How AI Can Help You Compete at a Higher Level

This transcript was created using AI tools and is not a verbatim, word-for-word transcript of the episode. Please forgive any errors or omissions from the finished product.

Courtney: [00:00:00] How can AI help your company compete at the next level? In other words, how can it help you punch above your weight? Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era. As always, I’m joined by Knownwell, CEO, David DeWolf, Chief Product Officer, Mohan Rao, and Chief Strategy Officer Pete Buer.

We also have a discussion with Aaron Linne, who has worked with Kodak, Meta and Microsoft about his role as a futurist in the age of ai. But first the news.

Courtney: Pete Buer joins us as always to break down some of the latest AI headlines and how they apply to your business. Hey, Pete.

Pete: Hey Courtney. How are you?

Courtney: Doing good. I would be doing better though if my bracket held up. Uh, which relates to the first story this week, Pete?

Uh, [00:01:00] it comes to us from Forbes and because tonight is the championship, the article is titled Slam Dunk Technology: How AI is Revolutionizing the Game of Basketball. Pete, can you give us an overview of this one?

Pete: You bet. This is sort of, uh, Moneyball comes to hoops in the form of ai. Uh, the article covers how NBA teams are using AI to achieve competitive advantage. And the prime example that they use is, um, a couple teams using ai. To examine game footage and statistics to drive discovery around player strengths and weaknesses, team dynamics and the like.

Ultimately so that coaches can make better decisions about, um, rotations. For instance, you know, what players tend to get hot in what kinds of circumstances? When does it happen? When should we sub in, sub out? What’s the combination of team members that will perform best on the court given a certain [00:02:00] type of competitor, uh, and so on.

Totally cool stuff. What I like better about the article though, is how it describes. The representation of AI use cases across all of the basketball business, for lack of a better term. Game optimization, yes. But also injury prevention, scouting, recruitment, fan engagement, marketing. That’s the lesson for leaders, and that’s what we’ve been stressing, is that there’s space for AI to play, uh, across multiple courts in your arena.

We, we often use the example of electricity. Uh, as a corollary for, for ai, you, you wouldn’t, with electricity newly at your fingertips, so to speak, you wouldn’t figure out how to light up a lamp in the corner of your family room, right? You would examine the entirety of the home for all the wonderful applications that electricity can bring.

Same story. Look across [00:03:00] the full footprint of your business and find all the different ways that AI can be powering you to, um, higher levels of competition.

Courtney: The next article comes to us from payments, and the headline reads, Wendy’s launches an AI driven loyalty platform to deliver customized results. Pete, what’d you think about this one?

Pete: So what a wonderful industry to be, um, looking for use cases for ai. Fast food is brutally competitive. Moving a percent of market share is incredibly valuable and incredibly difficult. Uh, but there’s tons and tons of data on customer buying behavior and preferences and, uh, so so why wouldn’t you? Right?

And so, um, to your intro, Wendy’s is using an AI. Uh, application to drive a customer loyalty play. So based on analysis of pest purchases across different segments, uh, creating customized offers for you [00:04:00] personally in the hopes of getting you to spend more, getting you to bring friends to buy with you, getting you to buy more frequently as loyalty programs are oriented to doing totally logical approach.

And depending on the segments that they target and room for change in buying behavior among those segments, and by the way, how quickly the competition responds, right? Because that’s the, the challenge in loyalty programs. Um, throughout, throughout all of time, um, maybe Wendy’s will squeeze out some competitive edge.

What an AI powered loyalty program can’t do is change the underlying product. Or service. And we also know from the press that Wendy’s takes a a little bit of a beating on that many times. But then again, this is something that AI could be helping them with as well.

Courtney: Very cool, Pete. Thank you as always.

Pete: Thank you.

[00:05:00] You know, AI could end up being the game changer for small and medium sized businesses. As you’ll hear in this discussion with David and Mohan on why the fortune may soon favor small, nimble, agile firms versus the larger providers with more historical cache.

Courtney: David Mohan, you may not remember this, but a few weeks ago we had Greg Alexander from Collective 54 on, and he said something that really resonated with me.

David: Okay.

Courtney: It used to be the big eat the small. Now the fast eat the slow. And it seems like this moment with ai and as we move further into the AI era, is becoming more and more true. So I wanted to ask both of you for executives [00:06:00] listening today, How can we use AI to really punch above our weight, so to speak?

How can we start to compete with companies we’ve never been able to compete with before?

David: I think it’s a great question, Courtney, ’cause it does resonate with me. Uh, I’ll tell you the thing that I thought of as soon as I heard Greg say that was, we’ve talked about this as the great, um, equalizer and how there will be a. A revival of the middle market because of ai. And, and I think as I start to think of that and frame a response for you, where my mind goes is there are a lot of aspects of being a great business that are really hard and expensive when you’re subscale, right?

And, and by scale we’ve often thought of. These huge behemoths, right? Um, but artificial intelligence starts to give us and democratize some of those functions. And I think on the show before we’ve talked [00:07:00] about, for example, people operations, the HR world typically isn’t done phenomenally well in the middle market, and it’s because it’s so expensive to go do.

Compensation benchmarking is just a small, very niche example. Right. But I do think this technology allows us to, and I really believe that it is going to shift the landscape. And I love the way Greg framed that as the fast eats slow, right? As opposed to, uh, the, the small and the big, and. I think it’s something that’s really worthy of exploring, and I go first and foremost to back to those altitudes we’ve talked about so many times around ai.

It is the operational and the strategic knowledge work that has been harder and harder and harder to do. When you’re a small business, you just don’t have the ability to do it, but you out execute. Right? I think the great equalization is happening because we now. Can automate some of that [00:08:00] operation, some of that strategy work that the, the large behemoths can and have historically been able to afford to do through manual labor.

Mohan: I, I agree with that. Um, you know, technology has always been a weapon for the small to compete against the big and also for the big to compete against the small, uh, right. So, so it’s, uh, it cuts both ways. I. But being small means you can be faster, all right? So by definition you can be faster. There’s less bureaucracy, there is less coordination.

There is, um, um, innovative new ways that you can do things and change your processes, so on and so forth. Uh, so, so I agree with that. Premise that it’s really gonna be about speed. And the way you can start thinking about it is, um, a very similar formulation to what, uh, David just said, which I would kind of break it into like, uh, in a slightly different way, but it amounts to the same thing.

How can you use AI to help the individuals in your company,

David: like whatever

Mohan: it is, their function. [00:09:00] How can you help at a team level?

David: Hmm.

How can you help at an organizational level and how can AI help at, uh, providing better products and services to your customers? So if you just kind of build upon that hierarchy of individual team, organization, and your customers, and then start thinking about the AI opportunities, uh, in each of these levels, that’s how you can compete with bigger companies by moving faster at each of these levels.

Mohan. I, I think the naysayers are gonna say, yeah, but for artificial intelligence to be powerful, data is so important and the large businesses just have access to so much more data that companies just aren’t gonna be able to compete. How do you respond to that? How, how does the middle market and the small business compete in a world where they just don’t have the volumes of data?

Mohan: Yeah, I think everybody has data to begin with. You are producing data all the time, right? So you may not have the volume of data to make better and stronger predictions, uh, that a bigger [00:10:00] company with a lot of data might have. Uh, but it with the framework that you, uh, mentioned or I mentioned, uh, right, so if you’re writing code.

Code is the data to write better code.

David: Hmm

Mohan: Uh,

David: mm-Hmm.

Mohan: is a better copy to, uh, you run it through a tool and do a better job at it, so on and so forth. So everybody has data. It is true that the more data, better organized data, the better use cases you can think of. Bigger companies have an advantage, but they also have to move.

A much bigger rock across,

David: Hmm. that’s an interesting way to look at it.

Mohan: the, that’s the, uh, uh, so there’s always data. It’s question of how do you come up with a use case where you

David: Hmm.

Mohan: AI to further your business?

David: And I think there’s also so much publicly available data now that’s available too, right? You’re like, just think about these LLMs that are now being democratized, that’s trained on the world’s data, right? And so we now all of a sudden have access to this intelligence in a way that the middle market didn’t have to have that [00:11:00] data.

And, and

so how do you tap other people’s data? Um, that’s, that’s readily available.

Mohan: So David, question for you as an, as an entrepreneur who moved against big companies and built something small into. Uh, a sizable company in your past life, what are the ways that small companies can compete against big companies? And then

David: Hmm.

Mohan: we can layer in AI, if that’s okay with you, Courtney?

David: Yeah.

Courtney: That’s great.

David: Well, I, I do think the, the scrappiness, um, that we often associate with an entrepreneurial company is very true. Right there, there tends to be a passion and a belief in the employees of an entrepreneurial organization that leads them to pour the whole heart and soul in a way. That you just don’t experience with a larger organization most of the time.

Um, I think you also have the, the core concept of speed, right? You can move a speedboat faster than a cruise ship, right? You just can, right? And when you are talking about responding and having, [00:12:00] whether it’s five fifty five hundred or five thousand employees, it’s a lot easier to move. All of those numbers than it is 500,000 employees.

Right? It just is. And so you can respond to the market faster. Um, I also think personal relationships, right? Like, like there’s a lot of goodness that comes with, um, you know, process and the different things we put in place as we scale to be efficient. But it also erodes the personal. Ability. Right? And it undermines the ability to, I think a lot of times entrepreneurial companies, especially at the early on, are successful because people connect with people.

And that personal aspect drives trust, drives belief, drives wanting to root for the underdog, right? Like those types of things. Um, and I think you lose that as you scale. So I think it’s these. Very nuanced things where I go back to, I think about all of those, [00:13:00] right? Leading people, um, personal relationships.

What are these? These are humans. Being humans, I think it’s putting, as I think of ai, it’s allowing us to be more human, um, and do less of what isn’t uniquely human in differentiating us and helping to get that momentum.

Courtney: I think that’s really interesting and I love this conversation. I think for all the executives listening, especially if you in are in a mid-market company or smaller, hopefully it gets you a little, you know, a little boost, uh, this morning as you think about it. I wanna ask you two, one more question.

yes, it’s so true. You can just move a speedboat faster than a cruise ship, you know? We, that’s kind of par, but especially right now as you think about deploying AI within organizations, I’ve heard over and over again, it seems like these smaller companies are able to do that faster. But do you think there is [00:14:00] like a window of time where that will not be true?

You know, that it will kind of even out, and so is there a unique moment for people listening to us that are in mid-market and smaller companies?

Mohan: I think the time is now, right? So we know that, uh, we’ve talked in the past that the bulk of the AI technologies that we’ve been talking about, especially around generative AI, is a Horizon two in the Three Horizons framework. Uh, right. So, uh, so it is coming, it’s, it could be an year or two away from getting to that, uh, peak of what you can do with, um, uh, with many of the, um, LLMs out there.

Um, so I think the time is now for, uh, the mid-market companies to start, um, organizing their use cases, start organizing their, uh, uh, data for A POC and getting going with that. I don’t think, uh, much any delay from this point on is useful, uh, for something to [00:15:00] catch up.

David: Yeah. You know, we had an episode a few, few episodes ago where we said, Hey, it’s not past the point of no return. Right. Um, that you’re digging a hole deeper and deeper, but you can still catch up. Um, I think that landscape’s changing. I. Very quickly. Um, I’m seeing more and more and more adoption and the advantage right now to AI is not just the efficiency and the productivity and all of the ROI we see, it’s that you will have that when your competitors don’t.

And getting ahead of that curve has proven out over innovation, after innovation, after innovation to be incredibly powerful in terms of your ability to actually. Jump to the other side and make it, if you get left behind, you’re gonna get left behind. So I’m kind of with Mohan. Um, I don’t know why you’d be waiting to be honest with you.

Um, and I’d be making smart bets, um, and really looking, uh, at what [00:16:00] can I leverage that’s out there that can accelerate me and really help me begin to compete in the way I haven’t been able to compete before.

Mohan: In the buy versus build spectrum, I think consuming. ai, especially generative AI, is a no-brainer tray, right? So you should be doing that if you’re not already doing it, but you should be taking the steps beyond it as well from consumption of, uh, generative ai, whichever, whatever flavor you like, uh, you can then start embedding that into your applications and services.

That’s a step further from just consuming it. And from there, as David was saying, you can go way deep into creating your own custom models. That’s a full custom build, and that would be truly transformational because you’ve built something strategic within your company. But for, for most companies to get there, it is few years out.

But the journey to start from consumption to embedding should, has to start soon, uh, sooner, uh,

David: Yeah.

Mohan: now.

David: as you’re saying that what’s coming to my mind on, on this [00:17:00] buy side is let’s just talk about some examples, right? Like we’ve talked about just execution work. If your team’s not using chat GPT to to write documents, they’ve gotta write already and get initial drafts. What are you doing? I. Like get out there and do it.

Right. I then go to some of the, the use cases that have been out there for a while, a sixth sense we’ve talked about on this podcast before. Right? It’s all about identifying intent data of who is buying the services. That is a little bit of AI that. Can you be leveraging a platform like that and then look at what we’re building at at Knownwell, right.

We are reinventing the way professional service companies are run, allowing to be them to be much more client oriented and centric through client intelligence. We are putting a platform out there and looking for partners to partner with us in. Bringing this to market, right? And so why wouldn’t you be taking some of those experiments and using some of those tools?

Those are just three different versions, kind of, uh, that get more and more [00:18:00] complex as you go. But you could very safely be taking risks with.

Courtney: Mohan, really great conversation. Thank you.

Mohan: Thank you, Courtney. Thanks David.

David: Thanks. It was fun.

Courtney: Are you ready to get started with ai, but unsure whether your company is actually ready for a full scale transformation? If so, first of all, you’re probably not alone, but second, we have a really great tool for you. You can go to Knownwell dot com slash assessment and get a personalized diagnostic of where your organization sits today and what they need to do to get ready for the future.

Courtney: Aaron Linne chatted with Pete Buer recently about what it means to be a classically trained futurist and what his training is helping him see on the horizon for ai.

Pete: Aaron, it’s so great to have you on the podcast. [00:19:00] Welcome.

Aaron: Thank you. Pleasure to be here. I.

Pete: If I may, first, I’d like to pull a line up from your LinkedIn profile because I’d like to understand it better. The description says you are a formerly trained futurist and managing technologist who reaches rising generations through native, interactive and digital languages.

Pick that apart for me. What does that mean? Um.

Aaron: Well, it means I actually am formally trained, the way that future studies works is that you look at current trends, current things happening in the world, you extrapolate them out 20, 50 years and say, you know what? If this trend just keeps going and nothing stops it, or what if this other trend outta nowhere comes in and, and, and creates an event that changes the world, right? For businesses, you then take that 20 year idea and say, this is the future I want. This is the future. I don’t want, what can I do today to get to that future and make that future happen? Or what can I do today to prevent that future? And they, and so you just break it down step by step, going backwards, which is the exact same thing that you do in development for product management, right?

You say, I want to have a feature built. I [00:20:00] want to have this, you know, cool new product. How do I get from that release to today what we need to do today?

Pete: what a cool moment in business history to be a futurist as the crashing wave of AI is, is hitting our, our beaches. I don’t even know how to focus the question, but like, when, when, as a futurist, you look at the hard questions that businesses need to be answering for themselves. What are, what are some of the big ones?

Aaron: I think the biggest one when it comes to AI specifically is what can’t it do, what

Pete: Hmm.

Aaron: not do? Right. Um, and we don’t know the answer to that period because we, ’cause we are, you know, as, as Bezos would say, we’re day one of the internet. We’re, we’re not even day one of ai. Right. Um, but, but, but we kinda are.

and I think. About AI in the way that it’s going to be a fundamental change to society in the exact same way that the printing press was. When before the printing press, before [00:21:00] you had books readily available to people, you had a specific language is what you heard, you know, Latin, especially the church, right?

You, you went and, and, and you heard the Bible in Latin. And so you, if you didn’t know Latin, you didn’t understand it, or, um, if you wanted to look up a passage in the Bible or whatnot, you couldn’t because you couldn’t read it. And so then all of a sudden you get the printing press and that leads to literacy and it leads to new ideas and new in-depth thoughts about the life universe and everything.

Right? Uh, and that becomes a fundamental change to our identity as a human, that we can start thinking for ourselves, that we can take in new information that we choose to take in, and that we can come, uh, read whatever book we want, whenever that was way back then, I think the same kind of. Societal change is gonna come from AI being available and readily available to everyone.

Pete: tell us, uh, a little more about, uh, AI producer. That’s sounds extremely cool and love to learn more.

Aaron: Absolutely. So, [00:22:00] um, when I was at Microsoft Teams, uh, one of the things that I got to build was, uh, the actual concept and the creation of. Apps in meetings, right? Um, and so being able to add any app into the meeting, that was one of the first things I got to build. And then I also got to build all the broadcast features, and I got to build a thing called the BDK, the broadcast Development kit, all that leading to different companies, um, different broadcasters, uh, the NFL, the voice, the Olympics, all using teams in order to.

to their broadcast, especially during Covid, right? ’cause you couldn’t come in person. during that time, between those two things, one, because I was um, working on the apps and meetings. Feature. And because I was working on broadcast features, I got introduced to a company, uh, AI producer, and they were so far ahead.

This was like, gosh, three, four years ago that they were already utilizing AI to do broadcast production in a way that I, I was impressed. Back then. I thought I was gonna put me out of a job because I have, like, how can I, I can’t even keep up with them [00:23:00] and, and now I get to work with them, which is so, so cool.

All it, uh, what it is, is it is literally using AI to manage the production of a broadcast. Uh, so all the different things that you would think of that go into it, switching back and forth, cameras doing different things with screen shares. Um, I. Right now it’s honed in for, uh, kinda like a town hall experience,

Pete: Uh.

Aaron: if you’re on teams or whatnot and you have a big enterprise company, uh, that way, uh, an assistant or a, a new person new to production, they can just click a button and let the whole thing run itself

Pete: We often get into conversations maybe with a futurist lens. This’ll be a good one for you too, about how, uh, AI in a situation like that, uh, makes jobs go away or makes jobs better. What’s your, uh, I. Digest. How do you digest that one?

Aaron: it democratizes all kinds of things, right? You know, uh, if you think about any kind of technology, uh, it actually makes the best, the people that are best at that skill or the best, that are [00:24:00] even better, right? Because it’s more accessible. And so now more people have the ability to do a thing.

Then you find out who’s the best at it. it doesn’t mean that that jobs in general go away. It actually means that there’s opportunities for new jobs or new things to happen because you’re not wasting your time doing something that you’re not good at or you’re not wasting your time doing something, you know, like trying to learn like you, you’re just natural at it.

Good. Go do it. Uh, I mean, uh, think about like Word, right? How many authors out there. Because Microsoft Word,

Pete: Right.

Aaron: to just write something down and email it to someone instead of scribing it down, you know, and, and taking it to who? To the, to the, to the publisher and all these things.

No, it’s, it’s, it’s, now anyone can, can create something and get it out there in the world. Same thing with this kinda production stuff, right? So yes, it’s always gonna be experts and it’s gonna be those people that make a lot of money because they’re highly talented and have a highly niche skill. But this opens up more people to learn how to do production.

Pete: If I’m, uh, an executive listening to the podcast and I’m trying to think about for my business, what’s the next smart, [00:25:00] cool thing I can do to solve a big problem or to make operations run better, taking advantage of ai, what would your advice be?

Aaron: Uh, just to play with it. Just play with it. Right. Um, because, uh, it’s not scary, right? You can’t break the world. It’s not an actual evil ai. You’re not gonna put something in there and say, oh, everyone. But whatever it is that you’re challenged with, whatever it is that you’re working on, there probably is some sort of AI tool that is, uh, that can help you move forward with it.

And that’s just all that Che GPD has done is it makes it easy that I can type in a sentence the way that we would normally work and normally talk, and then we, we get a response back. But once you start learning what is possible with ai, then you can start applying it to your own business. You know, there’s 1,000,001 different things that you can do with it.

Uh, and, and going back, if I made it like AI producer, right? We think about right now AI as, okay, well you’re, you’re creating an image and whose image are you [00:26:00] training it off of? Right? And what, what art is it being trained off? What photography is it being trained off of to create these new things? Well, that’s just images.

Okay, now we have, uh, the, the videos that are being created. We have Che gp, which is responding with, with text. Right? What other things are out there that can be generative? Right? So like, that’s one of the things we’re doing with AI producer is as we grow the product. There’ll be thoughts in there of like, okay, I want this to look and feel like a talk show.

I want this to look and feel like a sports center. I want this to look and feel like the wwe e you know, Nice. Yeah. that I like. But we, you know, but there’s training that AI to understand how different production things can happen, right?

you can create music with ai, right? You can just say, I want this beat and I want this kind of stuff, and then it just pumps it out. Use the ai, ai, play with it, and then start to think about what, what, what can I do that’s different?

And what can I hire a, an engineer that is doing something completely different and unique than everyone else, because that’s already been done. But as you start figuring out [00:27:00] what works for your business, uh, what is, what’s the unique thing that you do anyways, work on that.

Pete: Aaron, I, I can’t believe we’re getting to the end of time. It seems like that flew pass. Thank you so much for joining us today. It’s been an honor and, uh, I’ve appreciated all of your insights.

Aaron: My pleasure. Thank you for having me.

Courtney: Thanks as always for listening and watching. Don’t forget to give us a review, legit. It is super helpful for us and we would really appreciate it. at the end of every episode, we like to get one of our AI friends to weigh in on the topic at hand, so chat, GBT.

How can AI help small and medium sized businesses compete against larger organizations?

[00:28:00]

Courtney: and now you’re in the know. Thanks as always for listening and watching. We’ll be back next week with more headlines, round table discussions and interviews with AI experts.

Hey, if you made it this far in the episode, first of all, thank you. And second, we know that AI is changing all the time, and so we’ve got you covered. Here is another great episode for you to watch, to stay in the loop on what’s happening in AI and business, and second of all, we’d love for you to subscribe.

You can do that right here. I’ve always wanted to do that, by the way, so do that now. That would be great.