Episode 43: Heather Terry on Why You Should Start With Your KPIs Before Buying Another AI Tool

Have you purchased a bunch of AI tools, you're not getting the value that you want, and you've overwhelmed your people in the process? We're going to talk about how not to do that. Stay tuned. AI is everywhere right now, but what I see in small businesses is not a lack of interest. It's really a lack of clarity. Where do we start? What actually matters? What are the right tools? How do we use it without creating more chaos for our people? So today I'm joined with Heather Terry, who is the CEO and Chief Content Architect of Curious AI. And what I appreciate is Heather's approach to how we take AI learning and AI adoption. So we're going to talk about that today. Heather, thank you for being on the show today.

Thank you for having me. I'm so excited.

So before we get into the strategy side of AI, I'd love to start here, your background is not what most people would expect in this space. It's super fun. You started in education and writing and made your way into AI strategy. So can you kind of walk us through that journey of like, how does, how does someone in British literature become an AI expert?

Yeah, my, one of my favorite showstoppers at networking events is that in 2019, I was still teaching Shakespeare. And now here I am today leading Curious AI. And it's quite the interesting pathway to get here. It's not what you would expect. I picked up, you know, the, the writing composition part of the process of teaching. I bring that to the AI strategy and how we can both improve not just the writing process of prompts for the people using AI, but looking at AI as a writer itself and how to improve the AI's writing process, and then putting those together.

Wow. So let's start with something I hear all the time from business owners, and it is they're afraid that AI is going to make themselves and their brand sound generic. So What's the biggest mistake that you see that actually causes that?

Uh, there's two.

Okay.

Uh, one, they don't do any voice training with the AI, and two, they don't read and edit what the AI has created. Um, my writing process with AI, I use Voice to Text. Highly recommend that for anyone that's struggling with the AI's, uh, the AI-isms, the generic sounds. Because then you can actually have your real organic words that are coming through instead of the AI having to invent things along the way and using the, you know, standard fallbacks that they like to throw in there.

Yeah. So it's not just a tool, it's really about giving it the right type of context.

Yes.

Yeah. Okay. So another thing I see constantly, and I know it's personally, I say I see constantly because I'm doing it, is, you know, tool overload. So people feel like they need all these different platforms, subscriptions, they're not sure what's working. So how do you help businesses figure out, you know, what tools are actually supporting growth? Do you have things that— do you have a process or a framework that you walk through?

Yeah, so when I come in and I'm working with a client on what AI tools that they are going to be adopting across their organization, I look first at their business KPIs, and we identify the core projects and tasks in those projects that they are going to be using to drive the growth. Because if you're not having real business impact, why are you investing in this tool? But then I also work with the people actually doing those tasks because they're the boots on the ground. They're the ones who know how the job works, they know what they need and what the expectation is, and they're the ones who are responsible ultimately for their own KPIs that are driving those business KPIs. So you have to come at it from both sides, work together. It's a collaborative process. You get the same, those people in the same room, Have those conversations, get that clarity, and then we go through and start figuring out where AI can be injected into those tasks and what tools are going to be the best tools for the job.

Yeah. What do you, what do you think happens or what do you see happening when a company skips that KPI step?

Shadow AI becomes a problem where people are just using AI sort of Wild West.

Okay.

And there's no process, no framework. No process, no framework. The value of AI becomes all about time savings, but then that time savings evaporates.

Okay.

And people are getting the benefit, but that's not translating to business benefit. And so now people are getting their job— their jobs done faster, but they're not necessarily relaying that into reappropriating that time.

Yeah. So I would kind of describe that as like the, the AI for fun phase. Like, we're just kind of throwing spaghetti up against a wall and kind of seeing what's going to stick. So you've tried it, you've played with it, but it's not really part of, you know, true operations. So what does it look like when you move, and the clients that you work with, when you move from experimenting to actually executing with AI? How do people do this in an organized approach, and how do you take them through an organized framework?

So again, you come at it from the perspective of the KPI and the tasks needing done so that a role within a team responsible for a project, responsible for KPI, that, but those roles have dedicated tasks that people are going to be using. So there's a framework built from the ground up, but you also know what target you're reaching for with that framework. You know what you're building towards. Taking it away from AI for fun and getting it into that actual growth and scaling phase also talk needs to be, uh, you know, it needs to be a cultural side. You need to have those conversations, those learning opportunities, the cross-department interaction where people are sharing ideas and exchanging those best practices. You start doing that and you'll start seeing a lot more intentional growth with your AI use.

So we've had the privilege of, you know, having several conversations, getting to do some speaking together around AI, and I have heard you say, this several times. You, you say that AI is a magnifying glass, and I would love if you would explain to the audience what that means, because I think you do a really great job of, you know, giving some insight there.

Absolutely. Uh, yeah, so again, my catchphrase is AI is a magnifying glass. If you have an expert in the room, it's going to magnify that expertise, and if you have an empty chair in the room, it's going to magnify that you have an empty chair. So There's a number of studies out there. I've been writing about them in, on my LinkedIn posts lately, so by all means check them out. Absolutely. But there's a number of research out there where AI plus a person outperforms teams of people or either the person or the AI independently. It's about that collaboration before between the person and the AI. And what is possible when you have the human in the loop, HIDL. You'll see that word thrown around or that acronym thrown around a whole lot. And the AI's contribution as a thought partner, not as a completer of the tasks, but rather as a supporter of the human completing the tasks.

Yes, I like that. So, so often we kind of think about, you know, it's just the AI or it's just the human, but putting them together and kind of building that optimization, it's almost like they're, they're coworkers. I know I've heard different organizations talk about, you know, that coworker strategy, which kind of helps build some of the excitement around getting to work and becoming optimized. Where do you see, where do you see leaders unintentionally creating fear around AI? You know, we talk about like, we've got all these new tools, we've got all these things, like the AI can do a lot of different things. I know that you talk about, you know, having a human in the loop, having Heidel, but I also see in some organizations where, there can kind of be fear around AI. So where do you see leaders unintentionally creating that fear?

First is in a lack of communication on what the vision is. There, you know, when ChatGPT 3.5 dropped, I was a content marketing manager and I went through the existential crisis moment of, you know, I have 10 years of teaching experience. I just transitioned into marketing. I just started making growth. And now here's this AI thing. Coming along, I need a new career. I have since changed my perspective on that, but there was a moment when I was very concerned on the longevity of my career and what my future was going to look like with, you know, I have 3 degrees in English and this thing can write, so now what? Making it known, leadership's perspective and dedication, to that union between AI and human and finding that collaborative piece of co-working with AI, focusing on improving people's skills with working with AI, that is where fear evaporates. When people see how much better they can perform time-wise, quality of work-wise, type of work, because AI is going to expand how much you can innovate new ways of creating things, reaching, you know, new widgets, whatever it is that you're— whatever it is you're making, or new ways to reach your client base. When people realize how much innovation is just at their fingertips, the fear is going away. But if you keep that abstract, if you, uh, are leading your people and not communicating that you have a vision for a co-working environment between people and their AI, they're going to wonder is this coming from my seat or is it going to be sitting next to me?

No, and you make a really good point because we've had some of these conversations too at Clarity and at AUI. And as we're working on innovating, we're also making sure that we build a significant amount of psychological safety within our organization because what we don't want is, you know, fear around the tools. So I'm not going to use it because this is going to replace me or fear around. And the other— the opposite of that is now you're going to make me use all of these AI tools and how much more work am I going to do? So having the conversations around, we're using these, they're going to help in optimizing, we're going to be able to do more things, the human things that we like doing, like the client interaction, the conversations, things that are more face-to-face. I agree with you as we continue to walk through learning new things, also being willing to admit that there's going to be times where we're going to make mistakes. I mean, we know different large language models, different AI companies have had to roll back different things because they've made mistakes. So this is always just part of the process because we're learning something new. This is a very innovative process. How do you, when you're starting to work with clients, you know, tool fatigue is something that can be really real. How do you introduce the planning or the concept of, you know, what are the right tools that we're going to use at this point in time? And how many tools on average do you encourage people to start using all at once?

One.

Very good.

Start with one. Okay. If you come in with the fire hose, all you're going to do is just blast everything off the table and nothing's going to work. Start small. Pick again, looking from two sides, approaching this from your KPIs and then also from the people doing the task responsible for building up those KPIs. Pick one instance, one team, or, you know, whether they're working on the same tasks. But you need to assemble a small group of AI-forward people who can champion this. And they start with small tasks that support KPIs, but that are not going to completely, you know, cut the legs out from underneath the business because that's a lot of pressure to put on an experimental process where people are trying to learn how this thing works. And start with one tool and see what your people can do. Learn how it works for your company, evaluate it against your KPIs and what you're hoping for, and then rinse and repeat.

Okay, so reiteration, because I think that, you know, repetition is really important. It's the mother of skill. So are you saying, Heather, that we should pick like the most complicated process in our business and we should start with AI there? No. Okay.

Start with the tasks that you're— the people who are going to be championing, championing AI that they know and do well already, because the best place for you to evaluate the efficacy of a new tool in a process is in a process that you already know where you're not having to stumble through the process itself, but rather you can fact check on the fly how this tool is performing and where you can best apply it. You need to have a strategic look that requires a lot of metacognition over the task at hand. And metacognition is hard. That's, that is a, that is a hard ask for people. So make sure that it's a task that they know well, that they can think metacognitively about, and then start injecting AI where it makes sense to them.

Yeah, so I know that at AUI and Clarity, we've been working on, you know, different types of innovation and adoption, and we've been, you know, building our use cases, picking our projects, following some of the things that you've said, and specifically about, you know, picking one thing. We found a really great project that we started with was around some of our sales and marketing practices and helping with some of the lead qualifying that we were doing. It was a tedious task that we We just never really had anyone that was either really good at it or really wanted to do it to the level of just, you know, day in, day out. So we've been able to kind of train and work with a model to kind of build that for us and do the lead qualification. What are some common things that you're seeing now in different businesses, different ideas, different tracks that they're taking? What are some examples for those in our audience that are like, I don't even know where to start? Like, what are some common things that you're seeing, use cases? For small business?

Uh, yeah, so sales and marketing are generally a pretty easy in with AI. That's— there's a lot of work there, and the nature of, especially with marketing, uh, which is, you know, and that's where I come from, so my brain always goes there first, but it's forward-facing. And so having AI coming in there versus on anywhere where there are HIPAA, where there's PII that is much more sensitive, you know, proprietary information. Marketing tends to work on a very forward-facing set of data. So it's a safer place to start experimenting with this new technology that when you make a mistake, you don't necessarily want your secret sauce involved in that.

Yeah.

I also see professional development. HR has been very AI forward because AI has the potential to dramatically rewrite how we teach, how we learn. I'm, you know, I have a 5-year-old daughter. I'm very excited to see what education looks like for her moving forward. And that's not just in K-12 education, but in professional development for the rest of our careers.

Yeah.

And how we can change, improve, better learn processes, access information in new ways. It's really exciting to see how all that's coming together. So I'm seeing a lot of those departments coming in there anywhere where you need to train your staff, which is every department. And so HR has been pretty big player in that.

Nice. So I know that there are probably people listening that are early adopters. They understand all sorts of different things about AI, but there's probably some other listeners that this is the first time, they're really starting to listen and think about, you know, what could I do with my business? And they may, like, they maybe haven't really started yet and they feel like they're behind. So what's that one small practical way that they can start maybe using AI this week without overcomplicating it?

I like having my AI play sort of devil's advocate.

Okay.

Uh, where it challenges my ideas. AI is intrinsically sycophantic. So you have to train it. You have to tell it that you want it to do this critical process against your thoughts so that you can take your idea, have the AI review it, punch some holes through it so that your idea can come out stronger on the other end. It's not about the AI doing the thought for you, but instead it's asking questions, questions that you may not have considered, so that you can answer them and come out with something stronger on the other side. You start doing that and you're going to start having some ideas that have been really run through the gauntlet.

So Heather, I know you do some different types of education and training. Would you like to talk about, you know, I know that depending on when they listen, it may or may not be on the calendar, but I know you do recurring training. So if you talk about the different types of trainings that you do.

Yeah, so, uh, my favorite one right now is the L.I.G.H.T. framework, uh, which is L-I-G-H-T. It is Landmark Identity Gauntlet, Harbor, and Thinking. And it's how I build my personal assistants to be the best coworker for me. They have the Heather operating system in there, and I help people build the Chrissy operating system or what have you, so that the AI tool that they are using is custom fit to them. It is the tailored suit that, you know, you put it on, and when you're working with it everything just flows. So that one, uh, we are going to be doing on a recurring basis.

Wonderful.

Yeah, I'm really excited about that one. Um, we have a book in the works on it. Very excited to share that out. Uh, and then we have operating, uh, operational AI that you and I do, which I'm hoping that we can continue to do that on a regular basis. Yeah. And talk about, uh, responsible AI frameworks and how to help your people through the change.

Wonderful. So as people are connecting with you, um, we'll make sure that we link everything in the show notes to your LinkedIn, um, your website, and then of course to the events that you have coming up, different trainings. Um, we end the, the episode or conversation that we have with the same question every time, and that is, you know, um, if someone is listening today, what would you tell them to get 1% better in their business?

Talk to your people.

Mm.

Who do you have that are AI champions? How are they using AI? And have those conversations with them because that will take you much further than just 1%.

Wonderful. Heather, thank you for your time today. Thank you. And I'll be back to wrap up the episode.

Thank you.

So I learned a lot from my conversation with Heather today. You know, AI is not about doing more. It's really about doing the right things better. And if you start with tools and just tools and a lot of tools, you're going to create noise. But if you start with your business, which means your goals, your workflows, and your team, you're going to foster curiosity and you're going to create clarity around the things that you're wanting to accomplish. You know, curiosity can help belay fear, and clarity can really drive adoption. So don't try to overhaul everything at once. Just pick one thing, one process, one framework, one thing to keep you moving. Pick one task and start there, because small consistent improvements are what actually change your business over time. You know those 1% things that we talk about every week in every episode. So if this episode helped you, share it with another business owner who's trying to figure out AI as well. Connect with Heather on LinkedIn and look into attending one of our workshops. And as always, keep working on getting 1% better in your business every day. Thank you.