Now, I know what you're thinking. "Mike, we've heard about AI. We get it. It's revolutionary." But here's the million-dollar question: Are you actually seeing those eye-popping results in your own business? Are you doubling your qualified leads or saving tens of thousands of dollars with a single automation?
If you're shaking your head, don't worry. You're not alone. And that's exactly why today's episode is going to be a game-changer for you.
We're cutting through the noise and the hype to bring you real, tangible examples of businesses that have cracked the code on AI implementation. No more theoretical possibilities or vague promises. We're talking cold, hard facts and replicable strategies that you can start using in your business tomorrow.
To guide us through this AI success story safari, we have a true trailblazer with us. I'm thrilled to welcome Sara Davison, the mastermind behind the Maivenly AI Business Growth Accelerator. Sara isn't just talking about AI; she's in the trenches, turning AI potential into profit for businesses just like yours.
Get this: Sara has helped clients save over $40,000 a year with a single AI automation. She's worked with companies to double their qualified leads in just one month – a feat that used to take them half a decade! And the best part? She's here to spill the beans on how it's done.
The AI Hat Podcast host Mike Allton asked Sara Davison about:
✨ Start Small, Think Big: AI implementation doesn't have to be overwhelming; begin with one process and scale up.
✨ AI Enhances Human Potential: Successful AI integration empowers employees, leading to increased productivity and job satisfaction.
✨ Measurable Results Matter: Focus on AI applications that deliver tangible outcomes, like cost savings or lead generation.
Learn more about Sara Davison
- Connect with Sara Davison on LinkedIn
Resources & Brands mentioned in this episode
- Maivenly
- Respell
- CassidyAI
- AI Readiness: A Practical Guide Using the 5P Framework with Katie Robbert
- Clay
- Apollo
- Outthink Your Competition: AI in Marketing Strategy with Sunny Hunt
- AI Marketing Primer: A Comprehensive Guide for Marketers
- Explore past episodes of the AI in Marketing: Unpacked podcast
Full Transcript
(lightly edited)
Unlocking AI's Potential: Success Stories from Growing Businesses with Sara Davison
[00:00:00] Sara Davison: They were capped because they only had a few people who were able to do this process and they couldn't scale beyond where they were. So what we did is that we really understood their process, their workflow, and how they, their ideal outputs look like. And essentially built an AI or an agentic workflow that really understood the components of how they do do things.
[00:00:25] And took that, the friction down from that process, from like it would take me five to seven days to actually complete the end to end process to basically three minutes.
[00:00:38] Mike Allton: Mike's got The Hat, the AI kind. Unlocking power in business, you'll find. Cut through the hype, explore the tech. Every week, new ideas to check.
[00:01:12] Allton leads us on a digital quest. AI secrets, he'll always invest. Tune in tight, don't miss a beat. Knowledge, groove, keep you on your feet. Listen up! To the AI flow. Business growth, here we go. Cuttin' edge insights, that's the plan. With The AI Hat you'll understand.
[00:01:47] Greetings program. Welcome back to The AI Hat Podcast where I selfishly use this time to pick the brains of experts at keeping up with and integrating or layering artificial intelligence into social media, content, advertising, search, and other areas of business and marketing. Oh. And you get to learn too, subscribe and be shown to prepare yourself and your brand for this AI revolution and come out ahead.
[00:02:09] Now, I know what you're thinking, Mike. We've heard about Ai, we get it. It's revolutionary, blah, blah, blah, but here's just a million dollar question. Are you actually seeing those eye-popping results in your own business? Are you doubling your qualified leads or saving tens of thousands of dollars with a single automation?
[00:02:26] If you're shaking your head. Don't worry, you are not alone. And that's exactly why today's episode's gonna be a game changer for you. We're cutting through the noise and the hype to bring you real, tangible examples of businesses that have cracked the code on AI implementation. No more theoretical possibilities or vague promises.
[00:02:43] We're talking cold, hard facts and replicable strategies that you can start using in your business tomorrow. To guide us through this AI success story Safari. We've got a true. Trailblazer with us. I'm thrilled to welcome Sara Davison, the mastermind behind the Maivenly, the AI Business Growth Accelerator.
[00:02:59] Sara isn't just talking about ai, she's in the trenches turning AI potential into profit for businesses just like yours. Get this, Sara has helped clients save over $40,000 a year with a single. AI automation. She's worked with companies to double their qualified leads in just a month, a feat that used to take them half a decade.
[00:03:17] And the best part, she's here to spill the beans on how it's done. Hey, Sara, welcome to the show.
[00:03:24] Sara Davison: What an intro. Thank you so much, Mike. That was really fun to listen to.
[00:03:29] Mike Allton: My pleasure. And like I always tell folks, first of all, Claude helps me write these, but more importantly, you're the one doing the work.
[00:03:35] And so I'd love if you could just start by sharing your journey into AI and what led you to focus on helping businesses implement AI for growth.
[00:03:44] Sara Davison: It's a great question and first of all, thank you for having me. It's been such a pleasure to connect with you on social, so it's great to actually do this.
[00:03:52] Not quite IRL, but yes, but we, I guess my story is very similar to a lot of people. Where I was starting to pay attention to what was happening in the whole AI space with ChatGPT. And then I just went down that rabbit hole and I couldn't find the way out really. I just got obsessed and it was really just, just keeping apol in my finger on the pulse on what was happening and spending a lot of time experimenting and doing, research into things.
[00:04:21] Until. It consumed me and I figured maybe I should make a career out of this since I love it so much. And it's, it's been such a great experience. A lot of fun, a lot of really challenging but overall, so, such a satisfying experience for me.
[00:04:37] Mike Allton: That's, that's awesome. And before we get into the stories, could you just clarify, when you say make a career out of it, what, what exactly are you doing with AI today?
[00:04:46] Sara Davison: Yeah, so, I have an AI implementation agency called Maivenly where we specialize in helping ai companies scale their operations, scale their business through AI and agent workflows. I know that sounds a little bit like, what is that even? But we specialize in working with probably growth sage companies.
[00:05:08] We've worked on either side of like, from a lower amount to a higher amount, but that five to $50 million marks seems to be especially my sweet spot in helping them, integrate AI into their businesses in a way that helps them scale.
[00:05:23] Mike Allton: No, that, that makes complete sense. And I've said a couple times, we haven't talked about AI agents a lot yet.
[00:05:29] Right. On this show. 'cause it's like one of those aspects of AI that we're just on the cusp of being able to utilize. A lot of the AI agents that we see out there, like Salesforce, they're really just really smart automations. Mm-hmm. They're not. Mm-hmm. The true AI agents that're mm-hmm. We're seeing coming on the horizon.
[00:05:48] But to your point, there are really, really incredible things that folks can do with agents, with automation, with generative ai and it, and it takes a skilled hand to help them understand what's possible and how to actually employ those in a very smart way throughout the business. So, I'd love if you could, just share an example of a business that maybe was initially skeptical of Ai, but as a result of working with you and implementing AI in various aspects of the business, they ended up seeing some pretty remarkable results.
[00:06:19] Sara Davison: Yeah, we and this is the fun part of what we do because we're industry agnostic and so I learn so much about all different types of business problems that, business owners face and business leaders are trying to traverse and different models and all that kind of stuff, which makes things really interesting.
[00:06:37] I guess one par particular example I could think of is with a professional services firm who is like a global training company. They train NGOs, police departments, regulatory authorities on specific types of investigative interviewing. And so, they're, they develop essentially very nuanced course material, as you can imagine, that's designed for each and every client, but is weighted within a specific type of methodology.
[00:07:09] Methodology that they teach. And so. This particular process that was in their business is obviously very critical, which is, creating course material and developing a training material for each individual client. And you would think, because I feel a lot of people are like, oh yeah, I know the ChatGPT thing, but I'm constantly having to go in there and edit and I can't see it being like an actual AI workflow.
[00:07:36] So we, when we went in there and we consulted with them. We had to really understand their process, so we can essentially take that process and the way that they approach it and teach inverted comment, comment marks the AI on how to do this. So this particular process that is critical to their business.
[00:07:57] Is obviously critical to them being able to conduct their business because that's the core of what they offer, but it was also the biggest bottleneck in terms of hours that it would take. It's, they require a lot of people with a lot of knowledge to understand, the background, the regulatory context, the actual methodology itself.
[00:08:18] So there's not a lot of people who can actually do this. And that was costing them around 40 thou, 40 to $60,000 a year in just labor cost. But more important than that, it was a bottleneck within their business because the more clients that they took on. They were capped because they only had a few people who were able to do this process and they couldn't scale beyond where they were.
[00:08:43] So what we did is that we really understood their process, their workflow, and how they, their ideal output look like. And essentially built an AI or an agentic workflow that really understood the components of how they did do things. And. It took the, the friction down from that process, from like, it would take them five to seven days to actually complete the end to end process to basically three minutes.
[00:09:14] Where the majority of the work was done with ai and then the person after that would just, be reviewing and checking and editing. So that in itself saved them that roughly that amount of money, 40 to 60,000. But even bigger than that, as we're monitoring the ROI on these projects and how they really impact the business in the future.
[00:09:35] So they actually increased their revenue. They were able to scale by a, around 600% from the revenue perspective. So, it's really, I feel like there's a lot of. Focus in AI around, oh, what can I do additionally? Like, what can I create more of? But the part that actually really excites me is that for a lot of businesses, your growth is like right there. It's probably in this big hairy problem that you have, this big hairy process that you can't really reduce the friction off that's causing the friction in your business. So I feel like that's a good example to share because it's not just about like putting out more blog posts or whatever it is.
[00:10:20] It could be reducing a friction that's in your process that helps you unlock the growth that you're looking for.
[00:10:26] Mike Allton: I, I love hearing that. I love seeing these kinds of unexpected benefits. Yeah. Of implementing ai. I was, I was talking to a group of students from Otterbein University just last night, and the instructor was asking me, what are we, if we're saving all this time with ai, what are we, what are we gonna do with the rest of our time?
[00:10:45] And I was. I was amused by the question and, and, and thrilled at the same time because one of the beauties I think of, of artificial intelligence is that if we are able to save ourselves 2, 5, 10 hours a week mm-hmm. We now have that time to think about what else we might be able to do. Right now we're so busy running in our rat races to keep up with everything we're supposed to do.
[00:11:08] We just don't have the freedom to dream and explore and really, really just sit and think about what else we might accomplish. Whether it's scaling the business mm-hmm. And achieving more ROI or just doing more creative kinds of things. So I love this story. Are, are you able to share any more specific details about, the, the process that you guys created, what tools perhaps were involved?
[00:11:31] What did that actually look like?
[00:11:32] Sara Davison: Yeah, we, we did that particular workflow within Respell, which is a platform that we use quite regularly for more custom work that is. It requires a lot of flexibility for you to be able to really tailor the workflow to how you want it. So, not a cookie cutter approach, but a really nuanced process.
[00:11:56] We find that that is a great platform. We use cassidy.ai as a platform a lot. We actually teach our students how to use it 'cause it's a, it's an incredibly powerful way to build an AI first company. But regarding that particular work, the, the case study that I provided, the key was really understanding the human process.
[00:12:17] And really understanding how to mimic the human process in terms of what's called shot prompts. So these are essentially the examples that you give to the AI system to let it know when I give you the prompt to to perform a certain task a certain way. This is what I mean. When I ask you to produce content that is, professional, yet witty yet, whatever.
[00:12:42] So that is where we spend a lot of our time actually with within the workflows that we built, especially for these more nuanced ones that have a big amount of subjectivity to it versus objectivity is really understanding from the client process. What a five out of five looks like, what a three out of five looks like, and then really trying to bridge that gap with the techniques that we use.
[00:13:09] So we know that's a big part of what we do is the prompting, the shot prompts. We conduct what's called evals or evaluations, which, which is really key and not a lot of people talk about to. Ensuring that you can continue to scale that output at a consistent level continuously. And it's a very like human centered process to begin with until you teach the system.
[00:13:36] This is the benchmark that you have to actually meet each and every time that you produce this output. And then it learns through feedback. Okay, well, if the benchmark is 96%, but our output is now at 94%, then we need to ping the humans and let them know that we need to like bridge the gap somehow and suggest the changes.
[00:13:56] So it, it's a bit of a, f maybe sounds a bit technical, but there's no, I don't code, I've never written a line of code in my life. I just have learned how to leverage these systems in the way that they work really well.
[00:14:12] Mike Allton: Love it. And you're, you're mirroring a lot of what former guest Katie Robbert talked about.
[00:14:17] In her interview you talked about what the work that they do at Trust Insights and her five P's framework, because like you, she's putting people first. Yeah, absolutely. And always having this feedback loop in the process. I'll, I'll link to that in the show notes for you guys to make sure you go back and listen to her episode as well.
[00:14:31] Now, one thing, Sara, that you'd mentioned to me before was that you doubled the client's qualified leads list mm-hmm. In a month. Mm-hmm. And that is super impressive to me. Mm-hmm. How exactly did AI make that possible?
[00:14:45] Sara Davison: AI is really great at pattern recognition, right? So we this particular client had multiple franchises across the country in different brands but in the same kind of industry.
[00:14:57] And we, we, we basically looked at and analyzed, what their ideal client looks like what are the industries, what are the, the, the level of their, connection, where do they actually live? Where do they actually stay? And so, how do they network? All of that kind of information.
[00:15:19] We we were able to gather and create these more nuanced understanding of their ideal customer persona and then use different tools within in AI like clay. That's a very popular one, apollo.io. To really build that list based on what we know is their ideal client profile. And yeah, and, and AI is like a very powerful way of being able to identify and actually gather that information. But this is the trick to it, is that yes, you have all of these powerful tools, but you need to have a really good understanding of, what good looks like in the first place. So again, it comes back to the success of these projects. Depends on the success of the humans that are part of the process that enable us to build the, the picture or the design the outcomes that the business is looking for.
[00:16:18] Mike Allton: That, that's a great point because I can give you all the leads in the world, but if you don't have a good sales process or a good follow up process to actually leverage those leads, exactly. Not much is gonna happen. Do you have any insight with that particular customer? What happened next once you developed, yeah,
[00:16:33] Sara Davison: we're, we're actually going through a process where we're building exactly that for them, because now that they've had a, and this is something that we advise a lot, when it comes to AI, is that once you pull the lever with ai, it is such a, it has this amazing ability to scale, but if you don't have the ability to receive that growth, then that could like actually break your processes and your systems and put strain on it down the, down the way. So what we're doing with them is we're actually building a kind of more system around how, there we have a research agent that performs, like research on the clients before they call and like basically sets up the automation for the calendar and briefs the person who's gonna get on the call about the client and all of that kind of thing.
[00:17:24] So, that's one of the things that, like we've been learning as we've been doing these implementations is like really, really considering the downstream effects of when you implement ai. Because they can have, your business is a system at the end of the day, and if you each make changes in one part of the system, you need to consider the downstream effect of other parts of the system.
[00:17:47] Mike Allton: So. Love that perspective. Thanks for sharing that. Now, you mentioned coding earlier, which which was interesting. I was an actual computer coder, so I'm fine, jumping into JavaScript or HTML or anything like that. But I know many listeners aren't, many listeners are worried about the learning curve overall with ai.
[00:18:05] How do you help businesses overcome that kind of hurdle? And do you have a success story that you could share that illustrates that?
[00:18:12] Sara Davison: Yeah, so I feel like it's really, educating and then showing people what's possible right from the get go. We like to, like, when we have clients meetings, we actually, we've gotten to the stage where we can actually build light MVPs on the spot, or we show up to a, a client meeting with one if they have certainty around like what it is that they're looking for. And I think that the, the strength in that is showing how quickly you can move with this technology now without needing to be technical and without, necessarily this project that could have taken six months can not be done in like, three weeks or something like that with the testing and iteration and things.
[00:18:58] But I think for the, a lot of people and businesses who are entering this space, it's like they just don't know what's possible. Right? They have an idea of maybe, they, they may use ChatGPT they may have started, playing around and experimenting with different AI tools and that's a really helpful, introduction to what is possible. And that's usually when they come to us, they're like, I feel like there's more, I don't know what it is, and I don't know what's possible. And then when we, sit down with 'em and, and workshop, like, what is the, what is the thing that is going to be bring the biggest amount of impact to your business right now that you just haven't been able to solve for?
[00:19:43] I haven't come across a situation where we haven't been able to do that. And that's like the, when we, we walk in with an MVP, a light MVP, or we build something really quick on the spot and the just the like, holy wow. How, how did that just happen? Is like both, we have to tread lightly on that because it could be both terrifying a little bit and incredibly exciting.
[00:20:08] To see what's possible. But for us like that, because we are very implementation focused, that's how we have those conversations. I know there are more consultants that are more like strategists and they talk about the possibilities and like the impacts of, strategy and AI and things like that.
[00:20:26] But we're, we are like, we, we approach things by making AI really, I dunno what the word is crystallize. We crystallize the power of AI within people's businesses by actually deploying AI and integrating AI into their systems.
[00:20:46] Mike Allton: One difference I think that I'm picking up on between your approach and, and many other people's, and I understand the context is a little bit differently.
[00:20:53] You're, you're being paid to come into a business versus somebody who might just be listening to a podcast. But I often hear advice to start small. Yes. Pick, pick really small, limited pilot projects and start there. Whereas you're talking about, hey. Let's talk about the biggest, worst, most impactful thing that's happening in your business today and see how we can tackle that and solve this for you.
[00:21:14] Yeah, with ai, which is I think a radically different approach, and I find that fascinating.
[00:21:21] Sara Davison: So the biggest, the big hairy like problem often isn't like this big, hairy pro. It's, it's not the whole entire business. Often it's like when you're speaking to business leaders or business owners. It is a big hairy thing because of the impact that it has on their business, but it's not the entire business.
[00:21:42] So like that company that I mentioned at the beginning where we, we had the workflow that essentially automated a lot of their actual doing work of creating the training material for different organizations. That wasn't their whole entire business, but it was a critical part of it. And that they knew was like their bottleneck that's in their business.
[00:22:01] So. I feel like that, from, from our perspective, like we had another client also in professional services that again, had this, I guess it's a similar process where they're a, how do I put it? Without being with, with while being careful. So they do consulting to organizations on their technology roadmaps and strategies and come up with like a, five, five year plan or whatever it is. But, and they're industry veterans that, have been conducting this process. And as there's a lot of nuance when you are in the consulting space and you're gathering, you're meeting up with the client, you're like gathering all of this information.
[00:22:46] And then you're having to synthesize it and then really put that like context on of how, what does this look like? What is, what is the current state of the client and where do they wanna get to? And, and what does that roadmap look like? So that entire process. We were able to work with them within a, an agentic workflow.
[00:23:06] We built one for them. That the client, again, like to your question, they were like, you can't, like, it's not possible that AI can do this at the level of industry veterans who are, who've been doing it for years to this degree of something that is so personalized and nuanced and requires a lot of strategic thinking and insight.
[00:23:26] And they scored us an 11 out of 10, so, so there you go. Yeah, they're very happy with the workflow. And again, it's not like we're redesigning their whole entire business, but it is a critical part of their process. As we're able to reduce the friction in that process and the time that they're spending actually gathering, synthesizing, and then reworking, to get an outcome.
[00:23:51] Significantly. So now they're in a position to like take on five times as many clients because they have the capacity to do that.
[00:24:00] Mike Allton: I think that's one of the, the common surprises and the skepticism that I hear because most people's experience so far with AI is they'll open Chat GPT and they'll say, write me a blog post and it will write them a blog post, but it's gonna be crap because it's just gonna be the most average mediocre post it could possibly come up with to answer your question, 'cause you didn't put in the pre-work to tell it.
[00:24:22] You know who you're trying to talk to, how you communicate as a business, as a brand, or as a content creator and all the other nuanced work that has to go into creating really great content. But if you do those things, yeah, AI can come up with some phenomenal results. And that's just a tiny little example from a generative perspective.
[00:24:39] The agentic stuff is fascinating. Folks, we're talking with Sara Davison about the many ways that AI is helping. Businesses grow and scale today, and I've got a bunch more questions for her. But first, a quick word from our sponsor.
[00:24:51] This episode of AI for Business Leaders, The AI Hat Podcast is brought to you by Magai. Tired of juggling multiple AI subscriptions and trying to figure out which tool to use and when? Magai simplifies AI for businesses by offering access to all the leading language models and image and video generators for one low price.
[00:25:11] With Magai, you can create custom instructions to personalize AI for every business need, and use them across all LLMs, including Chat GPT, Gemini, Claude, and even Deep Seek. No more building custom GPTs or gems that are limited to just one platform. Magai also lets you create customized workspaces for your entire team, giving everyone in your organization access to the same AI assistance and tools and prompts ready to streamline your AI workflow and empower your team.
[00:25:40] Tap the link in the show notes to visit Magai today to learn more, and now back to the rest of today's episode.
[00:25:48] So, Sara, we talk about sales and marketing on this show all the time, but another critical area for businesses, I think, is making sure that customers are happy, that they're not churning, that they're growing, that they're, creating opportunities for upsell and referrals and those kinds of things.
[00:26:03] Could you share an example of a business you worked with where they used AI to actually enhance their customer experience and what some of those results were like?
[00:26:12] Sara Davison: Yeah, we, AI is great for sentiment analysis as well. So, one of the things that we're that is possible, like especially when you think about large, customer service teams and businesses that, produce a lot of volume and the need to keep up with all of the inquiries and things like that is the ability to quickly triage.
[00:26:36] Like what. When a, an inquiry comes in where it should be going, where how quickly it should be responded to, things like that. So, it's actually something that we are act teaching as part of our course to our student who are learning how to build all these things. Is, is we're, 'cause we teach by, learn by building is to teach them how to actually build a.
[00:27:01] Agentic or an AI assistant that can actually sense the sentiment off a particular, inquiry when it comes in. And then as part of the workflow where that inquiry should go. So that is an example of how AI can be very helpful in terms of being able to process, a large volume off these.
[00:27:31] High touch processes and communication points at scale. But the key to that is, is ensuring, and we teach a lot around this for anyone who is considering, implementing ai, where there is a customer touchpoint to have that human in the loop process because there are, there are, things that you need to be aware of that may impact the ability of the AI to, to process and to be behave in inverted common common marks how you are, how you would like, and there's a lot of pro, like, especially for customer facing things where, you're putting AI in front of the customer.
[00:28:16] I would, we, we teach a lot around having a human in the loop as part of the process and making sure that you are incredibly confident with your prompting, with your shot prompts, with your, evals and all of that kind of thing. That would be my, my kind of perspective on it.
[00:28:36] Mike Allton: Yeah, that makes a lot of sense.
[00:28:37] And you're absolutely right about AI's capacity for understanding language, nuance sentiment. We talked to previous guest, Sunny Hunt at length about how she was using AI at a university to analyze student responses to a questionnaire, to an onboarding survey because they wanted to do an outreach campaign and they wanted understand how students thought about.
[00:29:00] Certain topics, and this is an exercise they did regularly. They would spend, to your point, like four weeks analyzing these survey responses. 'cause if anyone's done survey responses, you know they're open-ended questions. So someone has to literally read each one and then bucketize categorize, tokenize what it is that person said, were they responding?
[00:29:15] Yay, no bad, good in different whatever. But AI can do that in moments, yeah. Tens of thousands of responses and categorize them all swiftly. You still need that human to review it. Mm-hmm. But it just, it moves. Yeah. So much faster
[00:29:30] Sara Davison: we're, it was, it's funny because we have someone who is currently doing our course, I just found out yesterday.
[00:29:37] So we, we teach people how to conduct evals or evaluations, which are incredibly important when it comes to, especially, especially anything that has like the. AI to human connection because you're, you are wanting to maintain that benchmark and. And undergoing that process. Like you say that the person spent four weeks actually, or really feeding into the system what, what, what kind of responses, how to categorize them, what they actually mean, what good looks like, what bad looks like.
[00:30:10] So we are teaching people how to do this as, as part of the eval process and they have to do it. It's very, very manual, but that's how you get the confidence down the track to be able to, have a certain degree of confidence around having AI interact with, with humans because you have gone through the process of an inverted mark.
[00:30:32] I'm just trying to like. Not be too technical teaching the ai, why you graded it a three out of five instead of a five out of five. So every time you're doing that manually as a human, when you see the output what you're doing is that you're bridging the gap between a three out of five and a five out of five for the system.
[00:30:52] So then you, the more that you do that, the more you shorten the gap because you're actually explaining what a five out, five out of five looks like. The delta gets shorter between that gap. And she so she was like sent us, 'cause we review all of our projects that they give us through the course and she was like, this was the most painful thing I've ever had to do because it was a CSR like scenario.
[00:31:14] She's like, why should I be doing this? Because I could, as a person who's managed. A team of 100 people, like I could actually be responding to these emails. It's faster than I'm doing these evals for the ai. And we're like, that's the point is that, you'll get to the stage where you will be able to delegate to AI with, with a lot more confidence because you, it's, it's like you've onboarded someone new into your team and when they start, they're, they're gonna try to figure out what a five out of five looks like.
[00:31:48] But they're probably gonna be doing tasks at a two or three out of five. So this eval process is like I was trying to explain to her, is like, you are coaching the new per person and say, I scored you a two out of five for these reasons. Now this is what a five out of five looks like and that. Process exactly like you would do honestly with a human, is what we're doing with in the system, even though it's not a, it's not a human, but it's the same kind of learning, mimicking the learning process around that.
[00:32:20] But yeah, it was funny 'cause then she got it. She's like, oh yes, that's why I would wanna do this because I doing those emails.
[00:32:27] Mike Allton: I, I just wanna underscore the importance of, of what you just shared, because again, most people today, they're using generative ai where they, they prompt it and they get an output, and they're able to read that output.
[00:32:38] They can make changes that they want to, but they have total control over what happens next. As we move into more and more automatization and autonomy mm-hmm. With AI agents and eventually a GI, there will be fewer and fewer instances where the human isn't actually controlling what the AI does next. So we've gotta have these operations upfront where we're evaluating, we're testing, we're reviewing, we're instructing, we are teaching keep putting it that way.
[00:33:07] We're teaching the AI what we expect. That way within the next three to five years, there's gonna be so many things that the AI is gonna be able to do for us, and it will just know exactly what we want. But another concern then that comes up when people hear me say things like this is, does that mean we're not gonna have jobs?
[00:33:25] Right. A lot of people are concerned about the AI replacing us, replacing our roles. Have you seen examples where the AI has actually empowered employees and improved job satisfaction?
[00:33:38] Sara Davison: Yeah, I think overall. My sense? Yes. Anyone who tells you that they know exactly what's going to happen in the future with ai, like just maybe question mark.
[00:33:48] But I feel like we, all of the functions remain the same. We're still gonna have marketing, we're, it's gonna have sales, we're gonna have these operations functions. The way, the roles themselves, I feel will change. Like the actual job description will change from, from where, from what we consider to be typical roles right now, in the sense that I feel like we will be elevating how we operate with these systems in a much more, like oversight, collaboration, hu like the human oversight and the, you are almost like the narrator of the process, and the execution, more of that kind of thing is going to be done more and more with ai, with human oversight. I feel like it is definitely a concern, and obviously we're seeing it, play out in the market around jobs being, people losing their, their jobs and things like that.
[00:34:46] And I really feel that. I know my advice to people who do have that concern is to actually, learn the skills because it's, we're at such a pivotal point that having skills off learning how to work with these systems is incredibly valuable and could be a way that you actually feel less, what's the word?
[00:35:12] You feel less a victim of the process and more, a driver of the process. I certainly feel more like that because I have, spent a lot of time building up these skills. But I also feel like when people start to get those wins and start to see it play out on a day-to-day basis in their businesses and in their work they start to embrace it more.
[00:35:36] So, like as an example, the first case study that, that I shared, the people who work for that company are the probably the most atypical people that you would think that, would embrace ai, they, a lot of them come from like, police backgrounds and, detective backgrounds and things like that.
[00:35:56] And we are creating, like, we're onboarding them into be becoming an ai, enabled company. And it's a process. Not everybody is on board straight away, but you have these people who are the, the people in the companies that are, are like the, what are they called the advocates and that process of them kind of taking on that role encourages more and more people to, to join in and see what it's like and experiment and just being, having that environment where they feel a lot safer within, with how they interact with ai.
[00:36:32] Mike Allton: That's fascinating because as to your point, you're not talking about programmers. You're not talking about people who've necessarily been working with technology day in and day out in their roles. I'm sure they're familiar, but that wasn't their job, per se, and yet they're seeing success. What do you think some of the differentiators are that are actually allowing certain businesses to succeed with Ai, where others seem to struggle?
[00:36:55] What's the difference?
[00:36:56] Sara Davison: From a business perspective or from a, like from the, from a workforce perspective? From like either. Okay. So I think the businesses, and obviously this is dependent a lot on the size of the company and things like that, but from the point of view of business leaders who just have more of a, ability to help their staff embrace the technology. That, you obviously have to have policies and guardrails and really call out what those no-go areas are in terms of how you want your organization and the people within it to, to work with AI and to experiment, but also the businesses that are enabling their people to take a lead around it.
[00:37:44] Have a team off a few core people who, who are putting their hands up. They're pro, they're likely already using this technology and just having, the space to say, yeah, we we're going in this direction and we want you to be part of helping us define what this looks like.
[00:38:01] You're the people who are doing the work on a daily basis. So you help us define and let us know what makes your work better with this technology. And having both like a two-sided conversation about things rather than. Then, people trying to guess about what their future is in their job and what it looks like and having less control over the process.
[00:38:23] Yeah, I, I think that that's it. We have a, a few CEOs who have taken our existing course who are now like. Going down the path and putting their, their, like a few key people from their teams in this course because they can see that giving people those wins and that those skills is on and on a really practical app, applicable basis.
[00:38:48] Like they can actually apply this technology to help them with their roles. It's what's gonna drive the adoption for other people in the broader team. So I think that that's. From my observation lately, that's, that's probably how I would encourage people to look at it if they can
[00:39:05] Mike Allton: love that.
[00:39:06] And for our listeners who are getting inspired by your stories, by some of these examples, what would you say is one actionable step that they can take this week to start unlocking AI's potential for their business?
[00:39:20] Sara Davison: I feel like if you haven't. Played around with chat GPT. Please do. If you've played around with chat GPT and written it off because you answered a question and then it gave you something completely not part of what you were expecting or wanting.
[00:39:39] Invest your time into into the technology. That's how you become. And, enabled with this technology is, it doesn't, doesn't click straight away. You learn, like you say, like you said Mike, about, well, if I, if I just write a random sentence, this is what it does. But when I give it more context, when I give it more richness than the information that it has to work with, then I know that it's gonna produce these results.
[00:40:05] And then you find out. I feel like ChatGPT is a really great entryway into understanding both the strengths and the limitations and how to work with these systems because in addition to like, oh, I've suddenly got a superpower because I can like now prompt and I can like really get the results that I want, but then it's hallucinating, and it's making stuff up and just your daily interaction with these systems, even if it's just ChatGPT, is going to give you a really like next level of awareness sense of how.
[00:40:38] This technology actually works. What are the strengths? What are the limitations? But I would just definitely say as much as you can build that muscle. So you are working with this, you were working with AI on a daily basis, that it becomes part of your workflow and the next thing you know, you're like, how did I ever get anything done without this?
[00:40:57] Mike Allton: Absolutely Sara, the work that you're doing is absolutely amazing. I appreciate so much that you've come on and shared the results and the details of the kind of work that you're doing for, for clients. But for folks who wanna learn more, they want to connect with you, maybe find out, how you could help them, where should they go?
[00:41:14] Sara Davison: Best to connect with me honestly on LinkedIn. I'm always there answering dms and I'm very present there. So that would just be Sara Davison and you should be able to find me.
[00:41:27] Mike Allton: Terrific, and we'll have all of Sara's links in the show notes below. That's all the time we've got for today, friends. But remember, if this is your first foray into the world of AI marketing, I've got that perfect resource for you in the show notes below the AI Marketing primer designed to quickly get you up to speed on terms, tactics, and the underlying technology that's powering this AI revolution.
[00:41:47] Check it out and I will see you in our next episode. Welcome to the grid.
[00:41:51] That's a wrap on another episode of The AI Hat Podcast. I hope you've gained some valuable insights and actionable strategies to boost your business with Ai. If you enjoyed this show, please subscribe, leave a review, and share it with your network. And don't forget to visit the ai hat.com for more resources and to connect with me.
[00:42:10] Until next time, keep innovating and remember, the future of business is human and it's powered by Ai.
