Building Your AI Dream Team - Who do you really need?

While technical skills are a big part of AI implementations a passion for problem-solving might just be what matters most. 

Alane and Micah dive into the real secret behind successful AI implementations - and it's not what most business leaders expect. After working with 150+ companies over 6 years, they've seen HR professionals become AI champions while seasoned developers resist change.

In this episode, you'll discover: 

• The 4 essential roles every AI-powered business needs (and why your IT team might not be one of them)
• How to identify your hidden AI champions across unexpected departments
• Why knowledge sharing is the difference between one AI rockstar and an entire AI-powered team
• Real examples of companies finding their champions in accounting, customer service, and HR
• The mindset shift that separates thriving AI adopters from those still stuck in manual processes

This isn't about hiring the most technical people or spending the biggest budget on AI tools. It's about creating a culture where AI makes everyone better at their job. If your competitors are experimenting with AI while your team is still copying and pasting data between systems, this episode shows you exactly how to catch up and pull ahead.

Ever wondered why some companies seamlessly adopt AI while others struggle? The answer isn't in their technology stack - it's in their people strategy.

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For more information, visit our website at biggestgoal.ai.

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Transcript

0:00:00 - (Alane): Welcome to Automate Your Agency. Every week we bring you expert insights, practical tips, and success stories that will help you streamline your business operations and boost your growth. Let's get started on your journey to more efficient and scalable operations.

0:00:18 - (Micah): So, Alane, for this episode, I've had this. This thing on my mind. That's how quickly not only automation and AI and AI agents and databases and all of that stuff is changing, but what that means for teams. So essentially, who do we have to think about employing, hiring, or finding contractors or vendors? Right. Like, how do you get this done now? I thought that'd be super interesting to talk about.

0:00:49 - (Alane): Yeah. Because there's even a change and just how much capacity each person has for. For more knowledge on something. Like, we have to be so niched into our expertise. Like, I can't do what our clients do. Like, I don't have the capacity to learn and be experts at what they do and be an expert at what we do.

0:01:09 - (Micah): Yeah, yeah. You mean you don't want to fully know every business that we've ever worked with and then also do that. But, you know, I know where. I know I just kind of made a joke about it. But at the same time, that's so real. Because if you flip. If you flip what you just said, then none of our clients really have the time to learn what we do, to be able to implement it within their business. Yet, you know, a lot of times you hear about, well, it's just super easy.

0:01:39 - (Micah): And I think I'm even guilty of this sometimes, too, is I'll look at it and go, I instantly know how to automate that. I know how to implement AI agents. I know we need to use a rag database for that. I'm already throwing out terms that for most business leaders will probably be like, wtf? I have no idea. Start slower.

0:01:58 - (Alane): Yeah. I mean, we make fun of you behind your back.

0:02:01 - (Micah): I know that it's not behind my back.

0:02:04 - (Alane): We do it to your face, but it's like, oh, it's super easy. Yeah. Because this is like how your brain works. This is how your expertise works. I can talk about these things, but I need to have our team of experts even being able to implement them, but in. Even with my own.

0:02:19 - (Micah): You mean even internally?

0:02:20 - (Alane): Yes, internally.

0:02:21 - (Micah): Yeah. So, like, you have an idea or you're talking to a client and what you're saying is then you'll go to our own team of experts to help validate or understand how it might work.

0:02:31 - (Alane): Right, right. And there's layers to this. There's Layers to even know what's capable. Like, I can do and talk about with clients and having that knowledge that maybe they don't have. Just like, I don't know how to design blinds, like shades for your. For curtains and windows. Like, I. I don't know how to do that. But I can help you with your workflow on where those pieces could be automated. And that's where I see, you know, layers of this knowledge happening is like, what is capable and what can you. What can you even solve? And then the whole nother piece is, well, how do you even implement and build that?

0:03:07 - (Micah): Yeah, absolutely. And how. So I think that's exactly getting to the crux of what I wanted to chat about today is the end result. Like, good art looks simple, but to get there, there's a lot of expertise, a lot of layers. So what do the listeners of this episode and of our podcast and of agencies and of almost any business, who do they need? Like, what do they need on their team? Who do they need to.

0:03:40 - (Micah): Whether it's on their team or hiring, you know, vendors to help them through this? What are all the. The different layers?

0:03:48 - (Alane): I think one of the things that I see is somebody that internally that is excited by this, that's not threatened, that they're passionate about the ways that it can help strengthen their strengths. I think that's a starting point. Who. Who on your team is excited about this man?

0:04:07 - (Micah): That could be a podcast in itself. Alane, I think you just like what I think about when I. When I was thinking about this episode and what we could talk about. Of course, I come at it from a technical point of view. What I love about these conversations that we have is we didn't rehearse any of this, but you're coming at it from a totally different perspective than I would have even thought about this.

0:04:28 - (Micah): And I think what you just said is so important because I can think of so many times where we have been chatting with teams, prospects, or clients, and there's somebody that is in charge, that has originally been put in charge of this, and they are not excited about it. They don't want to do this. They don't want to make changes. They don't care about automation. They don't care about AI. They don't see it as a, like, way to enhance their work or their work life or anything.

0:05:00 - (Micah): They just don't want to change. And it puts this giant roadblock up. And so, yeah, geez, that's huge.

0:05:08 - (Alane): Simple, right? But so hard to execute on. Like, typically, we want to assign Things like that, hey, you're in leadership, you're in this department. You go and figure this out where they might, they may need the support. This stuff is really new. And the, the podcast that they're listening to, the articles that they're reading may not be about AI, AI agents, automation, those kind of things. And so they're starting from square one. Whereas you might have somebody on your team that is just itching with excitement for this kind of stuff. So that's like one thing that I see work well at companies.

0:05:46 - (Micah): So I've got an awesome example of that that just happened this last week. Okay, we have a client. They're a decently large client, one of my favorites to work with, and they're one of their HR people. Of all the departments you could think would be excited about AI and AI agents, one of their HR people loves the concept of AI. As soon as GPT agent mode came out, they were all over that. And so internally that's become kind of a go to person for them.

0:06:21 - (Micah): To your point, like you wouldn't think, oh, you know what, I'm going to go to HR and get some AI. Yeah, some AI insight or have that be a point of contact or a champion for this project. But here we are, they've got an HR person who absolutely loves that and 100% would make an amazing champion and point of contact.

0:06:42 - (Alane): And on the reverse side, I've actually seen in tech some of the slowest growth for, for employees wanting to adapt because they are used to doing things a certain way, take pride in how they do things and, and maybe are more apprehensive because they feel like they're already in the tech mode. And so all these other departments might have your little AI champion in there.

0:07:06 - (Micah): I could see that too. Even just coming from my perspective. Right. Coming from a tech background, it seems almost trivial. Like I could just build this myself this other way. But if you look at the other departments and the other team members, they're going, I've been copying and pasting from one platform to another platform for three years and it sucks. And I don't have the technical acumen to write my own code to do all of this.

0:07:32 - (Micah): But maybe now I do. Maybe now I can explore this and maybe now I can work this out. And that excitement is what, maybe that's what you're seeing between tech versus non tech.

0:07:43 - (Alane): Yeah, it could be. One of the friends of mine that I was talking to, they implemented an aizar at their company and they were tasked with finding opportunities that AI or AI automation, whether it's AI agents or automation with AI could be implemented and they were stoked and they've been able to transform different things within the company. But the key piece of this is, is that they have the support of leadership, whoever that AI is, or whatever you want to call them, is that they're not just putting these ideas out and then being shut down and shut down and shut down, because that's a way to just tear apart your culture.

0:08:21 - (Alane): But if you're going to say this is an initiative of the company and we've got the person that's just so excited then having the support there for getting their ideas into fruition.

0:08:32 - (Micah): Yeah, yeah. And I think you know what you're describing here. It's interesting because specifically the non tech people on a team, they already know the workflows, they already know the operations, they already know the problems. So like what you just described is kind of what was going through my mind when I was thinking about chatting about this today, which is you do have to know how things are working. You have to know the operations. And then you, you pointed out something really great, which is, okay, if you know the operations, if you know how you're doing something currently and you know the pain points and you know it sucks then and you're excited about AI.

0:09:13 - (Micah): All right, well like can you, can you bridge those gaps? Can you identify those areas and go, I think AI might be able to help me with this.

0:09:22 - (Alane): And one thing we do need to keep in mind is while we're here for supporting those team members is they may not have the skills for implementation. That is a very different skill set than an idea and a concept of something working and then being able to go and build it. And, and this has even changed with our own team and how we are, I call it developing now where we're developing AI agents.

0:09:44 - (Micah): Because you have, we're all calling developing now.

0:09:48 - (Alane): Yeah, because you do need to be such a technical person in understanding databases and database structure and how things can work together that a person like me off the street or even somebody that's just really passionate about AI and build in maybe some zaps and things and make may not be the best skilled person to go into N8N and build AI agents. Most likely they aren't.

0:10:14 - (Micah): Yeah. So, I mean, so what we have so far is you need leadership. Who's going to say 100% this we, we're going to do AI initiatives. Then there's almost like a visionary, maybe multiple visionaries across your team who understand how things work currently and have a passion for AI. And then you have an implementer or set of implementers, a team of implementers and those are going to be your technical experts who can take the vision and run with it and ask the questions and go, okay, well where is the data?

0:10:50 - (Micah): What do you, what's the triggers? What are the actions that we want to have happen? Where do we want the output of this to go? What should it do? What should it look like? All of those things should go to an implementer role.

0:11:04 - (Alane): I've even seen a change. So we have a coaching package within our organization that we have some clients on where we're there for weekly support, but we're not doing implementation. And something that I'm seeing more coaching package is what is happening is they need AI support because they don't have this person internally that's saying I want to do this, this is the best way to do it. That they're not really able to cultivate that from within. And I'm seeing that with our, our account management team where we are living and breathing this every day and able to assist them as a company where they do want to be moving forward.

0:11:45 - (Alane): And I thought that was so interesting lately that we're not necessarily coaching so much on work management systems, but on AI usage and what's the right tool for this AI prompt? What, what's the difference between a GPT and an AI agent? Like they need support on just understanding this technology to even know what's capable for within their company.

0:12:08 - (Micah): Yeah, almost to support, I would say what in the instances that I've seen that you're talking about, it's like to support the visionary to help them shape that vision.

0:12:17 - (Alane): Yeah, there, there's just so much there that, you know, you, a lot of us especially starting up, we're just trying to get our work done on what we're an expertise in. Right. And then as we grow our team, we're just trying to teach them on what we do. We're not thinking of it as an operational system a lot of time and we do fall into, well, this is how we've always done it. Well now with AI and AI agents that really starts to create a gap for your company. How are you going to compete? How are you going to stay cost effective?

0:12:55 - (Alane): Because you can't transfer knowledge that fast.

0:13:00 - (Micah): Yeah. And I think there's a piece of this too. When we talk about the solutions. It's one thing to be able to go to ChatGPT or Claude and successfully prompt and get Some results and copy and paste and do stuff with it. It's a whole nother skill set to operationalize this and say when X happens, we want to send that to a workflow. And that workflow is powered by automation and AI agents and multiple prompts and maybe a team of agents. And then it's going to have an output and the output's going to be predictable.

0:13:36 - (Micah): That's a whole system. Like, we started this business years ago, Alane, with helping companies build scalable systems, and lo and behold, we're still doing that same damn thing. But how we're doing it is completely different.

0:13:51 - (Alane): It has evolved. And I mean, honestly, just a side note, it's so much fun to go from where we.

0:13:57 - (Micah): A lot better.

0:13:58 - (Alane): Yeah. Well, the idea that we had like building systems and work management systems, building automated system from your CRM to your work management system, like all those automations, those are super fun. But then when we add the AI agents on top of it and you can just see it's not just automation or data being transferred between systems, but that thinking is happening from that AI agent and helping produce some of the work that a team member would have to do.

0:14:30 - (Alane): It's a lot of fun.

0:14:31 - (Micah): Yeah, I totally agree. And so, I mean, it is game changing. It is super, super useful, what can be done. But I just wanted to call out that we're talking a lot more about how do you build scalable systems, how do you operationalize these tools, how do you design this, how do you leverage your own company data, how do you know how to build a team of agents? That's the technical side that needs to support the visionaries. The visionaries need to be supported by leadership.

0:15:03 - (Micah): Mm. And I, you know, for the sake of making this podcast episode way too long for everybody, since we get a lot of feedback that everybody does love our nice, concise, short, short episodes, because everybody is busy learning about AI right now instead of, you know, while trying to get their own work done. I, you know, we had an episode a few ago that we recorded that was about what are things changing in the workplace and jobs and teams.

0:15:32 - (Micah): And I think it'd be really interesting just to talk about these types of roles that we're, that we're discussing. These are going to be new roles in businesses that are being created because of this. Just like when the web came out, right before we had web pages, there weren't people on teams going, well, I'll build the web page. They didn't exist. Same thing with social media. You and I, in our last Business. Alane, we were right at the forefront at the beginning of social media and what that meant for businesses.

0:16:03 - (Micah): And we saw all of these jobs being created, all of these roles being created, because all of a sudden we need a social media expert. In fact, that was one of our entire business model foundations was, hey, instead of hiring a social media expert for every single one of your locations, hire us and we'll manage all your locations centrally. Yeah, worked pretty well.

0:16:28 - (Alane): Yeah, I, I think, Maika, you make, you make a really good point because a lot of times people are so focused on the jobs that AI is going to take away that they don't talk about all the jobs that it's going to create. You know, we just transition jobs just help us transition from how we were doing things the old way and it's going to create new opportunities, the new way of doing business. So are we going to have to be more technical in our knowledge? I think so.

0:16:53 - (Alane): But it's going to be new creative jobs, just like you mentioned with the social media and just like with sites, we're going to have new positions available, just like with AI.

0:17:03 - (Micah): Yeah, yeah. And I mean there's, there's a lot of fluff and hype to sort through, just like everything else. Chat GPT5 just dropped. Super underwhelming from my point of view at least, I mean, for the amount of hype that that model had and then the results. And I mean you can go online and you can see, you know, a lot of people that are also underwhelmed with what it can do.

0:17:31 - (Alane): We're definitely at a stage in AI where we might be underwhelmed in the beginning, but things will evolve and we'll be wowed by something coming in the future. I still get wild with, with stuff even if.

0:17:44 - (Micah): Yeah, and I think my point with that is, is like, that hype can bring fear. But where we're at right now, and you and I don't know, like, we may listen to this six months from now and go, holy crap, were we wrong? Maybe we're wrong. But today, right now, as a business owner, this is what we're dealing with. We need to be looking at AI. We need to find the champions in our team. We need to help those, support those visionaries.

0:18:10 - (Micah): Because if you're not doing it, your competitors 100% are. And if you are not leading the charge or helping support those visionaries, find the implementers to get this stuff working in your business, your competitors 100% are. And you know, there's stats out there like something like 91 of small businesses are experimenting with. Or maybe it's 75% of small businesses are experimenting with AI technology and 91 of those are experiencing increase in revenue because of those experiments.

0:18:45 - (Micah): What that means is all these small businesses are focused on this and if you and your team aren't, those small businesses are going to run right past you.

0:18:55 - (Alane): Yeah, I'll say one more thing and then we can wrap this episode up is knowledge sharing between your team. I think one thing that I appreciate with our team is that because we're so much on the side of let's learn and stay on top of this is that we're constantly sharing use cases with each other. And how we used either AI or let's see, ChatGPT or Claude or Perplexity. We share how we did that and then we're that way. It's not working in a silo. Alane didn't just have this great idea and she's implementing it.

0:19:27 - (Alane): It's now I had this great idea and now every single one of my team members can now benefit from this knowledge. And then so when you're looking at it from your team, you need to be sharing. Have a Slack channel just dedicated to how you used, even if it is just chatgpt. What prompt did you use? How did you use it? And share it. Share it. Have a weekly meeting where you're just talking and sharing about cool ways that you used AI that week.

0:19:53 - (Alane): Because you don't want just one person being the rock star because you're going to be operating at your lowest common denominator of usage. So if your rest of your employees aren't using it, that's as fast as you're going to move because the rest of your team isn't doing it.

0:20:07 - (Micah): Yeah. Love it. Great way to end the episode.

0:20:10 - (Alane): Thanks for listening to this episode of Automate youe Agency. We hope you're inspired to take your business to the next level. Don't forget to subscribe on your favorite podcast platform and leave us a review. Your feedback helps us improve and reach more listeners. If you're looking for more resources, visit our website at BiggestGold AI for free content and tools for automating your business. Join us next week as we dive into more ways to automate and scale your business.

0:20:35 - (Alane): Bye for now.