work. You’ve already designed them in such a way and crafted them in such a way that you know they work, but you’re throwing manpower at it, right?

Maddie: So again, we can use my example, just as an example, there are entire marketing teams that have built that customer journey, right? They see my post, they go to my site. And they get all the way to the door to say, “Yes, I’m going to meet with you.” And then you’re like, “Great. Fill out this calendar link.”

Maddie: Right. And then your prospect does. So they’re like, “Okay, fine.” And then they need to reschedule and then the human needs to jump on and then they’re probably not qualified, right? So you have these humans jumping into this customer journey because you know it works. So, the tools that you’re looking for are the ones that help you execute those playbooks that you know work at greater, faster, better scale.

Maddie: So suddenly you can take a process that you’re like, “Man, I want the customer journey to look like this. I’m going to create this content. I’m going to get them to my website. They’re immediately going to receive a personalized outreach. They’re going to have a great conversation to figure out what they’re really looking for. Then I’m going to get them with the right person, right?”

Maddie: And rather than having seven humans glue that all together, I’m going to spend the time and galvanize that into a platform that can do that 24/7, seven days a week, to my specification. Because I’m the boss and I already know what we need to be doing.

Maddie: That’s what I talk to people about is like, don’t look for a new thing to go do. Look for the things that you’re doing, but you’re having to put more input into and try to galvanize them into an automation that then works for you at scale.

Helen: And when it comes to, because you did mention responsible AI and one thing I’m very proud of, Cincinnati is leading the way with responsible AI and in so many ways.

Helen: I mean, what I tell people is to like, look at the terms of service and stuff, but you know, a lot of these tools, how would you evaluate the data security and privacy and responsible AI, you know, I go to the terms of service, let’s see what’s on their website, but there’s not really like a seal or anything like that to help people right now to understand what meets certain thresholds or not.

Helen: And to be honest, a lot of the big companies are releasing products that [are] not very responsibly either. So it feels like the wild, wild west, but for people who are concerned with this, do you have any other pointers that you would share?

Maddie: You know, obviously it’s… So number one; if you’re concerned about the privacy or the tool, you should ask and you should expect a response, right?

Maddie: You know, when people ask us, they’re like, Hey, you know, cause we talked to companies [that are] very, very big. And we talked to companies [that are] very, very small. And I came from a company that was very, very big. So even getting a wifi password at my company, I mean, you had to do some work there, right? So, I get it, right.

Maddie: I get it. And they’d come to me and they’d, especially the bigger ones that we’ve worked with and say, “Just so you know, I don’t know if this is going to work because, you know, we have. A pretty intense IT security review.” And our response has been great. Send it to us. Because that should be the response, right?

Maddie: And we’ll go fill it out and we pass them, right? And so the first thing I always encourage people to do is, if it’s something you’re interested in, ask the company. Now not every company can go say, “Okay, yeah, like, let me show you and walk you through it,” right? Because obviously we’re doing big infosec reviews for fortune 500 companies.

Maddie: You know, we may not be able to do that for every company that we meet with, but again, email us, ask the question. And if you’re emailing companies and they’re not answering your questions, then maybe you have your answer at least right now when we don’t have a universal guidance, right? Like, because even some of our previous infosec reviews, they weren’t actually designed for this.

Maddie: And I think a lot of that will come. I certainly do know that people are working on it. But I just like to say, look, like when people come to us and say, we have security requirements, we say, great. So do we, right? We, you know, it’s funny.

Helen: Yup, I love that.

Maddie: I think, you know, there, sometimes it’s hard, right? Because there are very few people that have met AI builders, right? We consume a lot of products and we’ve never met the people that created them. But sometimes it’s helpful for people that have never met an AI builder to know that, gosh, some of us live in Cincinnati. We have kids, we send them to school and we believe in responsible AI and our ability to shape that just as much as anybody else does, just as much as the consumers do.

Maddie: And I think, you know, I take a ton of pride in that personally, that like, this is something that, you know, I’m fortunate my co-founder was again in his previous position. He built tools for the world’s largest retailer. They had to be secure.

Maddie: And so he’s always had that as part of the mission and how we do this. And I think, you know, it’s interesting, right? Because even when you think about the role of AI. So our AI does engage with customers. It does, you know, work to understand them and see if they can get them into meetings and that can be abused too, right?

Maddie: Some people spray and pray. They use these chatbots to just throw at people, right? You’re like, “I’m never going to talk to a person at a company again. I’m just going to get a chatbot screaming at me,” right? And we made the call as a company that our mission is to create meaningful human connection.

Maddie: The role of our AI is to connect the right people at the right time for the right reasons, and I do believe AI plays a role in that. There are very few humans coming to me saying, “I just need to reschedule all my meetings. Like, I have to do that or else it’s not authentic,” right? Like, like, trust me, it’s fine, right?

Maddie: Or I’ve, I have very rarely heard someone say, “You know what? I don’t want you to reach out to me right away to help me with my problem. I want you to wait 24 hours till the person gets back to their desk and can call me.” Right? But they, but what we do hear is, “Okay, you didn’t help me with my problem. I want to talk to a human now.”

Maddie: Like, and so I think those nuances of responsible AI of, hey, if you want to know about the security, ask, send an email, try to get a response. If you’re at a big company and you have requirements, keep your requirements. Don’t drop your requirements.
Helen: Yeah. Lord no, please do not drop your requirements for AI.

Maddie: No. We’re not doing that. No. That’s like letting the new hires into the CEO suite and saying no rules. Like what!?

Helen: And I really appreciate you talking about the values of the builders. Cause you know the bias that humans come with, but a lot, I mean, I had a conversation with someone who’s working on AGI.

Helen: And in that conversation, it was just so clear that this gentleman was building his values into this AGI. And that has profound implications. If it really takes off and even among the large LLMs, you’ve got Anthropic who has different values because the founders left from Open AI. So I think, you know, you said that enough people, a lot of people don’t know the AI builders.

Helen: I think we should all really start to get really curious [about] who are the people behind the tools and the values that they’re embedding into it and how they’re getting – Anthropic is actually interesting because they have their whole, I forget what they call it, like Bill of Rights or whatnot that they put into it, but to really get clear on that as well as we’re navigating this wild, wild west together.

Helen: I think that’s a very important point as a takeaway too.

Maddie: Yeah, I mean, you know, we’ve had, at the same time though, all of our technology that has shaped human history has been built by someone. And that person is probably different than you and me. But these things are tools and the people who use them at scale will ultimately, the people who consume them are going to be the people that shape them.

Maddie: And so yes, it can feel a little nerve wracking right now of like, “Oh, gosh, these builders have all the control.” But the reality is we build for someone and it’s the people who consume, and it’s the people who ask, and it’s the people who are curious. I can say that the path that my technology has taken.

Maddie: Is not one I could have ever imagined, and it was a path shaped by people, by customers that had no, they didn’t know how to build AI. They didn’t even care about AI. They just wanted to go solve their business problems, right? And so I do love to remind people that like, “Hey, guys, you are the consumers. It’s okay to consume. It’s okay to give your opinion. It’s valid. It’s wanted. It’s desired.”

Maddie: And, you know, it is also the responsibility of the consumers to consume responsibly. And, you know, I do think that how you consume AI and what use cases you consume need to be, you know, thought out like we always there’s a book by Dan Martell.

Maddie: It’s great. It’s called “Buy Back Your Time.” And the whole premise of the book is that if you’re a successful marketer or a successful business owner, you don’t want to go into a business problem and say, “You know what I’m going to do? I’m going to hire a VP to solve this.” You want to always be buying back the lowest common denominator of your time, right?

Maddie: Like, as soon as I know how to do something and I know it works, I outsource it, and then I go to the next level up, and then I level up, and I level up, right? You don’t hire someone to go figure out your problems. You figure them out. You hire people to keep them good, and you move to the next one. And I very much so feel like that with AI, right?

Maddie: Like, we should not be hiring AI to solve our business problems, guys. What, no? But there are things that your organization is doing that they don’t need to be doing, and you could buy back their time to go do more. And again, what I love about the theme of this conversation is what would humans do? That’s what we do.

Maddie: So if for those that are feeling overwhelmed by this, I felt overwhelmed by this. Everyone’s feeling overwhelmed by this. I would just encourage you [to] be curious, try things in curious and safe ways, right? We’re not curious on a highway. Do not be curious on a highway. That’s not a good idea.

Maddie: We’re going to be curious on a low traffic road where we can just kinda check it out like that’s okay. Create safe space to be curious; automate things that you know work and you just need to galvanize them and give your opinion. And give your opinion to the people building.

Helen: And going back to the chat bots, and I know we’re getting close to the end of the interview, how you were describing the user experience. I kind of see there’s so many different tools popping up left and right in AI land. I have a feeling that the user experience will be very similar to the initial like phone trees, where I don’t think people actually mind tech if it’s convenient, the utility of it, and it’s easy and can answer the questions.

Helen: Like, I don’t mind talking to a chatbot customer service if it gets the answers, but if I’m saying “Human, human, I just want the effing answer,” then, you know, I can go from like, “Oh, this is a very helpful chatbot. Like it’s serving its purpose in what I’m doing.”

Helen: Yeah, to like, “Ah, you know, I want to throw my computer out the window because this is such a miserable experience.” And I have a feeling that we’re going to see what these AI tools, the whole breadth of, you know, the phone trees and the customer service, from the good to the bad, left and right too. So hopefully we’ll have more of the good tools out there making our lives easier.

Maddie: You know, it’s funny. I did a post on this. And the other thing that I would encourage folks with is, I did a post about builders should always build AI for their customer’s customer, because if you’re building AI to serve, right, and it’s in any sort of capacity where there’s a third person involved, right, if it’s customer success or sales, you might be able to make it a month by getting the result and giving the customer’s customer an unpleasant experience.

Maddie: But I highly doubt you’ll make it two, and I know you won’t make it three. Because at the end of the day, it goes back to the human piece, right? Which is, if I’m buying a piece of technology to serve my customer with, and my customer hates it, or doesn’t respond to it, or leaves my business because of it, do we really think that technology is going to last?

Maddie: And so we are actively seeing that right now. Like we are seeing that all of these again, these AI rag chatbots, they surfaced, they got on every website, but then, you know, they’re going, [robot sounds], the customers like, “That’s not even the question I asked. I don’t even want to know that. Please stop.” Right? So what’s going to happen, right, is I do believe in market maturation, in that we also have to remember that the supply and demand curve goes both ways.

Maddie: Right. So supply, there’s a lot of new interest. We’re all trying things, but eventually that curve will mature. And I do believe that what will be left and true supply and demand are products that have committed to giving not only a great buyer experience, but a buyer’s buyer experience. I think those are going to be the AI companies that survive and advance and honestly change the world for the better.

Maddie: So, you know, we have a saying in our business, the number one thing you can do to delight our customer is delight theirs. That is what is going to inspire customer loyalty. And customer loyalty is good, is what would take us from being a small company to a big company. That’s the one thing that we have that, you know, if you take the time to build it, it’s hard to have to give it back.

Maddie: So, I do think you’re right that we’re in a point of time where there’s a lot of frustration because we’re in a point of time of new and we’re trying things, but I do have confidence that the natural laws of economics will come into play and that you’ll start to see the companies that have committed to serving the buyer’s buyer and serving their customers and really getting that human experience right, I think you’ll start to see them and maybe not some of the others, but what do I know?

Helen: Well I’m really rooting for you and Scheduler AI.

Maddie: While I’m watching this in a couple months, I’ll be like “Man, I was wrong!”

Helen: One question I like to ask all of my guests is if you want our listeners and viewers to remember one thing or walk away with one thing, what is that from today’s conversation or related to the topic?

Maddie: Yeah, I think the key takeaway I would leave everyone with is the fundamentals of how to deliver great work, whether it’s marketing or sales or business.

Maddie: Those fundamentals haven’t changed because people haven’t changed, but the tools that we have to bring those strategies, those insights to life have absolutely changed. For the better. You are capable of doing something today that you weren’t. Even Sam Altman, who started OpenAI, said the next billion dollar company could be founded by one person.

Maddie: And that can seem very overwhelming. There is certainly risk to it, but it can also be really inspiring for that one person that’s always had the idea that they want to go pursue, because it is now possible for them to go do that. So go through the learning phase, keep your fundamentals, ask yourself, how could I make this process that I know works, work better, faster, stronger.

Maddie: And please let me know when you create something really, really cool.

Helen: Amazing. Well, Maddie, I feel like we could go on and on, but it has been such a pleasure having you on the show and just so proud to have you in Cincinnati and part of our AI ecosystem and one of the companies leading the way with responsible AI and building that into Scheduler AI.

Helen: And for anyone who speaks their interest with this episode, we’ll be sure to link to Scheduler AI if you want to test it out and see the magic at work. But thank you so much for coming on the show and sharing your insights and this wave of AI agents that we’re entering.

Maddie: Thanks, Helen. Thanks everybody.

Helen: Thank you for spending some time with us today. We’re just getting started and would love your support. Subscribe to Creativity Squared on your preferred podcast platform and like a review. It really helps. And I’d love to hear your feedback. What topics are you thinking about and want to dive into more?

Helen: I invite you to visit CreativitySquared.com to let me know. And while you’re there, be sure to sign up for our free weekly newsletter so you can easily stay on top of all the latest news at the intersection of AI and creativity. Because it’s so important to support artists, 10 percent of all revenue Creativity Squared generates will go to ArtsWave, a nationally recognized nonprofit that supports over 100 arts organizations.

Helen: Become a premium newsletter subscriber or leave a tip on the website to support this project and ArtsWave. And premium newsletter subscribers will receive NFTs of episode cover art and more extras to say thank you for helping bring my dream to life. And a big, big thank you to everyone who’s offered their time, energy, and encouragement and support so far.

Helen: I really appreciate it from the bottom of my heart. This show is produced and made possible by the team at Play Audio Agency. Until next week, keep creating.