Podcast Episode 20

Innovation and Integration: Crafting the Future of Content with AI 

The conversation between Ryan Davies and Monica Landers on the AiFounders podcast delves into the dynamic intersection of artificial intelligence and content creation, offering valuable insights into the evolving landscape of technology integration. Monica Landers, CEO of StoryFit, shares her expertise in leveraging AI to enhance storytelling and audience engagement in the entertainment and publishing industries. Through thought-provoking dialogue, they explore strategies for successful AI implementation, emphasizing the importance of balancing automation with human creativity and fostering a culture of innovation within organizations. This enlightening discussion showcases the limitless possibilities of AI while highlighting the critical role of human collaboration in driving future advancements. 

Monica Landers - Founder & CEO at StoryFit

Listen to the Episode Now


Ryan:  Welcome everyone to the AiFounders podcast show. Our podcast is dedicated to celebrating the remarkable accomplishments of AI innovators, entrepreneurs, and visionary founders and the captivating stories behind the movements that they’ve built. I’m Ryan Davies, and I have the honor of hosting today’s episode on innovation and integration, crafting the future of content with AI with our special guest, Monica Landers, Monica. Thank you so much for joining us here today.

Monica: Thank you. It’s great to be here, Ryan.

Monica’s Background and Experience

Ryan:  I’m really excited about this one. We’ve already had a great chat leading into this. We’ve kind of talked about where we’re going on this chat. I think this is going to be one of those ones that could go any number of directions, but everything we talk about is gonna be fascinating and very much directed to our audience in terms of what they’re looking for in this fit of AI. How do I bring it into my business? How do I make sure that I still keep people first? How do I, you really, you know, put it in a place to succeed and my people to succeed because of it? And we talk about this and balance that with content. Monica is the perfect person to have here for us. So, Monica, a strong innovator corporate strategist with 20 years of experience in content-centric businesses from Good Morning America to demand media with, you know, 100 plus million monthly touches, is there. An AI business executive adapted strategy, people, systems management, and product execution from start-ups to large companies and a proven ability to maximize people and resources to do things that have never been done before. She is the founder and CEO of Story Fit, which delivers artificial intelligent insights and machine learning solutions for the entertainment and publishing industries. She really focused on, again, measuring impact and having a direct impact on the insights content performance and sales of media Monica. I think you probably can color up much better than I can in your background. But I wanted to give a little bit there to kind of kick us off. Tell us a bit more about your background and the experience that you have in AI technology and its integration into various businesses.

Monica:  Sure. Well, thank you for the intro. The thread that connects everything I’ve done is really having 1 ft in content creation and 1 ft in technology. I think that that connection is tricky sometimes because creatives and technologists often speak different languages and so trying to connect to make sure that we’re building technology that creatives can use and that enhances their work. At the same time, it helps the communication of what creatives are asking for and gets a little bit more. An engineer speaks so that what they want can really be built. So that is where I focus my energy and have since the beginning. I started out with ABC News and produced for various news shows, including Good Morning America, for many years, and I just feel so lucky to have started my career that way. It was so fantastic to kind of land in the middle of big stories and have just one focus: how do we tell this story, and how do we get it on the air in whatever X number of hours? And it’s interesting in retrospect now to have done that kind of work with what in my twenties was infinite resources, not really, but it felt that way. It’s like just getting the story on versus now working for, you know, work at the start-up community, where you have very limited resources. But I think that the mental exercise that you need to do in either place is the same, and that’s to not hold just one. Don’t let one influence stop you from creating and thinking of new ideas. So, in this case, resources are being able beyond resources about what you really want to build and how it should be built. What is its use case? What kind of best-case scenario could we deliver? It would be really helpful. So, I’m glad I got to work that muscle early in my career. But, once I left news for start-ups, I’ve really been managing engineer teams and content teams for years ever since this, this StoryFit, so currently, we have built a technology that basically predicts the audience from scripts. So we work with large studios and networks and streamers as well as independently to ingest the story from the script stage but deliver information as if from an audience who’s watched the finished product. The reason why this is important for this industry is that for example, if I take the kind of large studios, you might spend a million on acquisition and time and by time, I mean years in development and then you spend 20-40 million in the production part of this, and then you start getting some early audience feedback and even that feedback can be very limited, it can be just 20 people, you know, in one particular city. And so what we are doing is delivering that type of information but much, much earlier. And so we are. We’ve worked hard to deliver that kind of information in language that creatives can use by asking similar questions: Is it scary, suspenseful, or funny enough? And if not, where does it fall through? Are the characters strong enough to carry this film or a potential franchise? You know, sometimes a writer or creator will love one character more than the other, and it shows in the finish. So it’s like, what can we do to build up these other characters and relationships? So what really needs to happen to be able to take the risks that creative storytellers need to and what we’ve learned, I think most people know intuitively, but we’ve really been able to measure this is originality matters. And the thing is when Hollywood gets stressed and nervous and is cutting budgets, what they tend to do understandably is resort to trying to make the closest copy to something that was good just before. And I think there is concern that I will be used this way. So I feel really proud that we’ve been able to build something that actually does the opposite and delivers data that says, here’s where you’ve met the audience’s expectation. Here’s where you are really a thriller, but here’s where you’ve done something original that is really going to catapult and, and, and make this a special story. . And so, we measurably encourage the risk-taking that’s required or the originality, but I think I put a little bit of support behind it. So that’s really our goal: How can we support creatives to build what they want to build, to create what they want to create, and empower them to sell it, which ultimately is required to get the money behind a project? How can we give them that kind of support to make truly amazing stories?

Integration of AI into Businesses

Ryan: I love that. You’re basically encompassing what your, what StoryFit does with what an I’s goal is and bringing them together in terms of the, we’re going to flip the script on this, right? We’re going to take what’s already good and what should be there. But then we’re going to supplement it with all the things that are missing and be able to bring that forward, right? And bring it ahead. Not the, well, AI makes it so we can just copy what’s already out there and, and regurgitate it and put it back out again and, and process it for you, but really bring that originality forward and kind of bring it completely unique thing. I mean, again, I consume a lot of content, and I’m exactly in that boat, right? I’m always looking for something different, something new, something exciting. And I can imagine all the stakeholders you have from, from the writers and the creatives, the producers to this marketing and sales team, to everybody that just could look at these insights that are provided. Let’s talk about how they integrate this, though, right? Like how do you define the role of AI in this space? And, like, how do you strategically and successfully integrate AI? Because I think that’s such a huge piece. We can talk, as we said, about this being an innovation and integration conversation. So I want to cover that because that’s probably like you said, it’s scary, and there are people, we just saw some things that, that happened in, in that industry specifically that people were like, well, I don’t know. Is it coming for me? How do you create a success story out of it?

Monica: Yeah. And let’s start with some of the scary challenges. first of all, you’ve got the name AI, which is really very broad and encompasses more than anyone ever intends to talk about in one conversation, right? And then, who has actually created the scary stories about AI for the most part over the years? It’s literally the group that we’re selling into, right? it is Hollywood that has made these stories. And so I think right there, you already have kind of an aura. The other thing that I’ve seen happen just in the last year or so is that because of the incredible progress in generative AI, a lot of times now when people are saying AI, they’re, they’re talking about Generative AI, and there are still a lot of different variations of how you can use AI, we are focused on what’s called discriminative. I think it’s easier and more common just to say analytical, but we’re working with the same large language models, but we’re building on our data to then analyze, which means we’re delivering consistent data. So this is one of those things that I just wouldn’t have even mentioned a couple of years ago. But now that people are thinking of generative. It’s really important to understand which AI is best for your use case because you can put a script into generative AI and get an answer back. But if you put that same script through again, you’re going to get a different answer because because it’s not consistent, that’s not what it’s made for, right? It gives great answers. I’m always trying to deliver this because I think the first step in any kind of AI integration is understanding what you’re working with and what your goals are. And so sometimes when I’m talking with companies, I hear they’re comparing Xy and Z, I’m like Xy and Z don’t even have the same out. I mean, I wouldn’t even use them for the same thing, right? They don’t have the same end zone. So, really, the first thing is understanding what you’re trying to do, and it is a lot to ask of companies right now. I like Andrew Wang, who is the CEO of Scale AI. I think it is infinitely quotable, but one of the things he said is that we’re unmistakably in the fiery takeoff of the most important technology of the rest of our lives. And so when you have this burden, you’re like, here’s what we’re trying to do now. So businesses are being asked to change and adapt faster than certainly anything I’ve seen in my lifetime. And so this is now where integration is important because the right tool and a poor integration means it doesn’t work. And so that’s something I’ve seen, and I’ve tried to pull a couple of my experiences together on this is that, on the one hand, I’m working directly with companies as they integrate our technology. I’m seeing things. I also remember when I was running R&D inside of a content company. How do we pull what we learned on our small team and get it into the rest of the company? And that’s a huge challenge. At the very base of it is people. So I think one of the things that’s happening now is we’ve got this huge focus on AI, and we’ve got to remember now, how do you, you know, carve the way for new technology? How do you create a space with the team so that they can start using it and testing it? And I think there’s a lot of pressure that we have to balance, and one is that a lot of this AI is still in its infancy, really. It’s amazing, but it doesn’t always work exactly the way you want it to. And so there’s the question, and I think this has to be defined before you start using new technology in a company. What are your expectations? Are you measuring it so that it does everything you ever want it to do? Which is what I see. A lot of times in companies, the expectations are frankly too high. So it’s going to fail, or are you testing to see? Are you testing other questions and what I do on a general level and not just for our technology but on a general level? I think it’s really good to have your test be. How would we use this? Now? How can we imagine using it if it were better? How do we lay out the team or the process? So, as this technology improves, we are now able to move with it because the mistake I see a lot of times is this test doesn’t work well enough. It’s wrong 10% of the time, and that’s too, and that’s too high. It’s like, OK. And so now they’re just going to wait and see until it’s better, but now it’s too late. Now you’ve missed the window. You don’t have the learnings along the way. So, figuring out how to adopt different technologies at different levels of accuracy is a real challenge and takes a lot of conversation. I think it has to be, yeah, there has to be that permission given from executives down of your job. It is to test and understand and give us information. It’s not one to figure out how to get yourself out of a role or two to just determine whether it’s good or not, and to frankly usually come back with, well, it’s not good enough. I can still do better, so really helping teams understand what they’re supposed to do with this is a key that I frankly see lacking in a lot of situations.

Ryan: I think it’s a wonderful call out in that. Again, it’s a little bit of a top-down leadership strategy. There needs to be a plan for it, right? It’s not just a cure; it can’t be seen that way. If it is, it’s probably going to fail. I think there’s a cultural shift, a dynamic shift, that needs to take place for AI integration to be successful. How have you seen leaders be able to successfully foster a culture that embraces AI technological advancements? Addressing that potential resistance, especially in the industry that you’re very familiar with?

Monica: I think the first thing is that they need to really define who you are as a company because I think there’s a pressure right now to be a technology company, but the idea is like, what is the product you’re building? What’s the special sauce? What makes your company unique? Because whatever you’ve done so far is important to value because whatever you figured out to get where you are is something another company hasn’t figured out. Who are you, first of all? Then, the reminder is that your job is to become a company that interfaces well with technology, especially for some of the media companies. I know that large media companies do have technology departments, but for the mid-size companies that we work with, you are not going to be a technology company overnight. There are nuances in how these companies run that are just different from a media company. I always tell them that you would say the same to a technology company that suddenly decided they were going to start making movies, right? You would say, oh, you don’t even know what it takes on this, whether it’s production, distribution, whatever it is, right? I was like, so you’ve got to know that the same thing has happened in this technology building that is not happening in your company. I am surprised at how many companies I talk to now that want to try and build things themselves, and I’m just like, well, OK, that’s millions of dollars, and so I try and encourage them like, yes, build it yourself but at the same time, use what’s available to again, start training your team. See what works, see how you can really integrate this technology, and make sure it’s worth it before you build it yourself, but I have. I do hear a lot from companies who have this idea of building itself. It looks easy from the outside. I mean, ChatGPT really does make it look easy, right? But they also had billions of dollars, and I don’t even know the numbers of really smart engineers working on this problem, and I just keep remembering, I keep reminding that billions of dollars to make it look this smooth and seamless, and so it’s really trying to keep that in balance.

Balancing AI and Human Creativity

Ryan:  That overnight success was years and years in the making, but because it came up so fast, it was like, well, it wasn’t here, and it was here like it’s just that easy, right? And it’s really not, but it’s always nice when it looks that way, right? Especially if we’re the person running that business, but you’re right. That’s kind of that caveat that catch there, right? And when we’re talking again about balancing innovation and integration, I want to talk about, you know, balancing automation and human creativity, right? I know again, especially content-centric businesses that are relying on or heavily historically have always been fully reliant on human creativity. Now, we’re looking to kind of like you said, that transition is taking place. How do you strike a balance between leveraging AI for automation and preserving the unique creative contributions of human workers?

Monica: I’m in technology, and I’m the first to say, absolutely, there’s a magic that happens with a group of creatives. I 100% agree that those magic elements need to be preserved. Now, there’s a lot of content creation that doesn’t have magic, right? So there are some spaces for AI but what I’ve seen, I mean, this is throughout my career, is the power of combining AI and people is where there’s real brilliance is. Sometimes I hear a lot of like this when content is all created by AI and it’s like, look, why are we even talking about that? I mean, maybe that will arrive someday in some way, but why even talk about it right now? What really should be happening now is what’s the best part of AI that we can pull out now if I flip back to our technology specifically, what I owe say is like, look, let this technology be just a seat at the table that can do something that humans can’t like. This technology remembers every scene ever shot, the level of suspense what was said, and what the characters were doing for like quick comparisons and really pulling out information that can help you be creative and see things from another light like that. To me, the best is the technology that makes you smarter. That last layer is always sprinkling the magic dust on top. So that’s one of the things I think is important, and I’ve just seen this over and over again is that if you have the flexibility to figure out, and again, this is back to what I was saying before, that teams need to be empowered to like to figure out how and where to pull in AI and really doesn’t have to be AI any kind of process automation and when it should be human and you can make incredible strides in and saving costs in areas where you don’t need humans and then really put the human power where it’s needed. I mean, even in conversations, right? A conversation is an incredibly powerful thing. I will come away and already have learned just from our conversation and the way I’m thinking and this just doesn’t happen without it. So, do we want to replace this? I think that’s the kind of mentality that needs to remain.

Ryan: I absolutely love that. I think that’s one of the big, I don’t know if you want to call it sticking points or fears or whatever you want to taboo myths. I don’t know what you want to call it. When a lot of businesses, a lot of people want to do that, it’s to replace, like, oh, I want to replace this, and I want to accelerate because if AI can do it faster and cheaper and better, I can replace. It’s like it’s the idea is to enable and strengthen and partner with AI essentially, right? And, like you said, it’s bringing forward different things. I think that’s something that you have a great, again, a great intake and a great look on is providing data and insights at a faster and more scalable rate, but then being able to take those and a human taking them away and going great. So now, what’s that magic dust that we have to add to this? What can we layer on top of it now that we’ve got this information faster, more accurately, and accessible to us, right? That’s kind of your take on that for that. 

Monica: I love the book Range. He tells a story of a chess player, and I will not get it as well as the books. I recommend it to anyone, but the story of the chess player who was first beaten by an AI and what he said afterward was, well, I am now a human and can be beaten by this, but when I pair myself with the AI and use AI information, no one can beat me. So it’s that pairing, and I think there’s a lot of brilliance and also a lot more fun there. The other element I was thinking that really has to be present for this integration to work and also for people to have the confidence to play with AI and not feel like they’re replacing their jobs, which is just a normal concern, is also the acceptance in the company that, hey, we’re talking, there’s transparency, we want to know what works and what not and being transparent about the goals. So that people are confident enough to report the problems, there are lots of studies with change management that just say if you’re in an environment where you’re not comfortable in talking about what works, but also what doesn’t work and where the failures are, you’re not going to have the kind of growth and knowledge and change that you want to see.

Ryan: Yeah, One of the interesting areas. I was following the story of the deep stack, right? And now they’re saying that this is the death of online poker, right? Because bots can come on and do this. So now it’s, but all it’s doing is pushing people back to actually like having to do things together in a room, but all of the pro poker players are basically using this to go. I can run thousands of simulations to understand every potential outcome, and then when I’m sitting live, I have basically been able to train myself. So that same sort of theory of yes, it may impact an industry, or it may impact one way of doing things, but the people who bring it in, accept it, and enable themselves to get better because of it are the ones who are going to benefit, right? It’s just being able to accelerate their own growth and things like that. Really, it’s again. I love all that stuff in terms of that side as well. I think it’s just amazing, and I think it leads to kind of a question around what you see in terms of, you know, are there emerging trends where you see the integration of AI and technology again, particularly in content-centric businesses, any advancements or technologies that organizations really need to prepare for? I know that’s all we’ve talked about in this episode. So I’m sure there’s a lot we’ve unpacked a lot of it, but anything more kind of comes to mind for you.

Monica: No, I think that there are a lot of technologies, and I think anything I even listed right now might change in just months. So I really think that the attitude that companies have and the mentality and the communication that they’ve laid out the groundwork they’ve done within the companies to pave the way for the fastest change ever is just so important that to me that overrides any technology because if that groundwork is laid out properly, then no matter what comes down the pipeline, that company is nimble enough to roll with it and learn it and bring it into their processes, bring it in, test it and throw it out right. There’s a way to test that because I think if companies right now if it’s too hard to test new things, that’s going to start putting them behind.

Ryan: I like that. I mean, taking a look at that a little bit deeper, you know, do you have any thoughts you’ve shared a bunch of already, just specific strategies that you see are successful in ensuring a smooth transition? As you said, top-down leadership, really the culture behind it, all of that sort of thing, but anything else from a strategic standpoint where like this is essential like you got to start here, you gotta do this, or it’s doomed to fail.

Monica: Yeah, I’ll almost answer it by starting kind of with the opposite. Is there this one phrase that when I hear it, I feel like we’re doomed to fail, like this is going to be a hard one, and I’m not sure how to overcome it, and it’s something that can be said casually, and, you know, in a meeting and I guess I mentioned it as sort of that warning of like, hey, when you hear this, you need to take a step back and really re-evaluate how you’re going to approach and how you’re going to bring it in and that phrase is, yeah, I just don’t like it. It’s that because now the first few times I heard it, I was like, well, just try it, you’re going to see or, well, you know, I just like, kept trying to put up an instant, you know, defense to it or kind of an argument or try and persuade and what I realized is that is a real warning moment, and what if it’s coming from a whole team you’ve really got some issues and that to me that’s the flag of you need to sit back and rethink like you do not if you’re an executive in this situation, you have not paved the way for this team or for that individual to be successful in adopting new technology and there’s so then it’s about asking the questions like is this team feeling so threatened that they can’t see straight which, which could be happening? Is it too risky? Is the company in the midst of layoffs? And so doing anything unusual is just too risky for them right now? Like, what are the real reasons? But I think that phrase is it should be just a warning flag for any integration that takes a step back. This isn’t about just demonstrating and working through a process, you know, working out the problem. There’s some emotion that just isn’t an easy answer.

Ryan: I like that. That’s phenomenal from that standpoint to kind of cover all of that. I told you I was going to do this. I was going to run along with all of my questions and everything. So, I’m going to try to sum it up so that we don’t keep you here too long because I appreciate all of your time and insight. I’m going say we’re going have to do this again, but you know, for organizations that are looking to start this AI integration because I think again, while it is the buzzword, I think a lot of people like you said, they’re scared to get started. They don’t know where to get started. They don’t know what to look at. Maybe any advice that you would give them from either technological implementation or managing the human aspect of change that you would say, and again, this is unpacking, it’s Pandora’s Box, we could talk for hours about this, but you know, just a little piece of advice to kind of start them off on the right path.

Strategies for Successful Integration

Monica:  I think it’s just a picture that you have to lay the groundwork before you can integrate new technology, and that requires all of the people skills. The change management type is the advice of how you have communicated with the team and gotten feedback from them about what it’s going to be like to test and integrate new technology because if that’s done right, then you can, then now 100 different technologies can come through that team, right? Because you have the process for it. So I have many times when I’m selling, just wanted to say, and of course, it’s hard if you’re selling a product like, whoa, whoa, you think this is a conversation about cost, and that is not where we’re going to have a problem. It is that you have half a team that’s ready and half a team that is not. And so this integration is going to be challenging either way. So I think just laying the groundwork and if, and if people think of that, whether you know, a team leader or from an executive, I mean, in other words, ground up top down ground up. Thinking through, do we have the ability within this company to test and communicate, bring things in, bring things out? Do we have the confidence in the team to work like this? And that’s what has to be set out first? I think that’s absolutely phenomenal.

Ryan: I love it, and I’m sure you’ve got tons more advice. I’m going to give you two little takeaways here to go with at the end here. Anything you want for our listeners to really remember when it comes to this podcast and your messaging and then after that as well, I know there are people going to be wanting to talk to you about this, ask questions, get contacted with you, learn more about StoryFit. So we’ll lead into that as well, but any last takeaways there.

Monica:  I think the key takeaway is that integrating AI requires strong people skills. Don’t forget the people in the process, and as far as reaching me, I’m on LinkedIn Monica Landers, StoryFit. I’m there, and I think that’s a great way to get in contact there.

Final Thoughts and Reflections

Ryan:  That’s absolutely perfect. I love both of those little pieces to go with them, and then again, storyfit.com for our listeners. Go check it out. It’s so cool. I’m absolutely right. I’m going to just continue to play around on this site afterward as well, but what an incredible idea and a great story of, again, enabling AI to really empower people and bring together what AI is supposed to be doing and what we want it to do and not necessarily again, like all of the Hollywood loves a good scary thriller story. They’ve been trying, they’ve been playing with it. I go back to like minority report even before those rights, of what AI is going to do, and it’s like now you’re scared of it too. So anyway, I absolutely love it, and I want to say a really genuine massive thank you, Monica Landers, for joining us here today. I’d love to do this again. It’s going to be fun to talk to you. I would I know our audience will love it as well. But thank you so much for your time today for this amazing insight as well on this episode. We can’t thank you enough. Thank you for this conversation.

Monica: It’s been great. Thanks so much, Ryan.

Ryan: Excellent. So with that, I will thank everybody for joining us on this enlightening journey through AI innovation and hope that you’ve been inspired by the incredible stories that we shared today and remember the future is driven by pioneers, like our guests, Monica Landers, and the limitless possibilities of AI. So stay curious, stay innovative, keep exploring the boundless horizons of technology, and, as always, before we sign off, make small requests for our dedicated listeners. If you’ve enjoyed the podcast, we know you did. Leave a review, subscribe to your favorite platform, and share it with others. That is how, with your feedback and support, we can bring you more amazing content and incredible guests like Monica Landers today. Thank you so much, everybody, for listening. This is Ryan Davies signing off. Take care.

About Our Host and Guest

Director of Marketing – Ekwa.Tech & Ekwa Marketing
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Founder & CEO at StoryFit
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” I think it’s just a picture that you have to lay the groundwork before you can integrate new technology, and that requires all of the people skills. “

– Monica Landers –