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- [00:01]
Michael Stelzner
Are you feeling overwhelmed trying to keep up with all the AI changes? Trust me, I know how it feels. The marketers who are truly thriving today with AI have discovered something really important. They're not doing it alone. At the AI Business Society, we've created a community where smart, curious marketers like you share discoveries, troubleshoot their challenges, and celebrate breakthroughs together. Listen to what Marissa Shadwick had to say. Quote, I found my people. I love chatting about our experiences with AI and supporting each other on our journey towards the future. Unquote. Stop navigating the AI revolution by yourself. Join our community of innovators and let's grow together. Visit socialmediaexaminer.com AI to learn more.
- [00:56]
Rachel Woods
Welcome to the AI Explored podcast, helping you put AI to work. And now, here's your host, Michael Stelzner.
- [01:08]
Michael Stelzner
Hello, hello, hello. Thank you so much for joining me for the AI Explored podcast brought to you by Social Media Examiner. I'm your host, Michael Stelzer, and this is the podcast for marketers, creators and and entrepreneurs who want to know how to put AI to work. You know, it occurred to me that I don't really talk about much about what I'm working on AI wise on this podcast episode. So I plan to have a little segment at the beginning of each episode where I kind of talk about what I've been working on. Today I was working on our AI Business Society sales page. And for those of you that don't know, we launched six months ago, maybe nine months ago, our AI Business Society. And back then, marketers were in a different spot than they are today. And it came to my attention that we really needed to alter the message on our sales page. So I got some great feedback from our agency that we use for advertising, and they said, you know, I think your conversion rates could be higher. Maybe you need to revamp your message. And they came back and I had kind of known that in the last, like six to nine months that the world had changed a little bit. So I had known that it was time to revamp the message. So they gave me a very detailed outline of areas that I can improve. And I'm guessing they used AI to enhance it. And I loved everything that they said, so much so that I had created a Claude project and that has already been trained up on the AI Business Society. And I gave it the link to our sales page. And I said, hey, do me a favor and recraft a sales page based on all of this feedback. And in a matter of a minute, it took all their feedback it recrafted my headlines, my subheads, the angles of the message, and in about three hours, I had crafted an entirely new sales page that we are split testing up against the original sales page to kind of see if it works. I can assure you that never would have been possible before if I did not have a great tool that powers the content that I'm creating behind the scenes. So check it out if you get a chance. AI Business Society all right, today I've got a great show for you. Today I'm going to be joined by Rachel Woods. She is a returning guest to the podcast and we're going to talk about how to become an AI first company and what we mean by that. We will explain a little bit later in the interview. But if you know that you need better systems inside your company so that you can basically get the benefits that you believe AI could bring to your business, then you are absolutely going to love today's interview with Rachel Woods. By the way, if you are new to this show, follow us on whatever app you're listening to because we've got some great content. Great. Coming your way. Let's now transition over to this week's interview with Rachel woods.
- [04:13]
Rachel Woods
Helping you simplify your AI journey. Here is this week's expert guide.
- [04:19]
Michael Stelzner
Today, I'm very excited to be joined by Rachel Woods. If you don't know who Rachel is, you've got to know Rachel. She is an AI expert and founder of Divi up, an agency that helps agencies develop AI operations procedures. She's also the founder of the AI Exchange, a membership for AIOps professionals and consultants. Her courses include Prompting for AI Operations and Intro to AI Operations. Rachel, welcome back to the show. How you doing?
- [04:49]
Rachel Woods
I'm doing great. So excited to be back here. It's always so fun hanging out talking about this stuff and feels like we just get to turn on a mic this time.
- [04:56]
Michael Stelzner
I know it's super cool and it was great seeing you at Social Media Marketing World. Just a little time back Today, Rachel and I are going to explore how to become an AI first company with a proven methodology. There's a lot of this phrase going around right Now, Rachel, this A.I. first thing, we're going to get into this a little bit. But first, why do businesses need better AI systems? Because I know based on your bio and based what I know about you, you are a systems person to your core. So for the people that are listening right now, regardless of whether they're an entrepreneur or a marketer, what is it about AI systems that's so Important for a business. Said another way, what's the upside if they pay close attention and get it right to what we're about to talk about?
- [05:43]
Rachel Woods
Yeah, great question. I love that you call me a systems person. The other side of what I often say is, like, I'm a nerd. I promise this won't get too nerdy, but I always like to acknowledge that, like, I'm a nerd and been a nerd about AI for like almost a decade, and that just recently became cool. So that's kind of where a lot of my lens comes from, but on the system side. So here's what I love about where we're at with AI right now is most people have tried ChatGPT. A lot of teams are using ChatGPT or AI pretty regularly, on a weekly basis, if not a daily basis. So everybody kind of like gets the plot. But what we like to especially expose people to is that they're not seeing the whole picture, the whole story. If you're using ChatGPT kind of like ad hoc on a daily basis, you know, tinkering with it, random acts of AI, any of that stuff, the research shows you're probably about like 30% more productive than you are without it, which is huge. Like, don't get me wrong. But that's not the full potential of what AI can unlock. AI can really unlock not just 30%, but like 300%, 3,000%, orders of magnitude more productivity and impact and everything. And systems are the bridge to get there. You can get your mind around and start getting in the habit of systematizing your AI usage. You define something, AI goes off and does it, and you could just be truly unstoppable. So that's what gets me really excited about all of the system stuff.
- [07:14]
Michael Stelzner
I love it and I agree with you. And I bet you so many people that listen to this show are kind of like me. They have set up systems that are kind of working but not perfect. And in the back of their mind they're like, oh, I knew I need to improve that. But not today. Hopefully people will walk out of this interview with at least some sort of framework at which they can improve their AI systems. Now, a little tangent. This AI first thing that's going around, why don't we just describe what, in your eyes, it means to be an AI First Business or AI First Company or an AI First Agency? Because there's a lot of talk happening in the AI world and not everybody really understands what that means. Do you mind just taking a swing at that?
- [07:56]
Rachel Woods
So the way that we define AI first is pretty simple. It's that you think about going to or using AI first when you're doing something. Now it doesn't mean that you're going to have some fancy system right off the bat, but at least in most tasks you're doing on a day to day basis, you're leaning into how could I get AI to either do this for me, help me with it, or how can I set up something that AIs be able to do in the future? The piece of why this is so important, which I, I think like everyone thinks they need to be AI first just because like that's the, the hot topic these days. But with a lot of our work we get exposed to what the tangible impact of these concepts or not having them really means when it comes to your AI adoption. AI first in particular, if you don't have the mindset yourself or your team doesn't have that mindset, you, you're not going to be able to get into really using systems or really scaling with AI because you're going to be trying to create a process that AI does, teaching people that process, and they're not even necessarily comfortable with AI in the first place. So getting to be AI first is super important and usually the first step before getting into a lot of the system stuff that we'll talk about.
- [09:12]
Michael Stelzner
So perfect. So let's talk about this mindset. When we were prepping for this, we talked about having an AI first mindset for both teams and people. What does that actually mean beyond just thinking to go to AI first?
- [09:26]
Rachel Woods
So a lot of it again is thinking about how AI can be integrated into whatever those work processes are. There's simple things like starting a prompt library and having all of the different ways you're using AI stored somewhere. Even things like sharing different AI use cases really regularly in your team. But again, I think like it sounds like it needs to be this really complicated thing. The simple thing really is just whenever you're doing any task, think about how you can use AI first before you go kind of do it manually, ask someone else on the team how to do it, any of those things. Again, like one of the things we've learned is if you don't have that comfort and familiarity, then getting to the place where you're using any system or setting up anything more complex, you're just going to run into a lot of friction because you haven't kind of done that, that first step.
- [10:19]
Michael Stelzner
Okay, so we're into your methodology now and we're Adopting an AI first mindset, which pretty much means before we start any process or procedure, we are thinking about AI and how it could aid, assist or enhance. Is that correct? Am I hearing that properly?
- [10:40]
Rachel Woods
Yeah, exactly.
- [10:41]
Michael Stelzner
And there was an example that we were chatting about about your very first AI agency client. Do you remember that example?
- [10:48]
Rachel Woods
Yeah. So it's actually a great example of what I'm talking about around if your team's not on board or you're not thinking about AI this way, you're going to run into a lot of friction if you try to jump into anything more complex. So our very first client, they had this really stellar onboarding process for any new client that they bring into their business. And what we did was we were like, cool, give us the process for what you do and we'll teach that to AI so AI can do that for you. This became an AI process that was, I mean, upwards of near 100 steps that AI was doing for them. The AI would go off and run that for an hour or two. It was just amazing process. It saved so much time. True game changer. But the only people that understood how to use it were the people that had been doing AI first work themselves already. And that was kind of like our main point of contact. People we were building this out with within their team. They had such a hard time getting the rest of the company to be comfortable with this, understand how to use it and kind of engage with it. And so what I ended up doing with them is like backtracking and say, hey, let's put that super powerful but complex system aside. Let's just get the team comfortable, like writing prompts, thinking about going to AI first for stuff. And once we did that, that's when then the unlock of people being like, okay, now I actually understand what this bigger AI process for onboarding is going to do for us. So really it's that prereq to get people comfortable with it and bought in before you can go after the stuff that's going to make a huge impact.
- [12:19]
Michael Stelzner
Okay, so I love this story on multiple dimensions because what I'm hearing you say is, let's say you have a champion inside of a business who loves AI and develops something really sophisticated, but they're the only one using it that's not going to really lead to an AI first company. It might lead to an AI first department, but an AI first person, but not a company. And what I heard you say is there was some training that was necessary. So for those that are listening that maybe they're the one inside their business that has a pretty good grasp on AI. Do you have any tips on how to train other people to get them kind of on board so they also have an AI first mindset?
- [13:02]
Rachel Woods
Yeah, I mean, I guess I kind of hate to sound like a broken record, but like you have to get your team to think about going to AI first for stuff. Usually if people don't necessarily make that leap themselves, walking through tons of examples like, hey, what was the project that we just did? Cool, let's spend 30 minutes looking at how you completed that project and go through together and do it again in chatgpt or write prompts for it. Just giving people some again, like real world use cases and examples of what they're already doing. They'll start to see those patterns in that work. There's also things, things like we recommend people habit stack a lot, which means like find something that you're already doing, like we're onboarding a client and figure out where you can take a prompt or some sort of AI task and actually put that in the process for the whole team to use. Make it super easy. Hey, copy and paste this prompt into chatgpt with these things. But even just finding places to kind of insert AI in the existing workflow for people can start to give folks ideas. The main thing is, if someone doesn't quite see work this way yet, just think of it like a snowball, like you got to get enough momentum for them and that should be your main focus because then they're eventually going to get to the place where they're starting to see those things on their own. And that's really what you want as the foundation before you move into expecting that the whole team or the whole company is going to go after really complex stuff.
- [14:29]
Michael Stelzner
Okay, so what we've talked about so far is first of all, you need to kind of set the foundation inside the business for this AI first concept, right? You might have a couple individuals who are heavy into AI use and they've already got the AI first thing down. But there's a good chance not everyone is. So train people, give them some small examples of things that they can improve, help them to see the light at the end of the tunnel. Maybe I'll add my thoughts, even set expectations that everybody use AI to improve their work on a regular basis and share insights back and forth. And don't just go down the path of creating a super complicated thing and expect everyone to adopt it. Right? Instead, it's really all about getting everyone on board to this new way of work. So once we've set all this kind of foundational stuff in place, what comes next?
- [15:18]
Rachel Woods
So once you've done that, you get to start thinking about the higher impact processes and back to what we started with, kind of the systems to start to set up in your business that are really going to make a very significant business impact. And this is one of the things that we see kind of get muddled when you start to think about AI use cases. Because naturally you're going to want to use AI for everything eventually. But if you try to just go boil the ocean and build every prompt, every workflow, everything yourself, you're going to have a never ending to do list. And there's a good chance that you don't work on this stuff. That's really the highest impact or highest leverage for your business. And so something that we spend a lot of time with, with our clients is helping them kind of map out use cases and develop a better strategy for what to go after and in what way. The things that we look for are, is this a use case that truly has a unique way that you need it done? You can't just go use an AI tool off the shelf, or you can't just put a really basic prompt into ChatGPT. If there's a unique method, unique process, unique expertise in that process, that usually is a signal that that's a really high leverage thing to go after. Because once you teach AI to do it, it can do something that's really unique to you and has a lot of leverage that normally you'd maybe need to train a team for. On the other side, there are other use cases that are pretty commoditized, if you will. You should still be looking to use AI for those things, but the process should look more like keeping track of things on Twitter or reading newsletter lists to see new tools come out that say they do that thing and then being a active tester and evaluate if that tool will work for your use case or not. Because if you try to again, just go after building everything, like you're never going to get through the whole list. A good example on the commoditized side is meeting scheduling is probably one of the things that early in the whole AI boom, everyone was like, oh, I need to build an assistant that's going to schedule my meetings for me. And thinking about needing to define that and build that themselves. There's already in the market now really, really great AI meeting scheduling products. Other people build that. You should just be plugging into your workflow I'm actually curious, have you used any of those yet? I have a new favorite. If I'm going to shout out, I.
- [17:42]
Michael Stelzner
Have an incredible as, you know, executive assistant, so I could never imagine not using her to help me with all that. But I'd love to hear the tool that you're using because I'm sure everybody would love to hear that.
- [17:54]
Rachel Woods
Yeah, so I use Howie. AI is a new.
- [17:58]
Michael Stelzner
How do you spell it?
- [17:59]
Rachel Woods
H, O, W, I, E. Yeah, Howie AI.
- [18:03]
Michael Stelzner
Okay, cool. What does it tap into your schedule.
- [18:05]
Rachel Woods
Or something like that so you can CC it in? And the way that we do it is I use it for certain meeting scheduling and we have kind of our normal process for others. But yeah, I mean, it's a great example where you should think about the use cases where you need, you know, you want to use AI in and then prioritize it. If it's something that you can follow or use somebody else's tool or process, then just go find that tool that does that.
- [18:29]
Michael Stelzner
I love it. And I want to come back and summarize what you just talked about, but I remember when we were prepping, we talked about something called an AI edge vision. I would love you to describe what the heck that is, because I feel like that might be something we put in place before we even come up with the stuff we've just been talking about.
- [18:45]
Rachel Woods
So an AI edge is another concept that we spend a lot of time with our clients on. And basically that's when you're thinking about AI. What are the things that you're going to do that not only save time, but help you build a competitive edge in the market. And really, we frame it a lot around, like, AI shouldn't just be something you're trying to, like, catch up on all the time. You should feel like you're winning because you're using AI. And so a good example of this, like in our world is we ask our clients all the time, hey, you deliver a certain, let's say our creative agency, you deliver certain services right now, maybe around branding, maybe around content, what would you be either adding to your existing services or launching as new services? If you had unlimited time or really wanted to win in the market or really wanted to build an edge, like, what are those things on that list? And how can AI be an enabler of going after that stuff? Related to what I was talking about around finding things that you have unique expertise in. When you combine things that you are really good at and things that will give you an edge in the market, all of A sudden now you have AI powered processes or systems that can really scale and help you build. I mean like a better word, an extremely hard to compete with competitive edge that other people would need to go through doing the same stuff with AI and your expertise to get even close to competing with.
- [20:14]
Michael Stelzner
Okay, people that were driving are like, I got to pull over and listen to that again. So folks, this is like a really important thing. Rachel just said if you could imagine some unique service or feature that your business does not currently have today that would give you such a competitive edge that would differentiate you in the marketplace and you had unlimited time, which you don't, but let's say you do to build such a thing, what would that make possible? That's the question really you're asking, Right? And then the question underneath that is, and can AI enable that? Because if that's true, then all of a sudden there's a lot of people, especially founders of businesses like myself, that would love to, to add new lines of business, but they don't have time, they don't have resources, they don't have access to capital, they lack access to the right people. But what you're saying is this could be possible with the assistance of AI. So just having that ability to dream a little bit is kind of a really good first thing to do or maybe an additional thing to do in addition to identifying the unique systems. Did I hear that correctly?
- [21:35]
Rachel Woods
Totally. And the thing that I would add is a good exercise is sitting down at an off site or even having, you know, a longer meeting with your team and go into ChatGPT and think about what are the things that, you know, either we did uniquely for some of the clients that were paying us the most, or we wish we could have done for that one client, but we didn't have time. And just see if you can get AI to have a version of that or start with those things. Because in our experience there's a lot of these hidden unlocks in a lot of businesses and if you're not finding them, then someone else in your market is going to. So trying to figure out what those are. Because AI, once you set it up, it could be doing that every single time without you needing to spend that time.
- [22:23]
Michael Stelzner
Well, if you haven't been tracking, there have been some major AI updates over the last month and the changes just keep coming. I know this feels overwhelming, but what if I told you you can actually thrive in this rapidly evolving AI frontier? The marketers succeeding aren't the ones with the most AI tools. They're the ones with the right guidance. That's exactly what you'll find inside the AI Business Society. Our team cuts through all the noise so you can focus on what actually moves the needle in your marketing. As member Shannon Caldwell told us, quote, these trainings are filling the gap between knowing what AI can do and knowing how to do it. Are you ready to thrive with AI? Join me inside the AI Business Society by visiting socialmediaexaminer.com AI okay, so we're in what I'm going to call the strategy part of the conversation here, where we're starting with what we've just been talking about for the next last few minutes, which is what could be your unique AI edge, what could be possible that could differentiate you in the marketplace? Prior to that, we were talking about what are the systems that already exist inside your business or that you wish existed inside your business that could have the biggest leverage. Right. Or the biggest impact on the business? And you said ideally you find the system that has the most leverage and you consider building something like that. Alternatively, you could also focus on what are the repeatable tasks that are very simple. You call them commoditized operational procedures. Maybe like, for example, meeting scheduling that you could just go and buy an off the shelf SaaS product. And having that kind of brainstorming session will help you kind of separate the big opportunities from the light opportunities. Am I hearing that correctly? I don't know. I just added a little bit of my thoughts in there as we went.
- [24:28]
Rachel Woods
No, it's great. And back to what we talked about at the beginning. All of this is your AI operating system. I think it's natural to think it's just going to be just like, oh, we need to one day become AI first. And it's going to be these five things across the business. But in reality, it's like you need to think about all the pieces of your operations and start to put it into some of these frameworks that we're discussing. And once you start structuring stuff, then you'll see, wow, there's a lot of opportunity, a lot of things to do. We need to prioritize. And that's where some of what we discussed so far can really help. The other thing that can really help is the people, which is probably my favorite thing to talk about. And this is like the most.
- [25:05]
Michael Stelzner
That was my next question, actually. So go for it. Okay.
- [25:08]
Rachel Woods
Okay. So this is like the most slept on or biggest secret I feel like in this industry right now, of the businesses that are making a ton of progress with AI ifying their operations, if you will, is that they've figured out how to have the right people driving the ship. I'm not talking about leading the entire company, but you need to have really the right people leading the AI operations function or all the stuff we're discussing. Because once you get these roles in place, what we've seen is it removes a ton of friction and helps you go really fast. I like to say the faster we go, the more use cases we can get in and the more ROI we're going to have. So the three roles, and I want you to hear, when I say roles, I'm not talking like three headcount, I'm talking three hats that you need to either find to put on people in your current organization or, you know, find how to have outside help for. But the three roles are you need someone who's going to be kind of the AI visionary or AI leadership. That's the person that leads a lot of the strategy conversations, makes sure you're working on the highest impact stuff, and keeps the business goals and direction in mind. But what most people kind of get wrong is that person who's really high up in the organization and really excited about AI. They also put the hat on them of the person who's responsible for driving the progress. And what we found is you actually need a different role or a different hat, which we call internally and with our clients, the AI operator. It's our term for it. But you can think of it as kind of the AI operations project manager, or the person who's really responsible for driving the AI ification of the business processes. That role, when you have that in place and you're supporting that person, making sure they have the time to do that stuff, that's probably the biggest differentiator we see between even like our clients that are going really fast and then the ones that are still kind of trying to figure out how to move forward. And we always are really encouraging them to set that that role up. But those are the two main hats. The third hat is the implementation. So this is another piece that oftentimes companies kind of assume it needs to be one jack of all trades that's doing this. It's totally okay if you have a different person who's the AI leadership, different person who's the AI operator, and then different person who's actually implementing or engineering or building. Because all three of those roles together. When you have that, that is an extremely powerful AI operations team that essentially can be deployed across like any use case. Any problem, any part of the business, and you'll be able to see progress on getting these like, systems and everything set up really effectively when you do that.
- [27:52]
Michael Stelzner
Okay, so what I heard you say is there's three roles. There's the AI visionary slash leader, which in some cases it's going to be the founder, CEO of the company, but in other cases it might be someone who is passionate about this role, I would imagine. Maybe we should talk about what kind of ideal person each of these roles might look like. Then you've got the AI operator slash project manager. This is the person that's going to be doing the, for lack of better words, directing to make sure progress is being made. And then you have the person doing the actual implementation. You call this person engineer, but they don't need to be be technically an engineer. They just need to be able to use the tools that are necessary to pull it off. So in your experience, especially working with agencies, because I know that's predominantly who you work with, who is the best visionary versus operator versus implementer.
- [28:39]
Rachel Woods
So the visionary oftentimes is the owner or founder or we also see the COO is a pretty common person to be in this hat. The main thing is you want to make sure this person has kind of that executive sponsorship level of authority and then the AI operator. Our favorite thing is to find a project manager or a process oriented team lead who's excited about AI.
- [29:07]
Michael Stelzner
Talk about this because like people that are visionary tend not to be very operationally minded and speak to the visionaries that are listening right now why this is so critical.
- [29:15]
Rachel Woods
Yeah, so imagine you're the AI visionary here. You said, great, we're going to go after using AI for. I'll use an example from before our onboarding process for new clients. Great. What needs to happen next? You probably need to make a process diagram or map out or write an SOP or some version of articulating exactly what that current process is. And not a 10 bullet point list of like, first we do this, then we do this, then we do this. You need to get details. Details enough that those can turn into prompts or instructions for AI to follow.
- [29:52]
Michael Stelzner
Love that.
- [29:52]
Rachel Woods
And usually that process becomes something that you might need to coordinate across multiple people across the team, because you might have five different ways of doing it. And so you need to codify all of that into one. All that stuff I just described, that's like step one. And if you're anything like the visionaries I know that's a lot of steps and a lot of work. And a lot of things to add to your plate of something that you're probably don't get energy from. But I guarantee you there are people on your team who, if given the right resources and training, would absolutely crush and be really great at doing all of that. And so it's just one example where like you can really have this yin yang, if you will, of like someone who's saying, hey, this is what we're going after. Here's all the energy and commitment that the company's doing this and then somebody who makes it happen.
- [30:40]
Michael Stelzner
Okay, what about the implementer?
- [30:41]
Rachel Woods
So this role can sometimes be the same as the AI operator if you're going after pretty like simple AI setups. So, you know, it can still be a system even if it just looks like a series of prompts that you run each time you do that process. If that's the case, then you probably don't need a separate implementation person. But if you want to get into automating things, so doing AI automation or using AI agents or any of the more complex AI solutions out there, or even assessing tools.
- [31:14]
Michael Stelzner
Right. Wouldn't this person potentially. Right. They need to have a somewhat of a technical competency, I would imagine. Right?
- [31:20]
Rachel Woods
Yeah. And also the time to stay up to date with how quickly everything's changing. And a lot of tinkering in R and D is what we call it. Because if you're committed to having systems that really work and keep you on that competitive edge, having somebody who's dedicated to the building and making it work and testing it and improving it when there's feedback and fixing it when it breaks and upgrading it, when you say that, it just becomes its own really role in itself and it's totally separate from that AI operator who again, really is that bridge between what's the business process and how are we going to break that down and define it in a way that AI could do.
- [31:59]
Michael Stelzner
When we were prepping, you talked about this Influencer Marketing Agency example that you were going to share. Can you share that?
- [32:05]
Rachel Woods
Yeah. So we have so many examples like this because again with our clients, this is one of the things we encourage them to set up internally the most. We really act as kind of that guide. And then also we're doing all the implementation. So I could give you dozens of these examples, but I'll just give you one which is so one of our clients, Influencer Marketing Agency. They're about a hundred people, not a small tiny organization. And we're working on AI operation systems for many parts of their business. But One specific part is vetting influencers.
- [32:39]
Michael Stelzner
Okay.
- [32:40]
Rachel Woods
So deciding for any campaign they want to do, out of potentially thousands of possible influencers to work with, who are the five that are the best fit this process?
- [32:53]
Michael Stelzner
Ah, for a prospective client or for something along those lines. Right. Is that the idea? Okay, yeah. Not just like building a network, but specifically finding the right influencers to do a task. And I would imagine that used to be a ridiculously manual procedure. Am I right or am I wrong?
- [33:06]
Rachel Woods
Oh yeah. And then they actually couldn't go through all the potential influencers they wanted to bet because there would just not be enough time.
- [33:13]
Michael Stelzner
What did they do? Yeah, tell us what happened.
- [33:15]
Rachel Woods
What we did with them is basically they had a kind of cross functional project manager, operations person already. This person wasn't doing anything official with AI yet, but was definitely excited and interested. What we set up with them was great. We're going to train that person to become the AI operator. They're going to work with the influencer vetting team who's kind of the subject matter experts on this process. Right. They're the ones doing the process. And that AI operator is essentially going to help codify or standardize what's getting done and then break that down into steps that AI can do and we'll work with them to implement. And this has worked extremely well because the benefit here is like we're not pulling anybody out of that team or process. We're not taking away from that team's time. There's also not a process oriented person on that team currently. So if we were working with that team or expecting that team directly to create this process, there would have been, I think, a lot more friction. But then this dedicated kind of AI operator, they're also learning the skill to where now the next process that we're looking at, they're going to be able to go and work with that team and they're already going to know how all of this stuff works. And so yeah, it's just, it makes things move so much faster, able to get so much more done. And like I said, the faster you go, the more things you do, the bigger roi.
- [34:33]
Michael Stelzner
I like a couple things you said there, you said in this particular case with this influencer marketing agency, there are some experts inside this agency who have a very deep bench of knowledge and, and the operator influencer, I mean, yeah, the operator, AI operator worked with them not as a threat to take work away from them, but as potentially an opportunity to allow them to be able to handle more volume. Right. As a company Totally. Or be able to do more business as a company because they could reduce the amount of time that it took for them to find these people, which would be one of those unique competitive advantages you were talking about, right?
- [35:12]
Rachel Woods
Yeah.
- [35:12]
Michael Stelzner
So now they can position their agency as, not only do we have a great network, we can move faster when you need to move faster. So if a prospect comes in and they've only got a week until they need to launch their campaign or something like that, these guys can come in and take the business where in the past, they'd have to pass on the business probably, right?
- [35:30]
Rachel Woods
Totally. And that AI operator, their conversation with the influencer vetting team was a lot around, what do you guys wish you had time to do? And one of the things, again, was they weren't able to vet as many possible influencers as they wanted because they just didn't have enough time to go through them. So thinking is this enabling function, you're going to get so much more done if you can codify or like have this role inside your company.
- [35:56]
Michael Stelzner
Okay, so is there anything else on the people side of this discussion before we move on to how we actually execute on this stuff? If not, we can move on to the how do we actually execute on this stuff?
- [36:08]
Rachel Woods
Yeah, I mean, I'd love to talk about execution, because what is this AI operator doing? So we have standardized the process of taking business processes and teaching them to AI, because that's what we do on repeat, all day, every day. We call it the craft cycle. It's five steps, but the AI operator's job is to run this craft cycle and that craft cycle. The first step is getting a clear picture. So like, I already kind of mentioned mapping out what's the current process, codifying it into SOPs, or getting all the instructions, like really getting a detail of what's going on in the business. Then R stands for realistic design. So this is usually where the AI operator might work a little bit with the AI implementer to figure out, okay, here are all the things we wish AI could do or want AI to do. What's realistic and what's not too complicated, and what would be a good first version to go after. And then you look at that realistic design and you kind of decide that, cool, this is something worth going after real quick.
- [37:07]
Michael Stelzner
Before we go through all of them, I want to back up a little bit. Okay, so this is an acronym crafty, and we're starting with the C in craft, which is clear picture. So in this case, when we're mapping out our current processes and developing SOPs. How big of a document are we typically talking about here? And what are kind of the basic elements that would go into providing this clear picture?
- [37:30]
Rachel Woods
I mean, you can do it a lot of different ways. The way that we kind of capture from a team is either through a written questionnaire. Okay, so kind of asking, what are the inputs, what's the steps, what are the outputs or deliverables? Can you share links to stuff? Do you guys have templates? There's kind of a bunch of discovery questions, if you will, all around process discovery. So if anyone listening to this wants to learn more about process mapping, process discovery, that's been around for a while, there's great resources on YouTube. But once you have that understanding of what the process is. This is where I think we talked about this last time I was on the podcast around Playbooks. This is where if you take your current process and you convert it into a really structured, here are the inputs of the things I want to give the AI, here are the steps I want AI to do, and then here are the outputs. We call that a playbook. That becomes what the design is. So that, like, second phase. So clear picture, understand what we're currently doing, and then realistic design. Here's what that solution looks like or what we're going to try to set up.
- [38:34]
Michael Stelzner
And folks, if you want to listen to the episode that Rachel's referring to, it was episode 17 of this show published on September 3rd. You can go to socialmediaexaminer.com a17 to learn about more about her playbook methodology. Okay, so this is really kind of a big undertaking, developing this clear picture. Because from what I recall about these playbooks is they can be many, many pages long. Is that fair to say?
- [38:58]
Rachel Woods
Yeah, I mean, it's a process for sure. I will say you can simplify them. Like, you can start with something pretty simple. We recommend going through the craft phases, potentially like multiple times for a use case. Start with the most simple thing and add more complexity over time. But yeah, going back to like, you're going to have a lot better outcomes. If you have a dedicated person doing this, it's because it takes time to do it. Yeah.
- [39:20]
Michael Stelzner
Okay, so C it in craft is clear picture. The R is realistic design for AI. So how do we know what is good enough for the first version? Do you have any tips?
- [39:29]
Rachel Woods
So it's kind of the science and art combination.
- [39:32]
Michael Stelzner
Right.
- [39:33]
Rachel Woods
Usually what you want is an AI thing that you can set up in like a week.
- [39:40]
Michael Stelzner
Okay.
- [39:40]
Rachel Woods
If you're going after something that feels like it's going to be a multiple month long process. You should scope that down into a first version because you'll never know what kind of feedback you're going to get once it's set up. And it's a lot better to learn what kind of feedback in a week versus like multiple months.
- [39:57]
Michael Stelzner
Got it. So said another way, try not to go for something humongous. If it is something big, break it into tiny parts and start figuring out if you can realistically design this with AI. And most people have no idea what the limitations of AI are. So do you have any tips on the kind of low hanging opportunities that might be easy to do with AI? I'm guessing it has. If it's anything to do with processing of information, that that would be an obvious low hanging kind of task. Am I right?
- [40:26]
Rachel Woods
I guess. Are you asking about like types of processes that you could put?
- [40:29]
Michael Stelzner
Yeah, because like some stuff might be harder to pull off, like art, you know what I mean? And that kind of stuff.
- [40:34]
Rachel Woods
Totally. So I'd say any like process where you're taking information in and converting it into other types of information. That sounds super nerdy, but like a content process, maybe where you're taking a transcript from a talk and you want to convert that into multiple social media posts, that'd be a great thing to run as like a first craft process. For example.
- [40:54]
Michael Stelzner
Okay, so we're in the craft acronym. C is clear picture. R is realistic. A design. What's next?
- [41:01]
Rachel Woods
So A stands for AI and automate. And notice we're on the third letter and we had just got to the building part. Okay, so this is something else that people naturally. You want to like jump into making a demo up front or like see if AI can do stuff. It's good to experiment, but if you wait until this third step to build it, you're going to be so much faster in building what you actually need. Because you've done the planning work up front. This step is usually done by that implementer and you can have it be as simple as aifying by writing out all the prompts that you want in that process or plugging those prompts into automations or setting up agents. Like there's a whole spectrum here. But the main thing is you want to have this be like a dedicated stage where it's getting AI fied.
- [41:47]
Michael Stelzner
Yeah. And we have had extensive people on the show that talk just about this part of the discussion. And you can all listen to any one of the episodes we've done on AI tasks and Automation tasks. What's the AFF in craft?
- [42:01]
Rachel Woods
That stands for feedback. And it's super important to have a dedicated stage on this as well. Usually what we recommend is having a smaller set of people that are tasked with giving a really high volume of feedback really quickly. So not just setting it live, putting this, the AI out there in its first version. You want to get people to look at the quality of the work that the AI is doing and really flag anything that's going to make it. So this isn't valuable because then it's really easy if you find something in this feedback phase to just kind of go into that AIFI phase again. Or the person who just implemented everything is still pretty like fresh in their mind of what they set up. So it'll just be a lot faster to knock out any of that feedback really quickly.
- [42:48]
Michael Stelzner
Any tips on the kind of feedback you want to ask for at this phase?
- [42:52]
Rachel Woods
So we like to ask for substance feedback. So is there anything that the AI is creating in its output or doing that feels like it's totally missing the boat? Like it's not. I'll give a good example. Like, if you're doing a content process and all of the post topics are terrible, it's like a substance issue. Usually that's a sign that you need to spend more time on the instructions and actually like breaking down what you're trying to get the AI to do, how you're. You're teaching it. The other type of feedback you're looking for is like style feedback. So other things around formatting that if you made just some small tweaks, it would make it a lot more usable for the team. These are honestly so much easier to fix but equally important than the substance stuff because you never know if you're doing, let's say an AI process that creates like a sales brief for your team or they get a overview of every single lead before they get on a call. If you make this whole report and then nobody's using it, but if you ask them why they're not using, they're like, oh, I have to skim the whole thing just to find how big the company is. Great, let's just put the company at the top. Then you know, like those simple style things that really helps it be super usable from the team.
- [44:11]
Michael Stelzner
Love this. I think this is really, really. I love how you said there's really two kinds of feedback. Number one is the substance of the output. Feel off or feel like it's not in the tone or voice of the brand or whatever. And then there's this whole is it usable from a user experience perspective. Right. So maybe is it just one big honking paragraph? You know, maybe you just need to break it into individual sentences with bullets and bold. And all these kind of things are possible with AI so that the human on the other end of the thing is going to find it useful. Right. Because the output is virtually the same. It's just a matter of reorganizing like you're saying, or highlighting certain key things that will all of a sudden bring more value to a human who's utilizing this. Correct?
- [44:57]
Rachel Woods
Yeah, exactly.
- [44:58]
Michael Stelzner
Okay, and then the last letter is T. What's the T in craft?
- [45:02]
Rachel Woods
So that stands for team rollout. And again, important to have a dedicated phase on this before you jump in, start the next craft cycle. That's like the number one thing we see is people like, okay, looks good, let's set it live and then let's start on the next one. If you don't at least pause and have some intentional steps around team rollout, then there's a chance you're not going to realize the full ROI of what you've set up. Some things on the team rollout that are really important are one, thinking about training. So it's everyone on the team is going to end up using this, know how to use it, know how to give feedback, know what their responsibility is in that process. If you do a live training, record this and link it next to the AI process and whatever it's used. Because this is a really mission critical part of getting people to use whatever you've set up. The other thing that's really helpful in this team rollout stage is making sure it's integrated into people's workflows. And that can just mean as simple as if you have a process in your task management tool, you know, your asana or ClickUp or wherever, making sure that there's a link to this AI process wherever it needs to be run. Actually I said earlier around like habit stacking, if it's really convenient and natural for people to use it, they're going to use it a lot more. The other piece is sometimes you need to have an actual integration. So this is kind of where you get a little bit more into automations of even starting this process. So let's say you want something to be run from HubSpot, like when a new deal closes in HubSpot or a new sale, you could automate the start of this AI process and we usually recommend doing that stuff in this team rollout. Phase, because that's really. And that last mile to get it really working with everybody.
- [46:48]
Michael Stelzner
Rachel Woods, Wow. Is what I have to say. Capital wow. Thank you so much for sharing your insights with us today. If people want to connect with you on the socials, where do you want to send them? And if they want to work with your business also, where should they go?
- [47:04]
Rachel Woods
So I'm on every platform. If you just search Rachel Woods AI usually come up. I'm the AI operations girl and I'll say I'm probably Most active on LinkedIn, so if you have any questions, feel free to reach out to me there. In terms of working with us, I'd love to hear from anybody who's interested in using these methodologies and concepts inside their business. We have ways we can plug you into the AI Exchange our community courses, and then we also have ways we can support you with our agency. So reach out and I'd love to figure out what's the best fit for you.
- [47:33]
Michael Stelzner
Where do they go to reach out?
- [47:35]
Rachel Woods
You can message me on LinkedIn or if you want to email me. I'll make sure that my email's in the show notes.
- [47:41]
Michael Stelzner
Okay. Rachel, thank you so much for sharing your insights with us today.
- [47:44]
Rachel Woods
Awesome. Thanks, Mike.
- [47:45]
Michael Stelzner
Hey, if you missed anything, we took all the notes for you over@socialmediaexaminer.com a56 and be sure to follow this show on your favorite podcast app. And if you've been a longtime listener, we would love a review on whatever app you're listening to. And would you let your friends know about this this show? Also check out our other shows, the Social Media Marketing Podcast and the Social Media Marketing Talk show. This brings us to the end of the AI Explored podcast. I'm your host, Michael Stelzner. I'll be back with you next week. I hope you make the best out of your day and may AI help you become more successful.
- [48:20]
Rachel Woods
The AI Explored Podcast is a production of Social Media Examiner.
- [48:28]
Michael Stelzner
Just a quick reminder before you go. If you're ready to become indispensable in the age of AI, the AI Business Society is your solution. Join now and secure your discounted membership by visiting social mediaexaminer.com AI I can't wait to see you inside the AI Business Society.