The AI Marketer's Playbook
The AI Marketer's Playbook is an actionable podcast focusing on AI and marketing. Each episode covers AI strategies, tools, and trends that are changing marketing. Listen to interviews with industry experts, analyze case studies, and get practical tips. This podcast is for anyone looking to leverage AI in marketing to improve results.
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The AI Marketer's Playbook
41 | Jared Bonila on Avoiding AI Hype and Finding Real ROI
What makes an AI solution truly valuable to your business? In this episode of The AI Marketer’s Playbook, host Audrey Chia talks with Jared Bonila, founder of Job Genie and an AI consultant to top-tier firms across law, insurance, and private equity. Jared shares how he identifies real business problems worth solving with AIand why onboarding, workflows, and customer feedback are often more impactful than flashy tools. They explore common pitfalls companies fall into, including shiny object syndrome and building without listening to their audience.
If you’re a founder or marketing leader trying to prioritize AI initiatives that actually move the needle, this is the conversation you need to hear.
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Hello and welcome back to the AI Market Playbook, where we cover actionable frameworks to help you leverage AI and marketing strategies in your business. I'm Audrey Chia, your host, and today I*have with me a good friend of mine. We have met each other since day one of our LinkedIn journeys. I'm Jared Bonia, the founder of Job Genie and AI research and development company focused on really impactful AI solutions. Now Jared, this big shot right here has been featured on Fors four times for his work, helping top private equity insurance and law firms across us, Puerto Rico and the UK adopt ai. He was also one of the first. To build an AI job application agent back in 2021, that could help you apply up to a hundred jobs in a single click. Now, Jared, I'm sure there are lots of things you can unpack together in this conversation. It's great to have you here.
Jared Bonila:Oh, thank you. It's so great, you know, to be here with you, and thank you for that great introduction. I feel so much cooler than I actually am based on the way that you described me.
Audrey Chia:You are cool. All right. Tell us more about yourself. So for listeners who don't know you, you know, how did you first get started in the world of ai? I know you have been in this space for quite some time. Tell us more about that journey.
Jared Bonila:Yeah, so my journey to AI was. Very different than, you know, most people. I didn't really come in with the concept of, oh, I wanna be an ai or even really technology. So I graduated with a degree in co uh, from college with a degree in psychology and I didn't really know what I wanted to do with it, but I understood that everything in life is really psychology. You know, whether that's business or just, you know. Daily conversations, you need to understand how people think, how they behave and all of that. So I thought for studying there was something, you know, could really go anywhere. And then when I graduated, obviously, you know, I need to figure out a job with that and I didn't wanna, you know, study for my master's, become a therapist. Um, so my father's a lawyer and I always. Spoke to him about like logical things and we had debates along those lines. So I took the, uh, lsat, which is a law school admissions exam, and I got like nine point shy of a perfect score, which is, which is very high. And then I kind of, before, you know, deciding to go to law school, I said, let me, you know, pursue. Or look into a few different, uh, job titles or industries that also have logic and the first good'cause the LSAT isn't really about law, it's more about understanding logic and logical reasoning. So that was what I really liked about, you know, studying for that. So I found out, you know, that computer programming was all just. You know, knowing logic and building upon logic. So I, I, I went to YouTube and just taught myself how to code. And then at that time, coding, you know, was so, so many different areas. You know, there's like automation, web development, machine learning, and data science. And then I decided that I would pursue machine learning, data science and ai because I felt at that time, and this was in 2018, that I, I saw that it was the future because, well, ai, you know, it's been around for a while and it's always been behind the scenes, but now it's getting better at, you know, helping people perform and helping people learn. And even back then that I, I think it's so interesting because like, if you think about chess is, AI has been in chess for a really long time and has been better than the best humans at chess, but we're still not paying to see an AI versus in AI in chess, right? We're paying to see humans versus humans in chess or maybe a human versus in ai, just to see how good it could potentially be. But people are really using AI to improve the way that they play chess, you know, to improve the way that they learn. So back then I thought that. When I made this observation, I was like, that's going to eventually apply into other jobs because you know what AI is, it's, you know, it understands patterns, recognition, things like that. So it's just, it seemed to be, you know, a potential obvious sign that, you know, there'd be a huge opportunity for it. So I went all in on data science and machine learning in like 2019, and then I started. Developing a few products and services and then chat. GPT blew up out of nowhere and it was like perfect'cause like right place, right time. I'd built a few things with ai and then businesses were like, you already have experience in ai. We need your help with it. So then a lot of people just started reaching out to me in terms of consulting and advising and that's really what I've been doing. And then. Been using a lot of the advisory and consulting that I've been doing to identify different ways that people and companies aren't using AI or gaps that they're missing, and then I create them and then, you know, throw them out to the world and see how they, the world responds.
Audrey Chia:Wow. See you, you used the law brain and applied it somewhere else and I'm so glad you did that.'cause I think there's a whole world of opportunity. It's really right timing right in the AI space. So you spoke a bit about, you know, consulting and building solutions. Can you tell us more about the, because many of our, um, guests, they specialize in a specific niche, but for yourself, you seem to know. A lot. So tell us more about how you usually work with clients. What does that process look like and how do you even identify a problem that is worth AI solving?
Jared Bonila:Yeah, so, so first I, I'll, I'll, I'll work at that backwards. So,'cause I think that the, the second question is probably, you know, in my opinion, one of the most important questions in, in, in the whole realm of AI is like, what is a problem that is worth ai solving it is a problem, whereas you can define, you know, what is good enough. So it's like if you're a human and you can do a process and you're like, all right, you know, I, I can do that in X, y, and Z steps, and then I know that if I follow those steps, the result will be good enough. You know, it's not a level of judgment or et cetera. You know, that goes to it. You know, if I do. A, B and CI will get to D then those are, you know, the best proce, the, the best processes and ways to use AI because it's predictable. Because what AI is, at least generative AI is, you know, a predictive engine. So, you know, if, if a, B and C works really well and you know, you have that process, uh, lined up and mapped out, then you know that you're gonna get d. But where people get. A little bit off topic with, and I wouldn't say off topic, but where, where they get lost and where the results don't really show is when they do it for things. And, and with that being said, before I really get into it doesn't mean, you know, it's bad for it, it just mean it's harder to measure. And that's, you know, where I help you, you know, really where I focus on is, you know, for like content creation is one aspect, right? And like content creation, we all, you and I both know, like AI is great for copywriting, it's great for you. For creating content, but, but the caveat with that and, you know, the, the little, uh, thing that makes it harder to measure, it's like, just because you know, a post looks great in terms of LinkedIn format doesn't mean it's going to, you know, get a lot of user engagement. And then just because it gets a lot of engagement doesn't mean it's going to convert. So is with that being said, you know, to bring it all together. Is, you know, there also needs to be like a clear metric that you're trying to reach. So that's why I say is like, by understanding that process, it is a good way to understand it. Because if you don't know what you're looking for, then it's hard to expect ai, you know, to. Do it. And then now, uh, I know that answered one of your questions, so I don't know if you wanna go back and, you know, tie in the, the original one?
Audrey Chia:Yeah. No, but what I love about what you said was mm-hmm. Just because AI can create something doesn't mean that that something's gonna work and get you the results, right? So there are actually so many layers, right? Just because you build a process and can get certain output out doesn't mean that the output is good enough. To get you the actual results that you want. And maybe for a business that's just starting out, how do you even get started? Because technically you can apply AI to everything. So how do you, like, how do you prioritize that business outcome? Um, what does that look like for a business owner? Yeah.
Jared Bonila:Yeah. So that's, in my opinion, the most important step and the step that's also been missed the most. So I don't know if, if you've seen, you know, there's been a lot of news lately on how a lot of AI pilots and projects are failing. From, you know, 80 to 95% of them. And a lot of it is, because exactly what you said is you can apply AI everywhere. So for me, you know, and, and that's what I do in terms, you know, back to what you said, you, you're asking in terms of the consulting and advising what clients typically ask me for and what they look for me opposed to, you know, other people who have niches like yourself, like in marketing or AI for sales or lead generation. Along those lines, what I really focus on with my advisory and consulting. Is prioritization and road mapping. So, you know, there's a lot of people where it's like AI's everywhere. Where could I do it? But like, I need to make sure that like, I'm investing AI because, you know, some comp and like I work with companies that have, you know, investors. So a lot of the decisions and investments they make, they need to go back to a board and say, you know, we're gonna invest in AI because we believe that, you know, it will increase our leads by this, it will increase our sales conversions, whatever that might. B. So, you know, you need to be able to understand, you know, what that is and, and how to get there. So where I always start with clients is by breaking down the current processes and, uh, different workflows that they already have, right? Because, you know, if you try to, you know, throw AI in. To create something new. You're essentially, you know, just you, it's just a hypothesis. You know, you, you, you have an idea that it's gonna work. You're gonna build something, and then you're gonna hope for the best. So that's hard, you know, to measure. But if you start by, you know, really doing like a breakdown in audit of everything, you know, different people do in your business. So as if you have a marketing department, right? They're creating content. How much time are they spending, you know, researching content, how much time are they spending drafting content? How much time are these? Spending, uh, what's it called? Publishing content, repurposing content to different platforms, so you know the different steps in time that they're taking with those. And then you u you unders, you use that to see where AI can fit in best and improve it because, you know, there's different steps where it can, you know, help. There's different steps where it could do the whole thing. And then there's certain steps where, you know, you need the human judgment, you know? Being that, you know, this is the marketer's playbook. I thought that was a really good example because, you know, for, for, from your experience, you know, you can use AI to like really, really save time with the research, right? It's like, that's been my opinion, you know, one of the best ways. So now you get the research, all you gotta do is double check it, make sure it didn't, hallucinate, didn't lie to you, you know? Now that saved you time where, you know, years ago you'd have to spend hours breaking down viral posts. What made this post go viral? All of that. But now you have AI do that. Then you know, now you see like, okay, maybe I'm good at writing. Then you use AI to draft it, et cetera. So by breaking down all of the different steps, and you know, that's just marketing, but like you do that across operations, you do that across sales, you do it across all of the diff communications, everything, you know that. Applies to your business and department. And then you see, you know, where can I, if I use AI here, what will be the time saved on it? What will be the pro the money saved on it? And that's where I think, you know, not a lot of people are going, right? Because they're also thinking about like, how can we replace people opposed to how can we amplify people? And if you think about the way that I just explained it, it's about amplifying people, right? It's like, okay, I spend X amount of time doing this. How can I use AI to. Save a little bit of time on that.
Audrey Chia:Definitely. I think you covered so many great points, right? Being able to use AI as an enabler, uh, not as a way to replace your current kind of team, that is something that businesses should think about. I think there's also the element of, even if AI can do it, sometimes you still need that human in the loop to make sure that quality of the content is what you're looking for. So just because AI can create a blog, a newsletter, a social post. Doesn't mean that it has the strategy behind creating that copy that converts. And I'm sure that also applies to so many aspects of businesses.
Jared Bonila:So many. Yeah. Right. Very, very well said. Yeah.
Audrey Chia:Yeah. And I'm so curious to know, Jared,'cause you also talk about, you know, using AI in different use cases. What are some of the more mind boggling kind of, or exciting endeavors that you have been working on? They are pushing the limits of what's possible right now.
Jared Bonila:EE. Exciting. So, so one of the things where, it's interesting'cause I consider myself more of a boring AI user than an exciting AI person. So, so when I got into ai, I was very big about, you know, trying to do. Something that nobody's done trying to do. Something super exciting. So as you said in my introduction in 2021, I created an AI agent that found jobs on LinkedIn that were 80, over 85% relevant to your resume, filled out the job applications for you. And click submit. So it's like if, if I was applying for a job and we were having this podcast, it'd be applying to those jobs. So that was one of those things. And again, 2021, this was before chat BT came out. So this was one of those where it was, you know, exciting. It was pushing the limits. All of that, but it, but it didn't have the impact that I wanted it to have because what happened was is people started using it, but then people started getting rejected by a lot of jobs at the same time. Because one of the things that I think everybody needs to think about when thinking about AI and applying. Is what is the real problem. And like a lot of the times is there's a problem, you know, beneath the problem. So with, you know, what I created is the problem most people have with, you know, finding a job isn't necessarily that they haven't applied to enough jobs. It might be, you know, that their resume isn't good enough, that their LinkedIn profile isn't good enough, you know, that their experience. Isn't, you know, just up to par. So if you, it doesn't matter if you apply, you know, if you don't have good experience, you don't have a good resume, you don't have a good LinkedIn profile, it doesn't matter if you apply to a hundred jobs, a thousand jobs, you know you're not going to do well. So, or you know, you might. Might not, you might do, well, you might not, you know, you might get lucky, but, but at the end of the day, it's like there's a problem beneath that, right? So as you apply to all of these jobs, you're getting denied. Now, you know, okay, what's the problem beneath that? My resume is not good. What's the problem beneath that? My skills aren't that good. What's the problem beneath that? So, you know, understanding all of that is what I've realized is really, you know, the lifeblood of AI success because, you know, they're like. You said is there's so many exciting ways to use ai, so many things, capabilities that can be done with it, but when bi, you know, I work with businesses and I work on a consulting and advisory basis. So it's like when they hire me is they, they're not hiring me. You know, to have something exciting where it's like, oh, this is cool. You know, we get a few views, but it doesn't, you know, turn into dollars. It doesn't turn into engagement, doesn't turn into whatever metric they're looking. So that's why I'm very against, I wouldn't say against, but. But more on the lines of, you know, really looking for. Not the, I wouldn't say the boring ways, but the ways that, but the predictable ways, you know, towards using AI towards for success.
Audrey Chia:Yeah, it makes total sense. I think for me, what I've seen is, for example, people could be building out workflows where you can just instantly generate an ad, right? Right. It generates the copy, the visuals, uh, and maybe even sound effects for you. However, then my question is, do the ads actually convert? So if you actually put that to the test, right? Does it really work? Um, do people buy it? Is it too AI for most people's liking? Those are some questions that I think brands also need to ask themselves. Right? Uh, not using AI for the sake of it, but like what you said, going back to the matrix, the ROI, um. Does it make sense for a business? And maybe that's something to think about now, JIRA, you're also, for example, a fractional lead, I guess, in many teams, right? As a chief AI officer, can you tell us more about what you think that future of teams are gonna look like? Do you think it's gonna be a hybrid thing? Tell us more about that.
Jared Bonila:Yeah. Yeah. So that's something where I think it's, it's definitely changing a lot.'cause like I, I got hired, like I had a lot of fractional chief AI officer jobs, like when that first started off. But now I would consider my work more like. AI operations, like head of AI operations or things like that. Because more of the work is along the lines of like, how can you plug in these different AI tools, these different processes within, you know, the company's organization, the teams, the workflows, and all of that opposed to, you know, needing to be like this chief officer, you know, having the C-Suite type thing. It's more of, you know, just a, uh. A way of, you know, guiding different people. And that's why I think what's going to happen, especially as these tools are becoming a lot more easy to use and, and, and like across, you know, positions. So you know, they're using it, you know, for marketing, sales, communication, literally everything that you can think of. And, and, and they're taking away a lot of. The technical know-how and like even the prompting know-how I'm sure you know, you've seen, you know, over the past few years even, you know, prompting has become easier. Like you can go to, you can take like a prompt and go to Claude and say, write this prompt as, you know, 20 times better. And you know, if you really put the time to write a good prompt with that, it could make an amazing, you know, world class high quality prompt. And now. You have a much better prompt, you know, for, for the result that you're looking for. So that's why I think the, the transition that we're gonna see, and, and we've started to see, and I've seen it in, in the teams that are succeeding the most with ai. Is what, what I'm calling, and I think you, you've actually had somebody on your podcast, uh, talk about it in a similar context like AI generalist, where, you know, they're not people who necessarily specialize in anything with ai, but they understand ai, they understand a few of the different tools and the capabilities and how they connect. To different tools and then how to use them, you know, for their jobs. Right. So like one, one of the things where I think it's gonna change is like, I think everybody's really gonna be full stack to an extent, like right now, full stack or you know, up until this point, full stack has been like, you know, developers. So full stack developers, someone front end and back end. But now I think we're gonna have like more full stack workers where you're gonna have people be able to do things across different domains. That, that make it easier for them to ship, make it easier for them, you know, to test products and different things along those lines. And I think a really good example, and, and a company that's doing it, uh, really well is like Gamma. I I, if you check out Gamma, and I know their CEO posted about it a while ago and, and like what they have is like, you know, now you can use Claude Chat, GPT, all of these things for, you know, your sales or marketing team. To do data analytics so that now you know you don't have to wait for an analyst to analyze this data, send it to your marketing person, then they need to convert that and understand, you know, how that applies to, you know, your demographic. Now you could have, you know, the marketing person that understands your. Your audience and they're doing the analysis too, because, you know, they don't need to know all of these different Python codes, you know, data analysis methods. You know, you can use clutter chat, GBT, hey, you know, act like an expert data analysis, you know, show me, you know, the patterns among my client reviews. And then, you know, from there, you as the marketer could use that, you know, to generate, you know, blog posts generate different content. And again, the same thing, you know, with sales, you know, in sales. Now you, you have. Um, what's it called? These meeting recorders. So now you have a meeting recorder, you know that, that analyze it. Then you could take that, that recording, throw that into chat GPT and use, you know, to better understand, better create, you know, a new offer. And then prototype different things because, you know, we have cursor lovable all of these, you know, coding, uh, platforms. So it's like. It's enabling teams to do a lot more with less. Because a lot of times, especially like in technology companies, we'd have to wait for other people to get things done, to do, you know, the next steps as if you have a marketing campaign, you know, you have to wait till you get, you know, the. The analytics back before, you know, you do the next thing and then, you know, same thing with a lot of different stuff. But now, uh, with all of the advances in ai, you, you know, if you have an idea, you can push it and, you know, say like, all right, you know, here's a test that we're throwing out. And it, and the, I think, you know, the most important aspect of it is, you know, the cost savings. Because, you know, if you can test a lot of, you know. Full marketing campaigns, you could test full, you know, product prototypes in the matter of days and weeks where for, you know, dollars and pennies where like, you know, what,$20 a month with, you know, a lovable subscription. Now you have a full clickable thing to see if that's something your audience would engage with. And if it is now, you know, then back to the ROI, right. Is, you know, you can build this with lovable. See if it's something you know, your clients will engage with, they'll pay for if, if they hate it, if they don't use it, you don't invest in it. You know, you, you, all you did was put something together in lovable within an hour. And if they do now, you know, okay, like this is worth investing it to turn into like a pro uh, production ready app.
Audrey Chia:Yeah, I, I think it's really cool that you're bridging all the different apps, all tools together and finding solutions.'cause it's almost like you have a puzzle piece, right? Then now you're like figuring out, okay, maybe I need an AI note taker. Then I need to put in the chat GPT. Then after that gaba and then you string like a whole flow of events. I think I. I think it's beautiful'cause it's actually a very creative way of looking at ai. But what I found is I think most people just see the tools in silo. So for example, let's say, um, Gemini has nano bananas, uh, new kind of, kind of. Visual creation features, right? Most people would just use it as is, but then they don't take a step back and think, okay, can I use this, um, for ads? But to run, to use this for ads, you then need to take a step back and think, how do I, um, develop the ad copy? And then you need the audience insights, which then goes back to your customer interviews. So, um, I think most people are only looking at who's. Just as is instead of full workflows. Um, what, what do you think, have you observed that? Do you think it's something that you've also seen?
Jared Bonila:Yeah, absolutely. And that's why, that's why I said, and how I do, you know, my work is, you know, we start off, like, I don't start off with any tools. Not like, Hey, go check out chat GBT, let's do a training. It's let's break down your workflows. Let's understand, you know, what people are doing, how much time they're spending on them, you know, per week, per day, per month. Per year where the opportunity for AI is how we can connect, you know? Those different pieces, not in silos, but in workflows, you know, so you can have like an actual process that creates results as opposed to you're going, here's HBT, here's Gemini, here's this next one. And then, you know, because at that point a lot of times, you know, it might not even save you time. You know, just might be a longer thing. So that's why I think it's so important, you know, for people really to understand AI as what it is. You know? It is. It is just something to amplify. Or, you know, fill in a gap that you can identify. If you can't identify the gap or where it can amplify somebody, you're really, you know, just taking a guess that like, hopefully this will work.
Audrey Chia:Yes. I think it would be interesting for us also to share with our listeners. A lot of them are founders, business owners, perhaps three use cases that you have seen that are a bit more specific in nature.'cause a lot of our listeners, they have doubled a little bit to ai. Maybe they have tried, uh, using certain tools in their workflows, but many of them are still not. To share about what does an AI enabled team look like? So perhaps there are a couple of use cases that you think would be relevant to most people out there. How, where do they get started? Like what are perhaps three use cases you can think of?
Jared Bonila:So I would say a few good use cases that I think is like really common and has a almost immediate, or, and like the first one I'm gonna say has an immediate ROI is onboarding. So whether that's it like new client onboarding or employee onboarding, if you understand that process and you can break it down through ai, you'll immediately. Get a ROI on your time, because if you think about it, right, is if you, right now, if you hire somebody, right, you need, you probably, if you don't have this process, you know, uh, automated using ai, you'd have to, you know, send them some like, oh, you hired them, boom. Now you send them this. Then once they get back to you on that, now you send them another thing. Then you have to ask them these questions and that, you know, as somebody, you know, and CEOs, founders, our most valuable, um, what's it called? Resource is our time. So, you know, when we're starting off. Those are things, you know, we might not necessarily need to spend as much time. So as if you have an ai, you know, go through that process and there's so many different ways that you can do that. You know, you can do that with a make.com N8N, or even, you know, just a Google extension, like scribed or something like that. Whereas, you know, they have these different things and then people get back to you only when they have a question that the AI doesn't answer.'cause you could also even do it, you know, with the GPT or a chat bot is, there's so many different ways, but that's a way where now you're immediately getting your time back.'cause that's, you know. Maybe an hour, maybe three days, you know, depending on how extensive your onboarding is, because bigger companies, sometimes the onboarding could be, you know, a week of time and you know, there's a lot of training and things involved in that. But now with AI is you can speed that up where the people only need to. Get back to you and ask you, you know, when the AI doesn't know that. And then as you do it more, you improve, you know what the AI doesn't know. So, you know, you started off with, with the first employee and then now it's like, okay, the, this employee based on the AI process and the feedback the employee had, the AI didn't know how to answer X, Y, and Z. So that's, you know, the gaps that we need to build in. So over time. It learns more. And then again, it, it gives you more time back on, you know, your onboarding process and things along those lines. So that's one of the ones, and again, where I say back to what we were saying prior, it's not sexy, it's not exciting. It's like, uh, it is like, and it was something so funny'cause I had. Uh, it was like very early because that was one of probably the most common use cases I've seen that has an ROI that again, most companies can do it because they usually have an onboarding process and I had a VC that that asked me and like, this was. Early, early on, right. Chat, GBT days. And they were like, what's the most common one? And I said that And they were like, you could tell they were a little bit disappointed'cause they wanted it to No, they wanted, they wanted it to be like, oh, this lead generation, you create ai, it's gonna go find your perfect customer, create an email, do this thing. Yeah. You into a million dollar company overnight. And I'm like, no, it's just gonna save you time onboarding, but you're gonna get at least, you know, 10 hours back, you know, a month every time that you're doing that. So, so that's one of the ones. And then I do think in, in my personal opinion, I think sa under using it to understand sales calls and people better is so important. And unutilized, they, and I mean, a lot of people are utilizing, you know, the meeting recordings. Like, you know, you'll have like a. Sybil a fathom or whatever, but I think, you know, if you take those and you go from it so much more, you know. Like after you get a bunch of them, you know, you use that to like really do data analysis. And, and, and that's where, you know, prior, uh, our prior conversation came in, you know, the generalism with it. It's like, okay, you know, we have, we've had 10 sales calls this week. We haven't converted one. Let's take every single transcript that we have and start breaking down patterns, start understanding things.'cause now you know, you can genuinely start understanding things that, you know, we can't see. You know, that, that might, you know, go past us. So I think that is such a, an amazing way that people can use it, that they are using it. But I don't think, you know, to the full extent. And then on a similar front to that is with customer, customer reviews and testimonials. There's so much that you can do on that front from creating dashboards to like really break down, you know, your feedback. Negative, positive, you know. The different areas to improve different people to get back to, like, you can create a very, you know, quick and efficient dashboard just based on a Google sheet. And you, and back to what we were saying earlier again, is these are things where years ago that would've took months. It would've took a whole budget. But now you can just take your, um, you know, reviews, throw them into lovable bolts or one of those things, you know, take out the personally identifying information for security purposes. But, um, but then you throw it in and then now. You understand your customer reviews better and then you know, now you can use that again to build potential prototypes, to build marketing campaigns, to build all things along those lines. So is that's where, again, it could create an actual ROI, because this is information that you're having these are calls, you know, back to the sales one, those are calls that you're on. So now you're using information and time that you already have, and then you're using the technology to extract insights. To, you know, make more informed decisions. And I wanna, you know, really make it clear that what I said, that all of the use cases that I said weren't decision making use cases, right? Is there informational use cases? You're retrieving information, you're understanding patterns, you're not using ai. To help you decide things, because as humans, we should still be the ones, you know, making the decision. We have AI to help us identify patterns, to help us ident, uh, retrieve information, but we are the people, we are decision makers, we have the experience. So it's on us to be able to take that information than use that information to make more informed decision.
Audrey Chia:Yeah. And I think like what you said isn't always about that shiny new object. Sometimes it's just going back to the fun foundations, right? And then seeing, okay, what can I do that helps to make, you know, move the needle in certain spaces unsexy. But lots of ROI to your second point on using sales calls, uh, what I found is I useable, and what I do is I then export all the kinds of like chats. I can even in civil itself, ask it for a common target audience, pain points, et cetera. And then what I like to do is turn those pain points into LinkedIn content. So I built a second GPT that is trained on sales objection handling. And then I use that to create content. Content that, um, helps me with objection handling through content. So there's really two like quick wins, you know, in one simple workflow,
Jared Bonila:Stacy. And Exactly. And that's a perfect. You know, example of how to take, you know, one of the aspects of the AI and you know, the information insight that you're gaining, and then using it to help make a decision on the other end. Because even though you know, I'm sure you know, you're not just taking it like, you know, for phase value, you're still, you know, all right, this makes sense. They were right on this. It didn't hallucinate, you know, you, but you're using it to help you, you know, understand. And speed up your process because if you didn't have AI for it, you know, you'd be analyzing things, doing research, trying to find the pain points, create the content, and that would take a lot more time. But now you're able to identify, you know, where that time is. And a lot of the time is in, you know, the research, the looking for the pain points, you know, extracting those patterns. And now you don't have to do that.
Audrey Chia:Yes. I think one interesting thing to also consider is perhaps we've talked so much about all the benefits and perks by using ai, but I'm sure there are certain challenges that businesses face or certain concerns that they might have. So what have you noticed so far in terms of challenges, concerns, or potential drawbacks? It
Jared Bonila:don't matter. I'm like, where, where do I, where do I start with this? Because I, I think it is so much easier to fail with AI than it is to succeed with it. And based on, you know, the numbers and studies that we're seeing. It's like that's, that's what's happening. And I think a lot of it is because of, you know, really the shiny object syndrome with it. And, and the fact that, you know, it is really cool, it's really exciting and that. There are aspects and ways that people are using it where they're having wild, crazy results and everybody wants that same result. Right? So it's like if you have people who have like. They'll use, you know, nano banana to create, you know, a, a viral video and it'll get 20 million views. And, you know, and a perfect example of one, like I I, I didn't mean, even mean for this to be example, it just came to my mind is there was somebody who did like a liquid death commercial using nano banana. And it was so insane. It was so nuts and, and like very, very, very good and well done. But that was like one example of the many hundreds of examples where people are trying, where, you know, it sucks and it's awful and nobody wants to watch it. So, you know, you see all of these things that are exciting and it's like, that's exciting. Like there, and I, I wish that that, like, I had it ready so I could like share it because it, it was really, you know, appropriate for liquid death, for their position because, you know, they did just this absolutely outrageous commercial and that's what liquid Death's brand is all about. It's like, you know, doing things that are just. Crazy and, and they use nano banana to do. You know, just put together crazy clips and ridiculous things. So for that use case, it made sense. But, you know, for the average business, you know, that is a coffee shop down the street. Like them using, you know, an AI or video generator to create their content, it's not gonna hit people. The same way. So, so where I see, you know, a lot of people and companies going wrong is there, they're trying to do something that is so big, so extravagant, and they put so much time, they put so much money into it, and then. It, it, it doesn't turn out. And a lot of it, and, and one of the things where I think, and, and that leads to my second point yes. Is I think the biggest, and I think this potentially is even bigger, is now we have no excuse anymore. Not to do things that are data driven, because we have endless data. We can extract the data that we don't have. We can do research. So is everything that you are doing within your business, all of the bets you're making, the pilots that you're doing, is they should be based on. What your customers are talking about, you know, their real pain points and stuff. You know, you can, where you can identify and, and now again, you can put it in a dashboard and be like, I am building this because a hundred people, you know, have said that this is their problem. Where, uh, and you know, where that ties into the last point of why I think it's the biggest problem and, and I see this a lot with founders, like companies who are starting off and, and I've worked. With a handful of these where they'll, they, they, they see this new technology, like, I'm gonna build this new cool AI product, and they won't talk to anybody about it. They'll think it's the coolest thing ever. And then they'll spend hundreds of thousands of dollars developing, you know, it that like this advanced thing, and then they put it out into the world and nobody wanted it, or they wanted something simpler. And then now, you know, you gotta backtrack. But the, but the reality is, like most founders, and this is something like different topic, but on the same topic is most founders love their idea more than they love their audience's solution, or, you know, the need to solve their audience's problem. So they'll create this product because they think it will help the audience. But then when it doesn't help the audience, they'll still try to shove the product down. They'll be like, no, I'm just gonna tweak it a little bit. I'm just gonna do this. I'm just gonna do that. But at the end of the day is they didn't want that. You know, it's like, that's not what's, what's helping. So it's like with AI right now, with the, you know, the amount of data, information available, especially like we're all on social media, we're all talking. Yeah. Like I think TikTok, in my opinion, is the best. Place to find information because TikTok is different than LinkedIn, where like people are just, just go to TikTok and vent about everything. I I, and I am a big advocate of doom scrolling at least an hour a day on TikTok. Within your niche just to hear about what people are talking about, hear about their complaints, hear about, you know, the actual news, you know, see these things. Because the difference between TikTok and LinkedIn is LinkedIn's a professional platform. You know, we're all trying to go there and, you know, look like our best self, you know, express all of the good that we have, all of the knowledge that we have. We're not talking about our doubts. We're, and like obviously you and I both know, you know, talking about your failures and things like that is good for LinkedIn, but most people, you know. Do it in a way where it's also self-serving, where it's like, you know, Hey, I failed this, but that failure made me so successful. Where in TikTok, you know, people are just vulnerable. Where they'll go there and they'll be like, you know, I'm really worried that AI is, you know, gonna take my job because I'm spending, you know, this amount of time. Uh, writing and AI could already write better than me. So now, you know, you go there and you're starting to learn, you know, what people are actually talking about. So, you know, with TikTok, and you could then again, with these, with these tools, you can scrape tiktoks. You know, you can analyze hundreds of thousands of, uh, video scripts. In, in the matter of a day, and then now you have information to make decisions. So that's why I think the biggest thing that people are going wrong is not finding and listening to data to make decisions, to make moves because there's so much available and we have the tools to do it now. So, you know, everybody should be making informed, data-driven decisions opposed to, oh, this is what I think will work. And then I think the, and then my third one that I'll say is I think not realizing how much the times have changed.
Audrey Chia:Yeah. So,
Jared Bonila:you know, because the truth of the matter is now too, that attention is different. Yes. You know, just putting out content doesn't do it anymore. You know, you really need to be able to grab mind share to get people to notice you and do all of that. And so like the typical way is to build a business. Aren't working the same like in the past year or two, I've worked with a few founders who have came from wildly successful companies. So like they've, they've exited to billion dollar companies that I can't even say'cause of NDAs, but, but like for nine figures. And then, but, but in like. 2000 tens and like up to 2020. A lot of SaaS and, you know, technology companies is, they were built off of sales, right. You know, you get, you get people, you're making sales calls, you're doing outreach, cold outreach emails, all of these different things. But now that, that, that game doesn't work the same way it does, you know, people aren't picking up the calls the same way that they were. People aren't answering emails the same way that they were. People are looking, you know, for trust. So it's like, you know, if, if you send me an email saying like, Hey, you know. I could help out your business. And then I go and I'm gonna look at your LinkedIn and if you don't have anything on LinkedIn, I'm saying, I don't know who you are. You know, I'm gonna find somebody who does. And then you, and that's something a lot of companies are under, uh, estimating the power of branding right now. Yeah.'cause as somebody, like, I've been in AI since before, you know, AI was popular and I genuinely believe with all of my heart that. In the next year, and I think already right now, branding is going to be more important than AI because like I said earlier with, you know, the generalist content, uh, conversation is that people are gonna, you know, these tools are getting so much better and so much easier to use that, you know, three years from now it's not going to be hard to use. Right. Everybody's gonna have an AI agent that could help them do everything. But what, so what's gonna help you stand out? What's gonna help you stand out is your brand. It's gonna be how can you get people's attention? How can you get people, you know, to want to support you, to want to follow you? And, and when I say follow, I don't mean like. Click to follow and like see, like genuinely follow you. Like, you know, see what you're doing every day, see what new features are coming out. See these things, create that level of brand resonance where it's like, you know, people are there. You know, if you think about, you know, the best companies of all time have been companies where they really have a strong brand identity, right? Yeah. So like Nike, Nike's a perfect example. People wait, you know, for Nike ads. So long, you know, I mean, Nike releases and different stuff like that. So, so it's like by creating a brand where people could become a part of the brand, right? It's not, I'm using your brand, your company, for the product. You know, I wanna be a part of your brand because you know, you have my val, you share the same values I share. And at the same time, you have the solutions that I share and then you know, that's how you create, not only you solve their problem, but you create like brand loyalty around that too. Yeah.
Audrey Chia:So many great points that you shared there. I think the last point that you mentioned about brand beauty, I feel very strongly about it, is you can tell. There is already a whole wave of AI content. There are so many blog articles, so many pieces of, you know, stuff going around. Right? So then how does any company stand out? Right? Which is why, like, as much as I love ai, I always go back to what I do best, uh, content strategy and branding, because that part is. Inherently human. And at the end of the day, you want to buy from someone that, like what you said, Jared, being able to, uh, you emotionally resonate with you, align with on a values basis, you know, um, you enjoy their visual perspective. So. All of these human traits are gonna be also important in the world of ai, and you will see that in the next few years. I think right now it's still a, a race where people are still trying to catch up. But I think when ai, uh, plateaus right, and everyone's around the same kind of range, that's when the brands with good storytelling are going to stand out.
Jared Bonila:Absolutely. And that's why I think right now is the time to focus on that. Because, because that, that's what's gonna happen is everybody's gonna level out, then everybody's gonna be, oh damn, how, how do we get our brand storytelling right? How do we do it right? Where, in my opinion, is the goal? Should we do that now?'cause nobody's focusing on, you know, most of the businesses. And, and like I'm telling businesses this too. And, and when I tell you, and like I, I work with AI and obviously I do consulting with it, but a lot of what I'm doing is like, I'm, you know, I'm consulting based on, you know, patterns and information and research and things that, you know, I've seen. So I'm trying to lean companies more towards that. And, and Audrey, I'll tell you, a lot of companies are like, nah, it's not worth it yet. We'll get to it later. And, and again, all all I can do is give them the data and, you know, give them, you know, a, a potential roadmap with it. But it's on them, you know, to make the decision. But a lot of companies are at that point where it's like, brand doesn't worry. We need to figure out AI now and then, and, and, and again, brand is where you, you know, you get the people to pay attention to. And I think there are so many, you know, companies that, that do this really, really well right now. And I think. A really, really, really, really good example. That's why I said really so many times is lovable and'cause lovable in my opinion. And, and I, I use all of, I've used all of the AI, coding editors, generators, all of those things. Lovable is not even in the top three, in my opinion. Not even top three, but in my, but it has the best brand out of them all.
Audrey Chia:Yes, it does.
Jared Bonila:Because of that, they're the fastest company ever to a hundred million. They're doing so well. They have a community that shares, you know, content for them. You know, they've understood that. So they don't need to be the best product. You know, they have the best brand and then. Based on the best brand, you know, it, it does everything for them. So they understood, you know, prior and, and that's what I think a lot, I'm trying to like lean a lot of companies towards like this AI stuff. Yeah, it's important, but you will fi you know, if you're smart, you'll figure that out. You know, it's like all you need is, you know, the roadmap, the understanding of where to use it for ROI, you know, understanding the areas where, you know. It's just potentially a distraction and then using that, you know, to imp to amplify how you reach your audience, how you speak to your audience. That's why, back to what we were saying is, you know, using it to understand sales calls and reviews or things like is so important because that gives you a better understanding of your audience and the better you understand your audience and you can talk to them, the better that they could relate to you, you know, is is like if they feel you really get their problems. They're, they're gonna wanna, you know, be with somebody, work with somebody who has that opposed to, you know, I'm just creating products. I think that, you know, that's what's gonna help you.
Audrey Chia:Yes. So I think in the increasingly AI first world, being human at our core still matters. And I think that's what's gonna get you that brand loyalty Abso
Jared Bonila:community. Absolutely. And, and I'm, I'm kind of like, like I consider myself a contrarian a bit in the AI world.'cause like, I don't like the term AI first at all. I, I actually hate it. I think AI native is much better.'cause I think if AI first makes people feel like human second, you know? And, and, and that's my opinion because. The, and the reason I say that is because if you think about, like, if you have heard what happened with Duolingo, Duolingo is like, we're going AI first. And then people started deleting it. They started taking social media and, you know, attacking it and all of that. And it was because, you know, the, the way that they messaged it was we're putting. Front of our people. And if we're putting AI in front of our people, then you know, how much do we really value our people? And if we don't value the people that are building our product, then how much do we value our customer and pe and that and, and that's where, you know, psychology and everything, you know, comes into it is, you know, you need to understand, you know, who is your audience? Do they want you to be AI first? Because if you really take the time to listen to most people right now, it's, they're not the biggest fans of ai. It's like the world, you know, us, we, as you know, operators, marketers, brand experts. We like AI because it helps us do our job better. But if it doesn't help you do your job better, and it's not obvious you don't like it. Yeah, no, I, there's not a, you know, it's, it's like one of those things where you're worried it's gonna replace jobs. You're worried, you know, it's lying, it's doing all of these things. It's, you're worried it's bad for the environment. That's a whole different conversation. But, but what, as you know, there's so many different things where the world isn't all, the world isn't ai, the world doesn't want to be AI first. The world wants to be AI native, they want to have AI to help them with it.'cause even the people that complain about AI and you know, they don't, they hate on it for certain things. They're using chat, GPT, you know, when they need a recipe.
Audrey Chia:You know what I'm
Jared Bonila:saying? The system is, that
Audrey Chia:is very true.
Jared Bonila:CISO is, that's the thing, it's like. It's, it, it, it's a, and that's why I think, you know, the, the psychology and understanding the people behind it is so important because people want ai, they, they, even if they don't say it, they want it. Because what people want is people want better solutions for everything.'cause like, they don't wanna, you know, have to spend an hour on Google looking to find out like, is my dog gonna be sick based on what he ate? You know, I, I wanna type into to chat GBT and get, you know, a full breakdown of when do I need to bring him to the pet. Right. If, if I need to bring him to the vet. So it's like that's, that's the behavioral aspect behind it. But, but at the end of the day, like I don't want AI in my face at everything. And I love ai. You know, this is what I've done, this is my career. But, but like, throwing it down people's first with the AI first. Uh, and throwing it down people's throat. I mean, you know, with the AI first, I think that is a direction where, and, and I even know people that like I look up to in the AI space that are big on the AI first, and I, I disagree with them with it because again, is, that's the thing. It's, it's, it's about the people too. You know, we, we really have to think about how they're reacting to.
Audrey Chia:Yeah, I think this was such a beautiful and and reaching discussion where we blend both, you know, psychology, copywriting, marketing, and of course AI into the picture. Mm-hmm. I'm sure our listeners have gained a lot, as much as I have, so thank you so much, Gerald, for sharing your insights. Where can our listeners find you and who should reach out to you?
Jared Bonila:Yeah, so, so you can find me on LinkedIn. I also just started at TikTok because like I said, I think TikTok is such a good aspect. For personal branding, uh, that, that I'm experimenting with it. And I would recommend any and every founder that's watching it do the same thing. If you are like you or you, you know, you'd like getting behind a, a camera and talking just because one, it's a lot more authentic and the algorithm is better in terms of reach, so. One, you can find me on TikTok it, the name is Progressively Failing. So I like to, I like to loved it. I like to let people know that failure's. Okay. Um, and, and then on LinkedIn, Jared Bonia, my name. And right now I'm really working just with VCs and private equity companies, or companies, anyone that has a portfolio, because as I've told you, I, I do a lot of like AI road mapping and. Prioritization. So what I've been doing is helping investors understand how they could, you know, provide that value to their portfolio company. So it's instead of, you know, just hitting one company, helping investors hit all of their companies so that they, you know, get a better in, get a better ROI on their investments. Yes. So, but, but, but I also do, you know, being that, you know, my work is, you know, for VCs to do work with companies, I do work with founders and you know, CEOs as well. But right now I'm mostly focused on investors.
Audrey Chia:Awesome. And we will link all of your socials on our podcast. Thank you Giraf for being here. And thank you listeners for tuning in. Don't forget to hit the Be and stay tuned for next week's episode of the AI Marketers Playbook. Take care.
Jared Bonila:Thank you so much for having me, Audrey.