AI Innovation, Customer Trust, and Startup Strategy with Brian Ardinger and Robyn Bolton

On this week's episode of Inside Outside Innovation, Robyn and I talk about creating flywheel effects through customer obsession, the landscape of AI startups and what's real and what's not, and why workers don't trust AI. Let's get started.

Inside Outside Innovation is the podcast to help innovation leaders navigate what's next. Each week we'll give you a front row seat into what it takes to grow and thrive in a world of hyper uncertainty and accelerating change. Join me, Brian Ardinger, and Miles Zero's Robyn Bolton as we discuss the latest tools, tactics, and trends for creating Innovations with Impact. Let's get started.

Podcast Transcript with Brian Ardinger and Robyn Bolton

Startup Ecosystem Building, Travel, and Early Observations

[00:00:45] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger, and with me, I have a co-host Robyn Bolton from Mile Zero. Welcome, Robyn.

[00:00:50] Robyn Bolton: Thank you. Great to see you, Brian. 

[00:00:52] Brian Ardinger: Great to see you. Both you and I have been on the road quite a bit for the last couple weeks, so it's nice to actually say hello again and get back into the swing of things.

I spent last week in Savannah, Georgia, talking about startup ecosystem building with the Savannah Harbor Innovation Partnership. And they're looking for new ways to spice up and kickstart a lot of the startup activity there. So it was quite interesting. As an innovator, I think it's always important to get out to other communities and see what's going on and share war stories and best practices and all that kind of fun stuff. So, it was fun to get out there.

I give a shout out to what they're trying to do, trying to get the right people across all parts of their ecosystem together, whether it's founders or investors, university, and things along those lines. I think they're doing a good job of trying to kickstart a lot of stuff going on down there. I'm excited to see where they go to. 

[00:01:41] Robyn Bolton: Savannah is home to one of my favorite innovations, the Savannah Bananas. But yes, I was on the road too. I went a little further afield. I was in London for the Thinkers 50 Conference, which as you would imagine was extremely interesting, especially these days where everything is so volatile and uncertain everywhere across the globe.

Thinkers 50 Takeaways and Early Reflections on Uncertainty

And there was a lot of discussion around how now more than ever, is a time for courage and to be brave. There was a lot of discussion around what the future holds and several brave souls who just said, we don't know. It could be anything. One of my favorites was Daniel Pink. He said, basically, we're living in the era of Schrödinger's cat, that the future will be radically different and the same.

All at the same time. And I'm like, okay, that sounds totally fair. So lots of really interesting ideas. Lots to think about, as you would expect from a conference's called Thinkers 50. Fascinating, fascinating conversations. 

[00:02:47] Brian Ardinger: Now we're going to open the box and what do we find when, when it's opened? The box is already open. You know, we're going down that path no matter what. And you know, it is kind of interesting. You, you're seeing a lot more bubble talk and things like that, but yet yesterday Nvidia had their quarterly announcements and $5 trillion valuation and blew out their estimates.

And so it's like, well, it's not a bubble yet, or people are at least spending money NVIDIA's getting paid for this stuff. So, we'll, we'll see where it all shakes out. 

[00:03:12] Robyn Bolton: Yeah. Even if it's a bubble, I mean, we had an internet bubble back in the early part of the century and it didn't mean the internet went away. It just means we resorted ourselves. So even if AI is a bubble, I don't think it's going away.

The Flywheel Effect, Customer Obsession, and Human-Centered Touchpoints

[00:03:26] Brian Ardinger: Got three articles to talk about today. First one's called the Flywheel Effect: How Customer Obsession Creates Self-Reinforcing Advantages. This is from Wildfire Labs. They've been putting out some great content. The Flying Wheel Effect talks about building a startup isn't about growth hacking. It's really about how do you create customer experiences and these flywheels that generate self-reinforcing momentum because there's so many things out there taking aways attention and competing for dollars and mindset.

So how do you build into your process different ways that you can create a flywheel to differentiate and build it up? So, one of the examples they talk about is chewy.com and how Chewy built into their experience the idea of when a person's pet passes away, they actually sent them flowers. And created an experience and a touchpoint as part of that to relate to their customers but also create a means for further conversations. And, you know, creating a positive experience with that brand and with that company. 

[00:04:27] Robyn Bolton: Yeah, I think it's so interesting and this idea of flywheel, it's one of the things mentioned in the article is the first step is creating an exceptional experience that creates emotional impact.

Rising Customer Acquisition Costs and the Decline of Consumer Trust

And you just think of our world right now, which is focused on cost cutting and on driving waste out of the system and on AI. The first step of creating this flywheel and this incredible loyalty and retention and word of mouth is so very human.

You know, I think more and more we're going to start seeing that the more human you can be, you know, a handwritten card, sending flowers. That's something probably you could get AI to do, but it's a very human thing to acknowledge the grief that comes with the loss of a pet.

The more human businesses can be, especially at key moments, that's where they're going to win. That's where they're going to differentiate themselves, in a world that is increasingly kind of more robotic and lean. 

[00:05:27] Brian Ardinger: The ironic thing is, startups have the exact same tools to create and reach customers as in the past. So it's being commoditized, the ability to actually grab a customer and have that first interaction.

But the cost of customer acquisition, I think some of the statistics they had in the article talked about what costs, you know, a hundred dollars in 2019 now costs $160. You know, a startup that spends 61% of their new capital on customer acquisition up from 28% in 2018. So those are massive jumps and it's hard to make a business model work if you have that much to acquire the brand new customer and you can't keep them from churning or going somewhere else.

Community Building, Trust Signals, and Real Startup Differentiation

And the other things, the idea of trust and how consumer brands are, the ability to trust brands is going down 73%, I think they said reported increased skepticism toward marketing claims, and that makes sense that you're seeing a lot of AI slop and a lot of things. Who do you trust anymore?

And then finally, this idea of how do you build a community around your company, not just a product or service, word of mouth being so important. 78% of successful seed stage companies cite that community and referrals as one of their primary acquisition sources. 

[00:06:35] Robyn Bolton: To create all of that, to build the trust, to build the community, to build the word of mouth, it doesn't take millions of dollars. I mean, I think about companies that I've bought from, and I get like a little, again, handwritten card in that first shipment and that's so different from getting the Amazon package that I just don't even bother looking at what's in it and just pull out my product.

Practical Customer Journey Mapping and Choosing One Moment of Truth

I'm loyal to those companies with that human touch because I'm like, oh, there are actual humans here that are doing this, and that doesn't cost millions of dollars. Especially if you're a startup. You just kind of get this huge bang for your buck by just taking a moment and you get that trust. You build that loyalty. You build those social media moments by doing the little things and that's so much easier. I will say not easy, but easier for a startup to do it and build in, versus a huge multinational company.

[00:07:35] Brian Ardinger: And again, I think a lot of startups fall into the trap. They see what's on the internet and they follow the five-steps advice that they see on the blog or, or something along those lines. But just doing some basic blocking and tackling as far as like, okay, how can you map out the customer journey? Like how do they first interact with you? What are the touch points that you have? How can you identify those critical interactions?

And then what can you do to enhance or improve or double down or differentiate those particular experiences and recommend anybody out there, go through your customer journey if, if you have customers out there and try to figure out what are those kind of key moments of truth to work on?

[00:08:10] Robyn Bolton: And it doesn't have to be every single moment of truth. Pick one. Yeah, start there and see what happens.

Reverse Engineering AI Startups and the Problem of Repackaged APIs

[00:08:16] Brian Ardinger: Alright, the second article is titled I Reversed Engineered 200 AI Startups, 146 are Selling You Repackaged Chat GPT. So welcome to the world of AI. This is an article from Towards AI. And this person did an amazing analysis.

We looked at the 200 funded AI startups from Y Combinator and some other places and did a deep dive on what these platforms were being built on and did an analysis of trying to figure out what's the underlying thing and, and from that he looked at network traffic. The code traced some API calls, and he found out that 73% of these 200 startups are running third party APIs with just extra steps.

Just basically running on top of open AI or, or Claude. While that's not necessarily the problem, it's how the landscape has changed and how they are positioning their companies around this and kind of saying, we've got these proprietary new things. Well, a lot of times it's really just a wrapper and buyer beware.

[00:09:17] Robyn Bolton: This article, when you sent it to me, I literally stopped everything I was doing. Just kind of chuckled because in some ways when you're playing with, when you're experimenting with a bunch of different AI offerings, there's kind of this creeping suspicion of like, are you just layering on top of Chat GPT?

Defensibility, Real AI Innovation, and Investor Due Diligence

Because I could ask ChatGPT or Claude or whoever this question and get the same answer and it takes me back to a session at the InnoLead conference impact. That happened at the end of October, and there was a woman on there, Rana El Kalioubi, who was talking about the state of AI today, and she said, as an investor, she has a VC firm, that one of the first questions she asks is, what is your defensibility as an AI offering?

What is it that you are uniquely bringing? Because if you can answer that. Then it's fine that you're building on top of, but if you don't have anything defensible, then bubble alert. 

[00:10:18] Brian Ardinger: Looking at the data of the 200 startups, he said that 8% were actually pretty concerning from the standpoint they copied open source code without attribution. Basically, we're misrepresenting exactly what they had. And effectively what you could have done as either a customer, you could have just be paying premium prices for an API that you could just literally drop into, into chat GPT yourself and asked the same kind of questions.

Bubble Signals, Ecosystem Implications, and Developer Opportunity

He did say that there were 27% of the companies that he looked at were doing some, building real tech, building off novel architectures or specialized data sources or that were creating some uniqueness to it. And I think the bottom line is, again, a lot of people will say, well, who cares if it works? And then you're creating value. Let people buy and use whatever they want.

But I think as we are trying to understand. The value of AI and how do we build and create things in this marketplace, it's important for investors. You know, taking a look at, are you funding prompt engineering or AI research and make sure you're paying the valuations for what you are paying for.

From a customer perspective, are you paying premium for an API costs that are just marked up. For developers, you know, looking at, quite frankly, this was kind of exciting from a developer perspective. You could look at it and say, all these companies out there, they're creating real businesses that are getting paid for that. And I can build something too, because there's barrier for entry to actually test and try and build things, are pretty low. And then finally, from an ecosystem perspective, when 73% of the companies are misrepresenting their technology, we're probably in a bubble territory in some form or fashion. 

[00:11:48] Robyn Bolton: As you just described, there are so many layers to this article. It's so well researched. And Interesting that wherever listeners fall in the ecosystem, it is well worth reading because I read it from the user, the consumer, the casual civilian point of view.

Employee Trust, AI Adoption Resistance, and Organizational Dynamics

I sent it to my husband who is a programmer, a developer, and he took away completely different things, but still it's like, wow, this is incredibly well researched and fascinating and has a really important message about kind of the state of AI at the moment. 

[00:12:24] Brian Ardinger: And it's a great segue to our third article, which is from Harvard Business Review, and the title of the article is Workers Don't Trust AI: Here's How Companies Can Change That.

So, this take was more from the standpoint of an organizational perspective. There's research showing that companies that are putting AI tools into the workplace, employees are, are not feeling the love of that a lot of times and not trusting necessarily what's coming out of the exec room, as well as kinda maybe the disconnect that they're hearing from the marketplace where AI is gonna take your job.

And yet all these companies are saying, Hey, you've got to use AI. There's definitely a tug and pull around what do we do with this new technology and, and how can we position ourselves for this? 

[00:13:03] Robyn Bolton: The stats that begin the article make me chuckle that trust and company provided gen AI tools fell 31% between May and July. Usage of employer provided AI tools declined 15% between February and July. And to these employees, company-sanctioned tools, feel imposed, not introduced, mandated, not co-created.

Misaligned Communication, Job Security Fears, and Predictable Pushback

And that, as you said, employees that are being asked to advance the very technology that's going to replace them. And this made me chuckle because I'm like, yes, this is totally predictable. If you just imagine humans and especially large companies where decisions, especially a purchaser, an implementation of big eyed, AI tends to be centralized and then just pushed out.

They're not excited to train their replacement and put themselves out of a job. And so, especially with a lot of top-down things, if you just kind of say, hey, here's this AI, it's going to help you. You know, people are like, no, it's not. It's going to replace me, and so I'm not going to use it. I'm not going to train it, and I'm going to keep doing my job so that I get to keep my job.

In so many ways, this was like, yeah, saw this coming. It was fascinating to see the data start to prove it out. But then also, you know, there are some success stories in the article that are like, hey, here are things you can do to try to get some ROI from that AI. 

[00:14:28] Brian Ardinger: You know, I think a lot of it is probably partially from the ecosystem of media talking about a variety of different things. Everything from AI's going to cure cancer to whatever. And you get into an environment where you start using it, and it's like, well, this isn't going to cure cancer. Could barely do, you know, the basic research or something. But you can see that you know, the step from here to there.

AI Timeframes, Realistic Expectations, and Misaligned Use Cases

And part of it, I think is, you know, maybe the timeframe that people are getting confused on or, you know, is this going to happen tomorrow? Like everybody's saying, it's going to happen, or is it going to take place over a longer period of time?

And, and I think the other thing is, a lot of companies are not necessarily very good at trying to understand like, what's the best use case. So that they're looking at it from let's deploy to technology versus what are we trying to solve here?

And what's the best way to solve that problem? And is AI a component of that or not? And I think when you just throw technology at a person, say you've gotta use this without clear understanding of what you're using it for and the benefits that you're trying to build, it does create an environment where it's hard to know how to navigate.

[00:15:29] Robyn Bolton: Yeah, I was talking to our mutual friend, an innovation colleague, Jared Simmons, earlier this week, and he had this great analogy that with AI, we've essentially dropped a combustion engine into a buggy factory.

What a lot of companies are doing is they're like, okay, let's figure out how to bolt the combustion engine onto the buggy. And what we really need to do is figure out what is going to happen to the horse when we turn this thing on. What's going to happen to the stability of the buggy? What's going to happen to the driver? And we need to think through a whole lot of things before we just jam everything into the existing paradigm.

Tactics to Try: Gratitude, Culture, and Flywheel Thinking

[00:16:02] Brian Ardinger: That leads us to our tactics to try for the week, maybe thank your team, thank your customers. Be grateful for the world we're living in today. 

[00:16:10] Robyn Bolton: I'll pile onto that, and taking an inspiration from the flywheel is think about how you can make gratitude a flywheel part of your business. So not just in Thanksgiving, but kind of every day, every time you know your process is run, how can you build expressing gratitude into that. And just make it part of how you do business.

[00:16:32] Brian Ardinger: Excellent. Well, thanks again for coming on Inside Outside Innovation. We look forward to seeing you next time and have a great Thanksgiving.

That's it for another episode of Inside Outside Innovation. Today's episode was produced and engineered by Susan Stibal. If you want to learn more about our teams, our content, our services, check out insideoutside.io or if you want to connect with Robyn Bolton, go to MileZero.io, and until next time, go out and innovate.


Articles Discussed

The Flywheel Effect: How Customer Obsession Creates Self-Reinforcing Advantages - Wildfire Labs

I Reverse-Engineered 200 AI Startups. 146 Are Selling You Repackaged ChatGPT and Claude with New UI - Towards AI

Workers Don’t Trust AI. Here’s How Companies Can Change That - HBR

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This podcast is available on all podcast platforms and InsideOutside.io. Sign up for the weekly innovation newsletter at http://bit.ly/ionewsletter. Follow Brian on Twitter at @ardinger or @theiopodcast or Email [e-mail]

On this week's episode of Inside Outside Innovation, Robyn and I talked about creating flywheel effects through customer obsession, the landscape of AI startups, and what's real and what's not, and why workers don't trust AI. Let's get started.

Inside Outside Innovation is the podcast to help innovation leaders navigate what's next. Each week we'll give you a front row seat into what it takes to grow and thrive in a world of hyper uncertainty and accelerating change. Join me, Brian Ardinger, and Miles Zero's Robyn Bolton as we discuss the latest tools, tactics, and trends for creating Innovations with Impact. Let's get started.

Podcast Transcript with Brian Ardinger and Robyn Bolton

Startup Ecosystem Building, Travel, and Early Observations

[00:00:45] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger, and with me, I have a co-host Robyn Bolton from Mile Zero. Welcome, Robyn.

[00:00:50] Robyn Bolton: Thank you. Great to see you, Brian.

[00:00:52] Brian Ardinger: Great to see you. Both you and I have been on the road quite a bit for the last couple weeks, so it's nice to actually say hello again and get back into the swing of things.

I spent last week in Savannah, Georgia, talking about startup ecosystem building with the Savannah Harbor Innovation Partnership. And they're looking for new ways to spice up and kickstart a lot of the startup activity there. So it was quite interesting. As an innovator, I think it's always important to get out to other communities and see what's going on and share war stories and best practices and all that kind of fun stuff. So, it was fun to get out there.

I give a shout out to what they're trying to do, trying to get the right people across all parts of their ecosystem together, whether it's founders or investors, university, and things along those lines. I think they're doing a good job of trying to kickstart a lot of stuff going on down there. I'm excited to see where they go to.

[00:01:41] Robyn Bolton: Savannah is home to one of my favorite innovations, the Savannah Bananas. But yes, I was on the road too. I went a little further afield. I was in London for the Thinkers 50 Conference, which as you would imagine was extremely interesting, especially these days where everything is so volatile and uncertain everywhere across the globe.

Thinkers 50 Takeaways and Early Reflections on Uncertainty

And there was a lot of discussion around how now more than ever, is a time for courage and to be brave. There was a lot of discussion around what the future holds and several brave souls who just said, we don't know. It could be anything. One of my favorites was Daniel Pink. He said, basically, we're living in the era of Schrödinger's cat, that the future will be radically different and the same.

All at the same time. And I'm like, okay, that sounds totally fair. So lots of really interesting ideas. Lots to think about, as you would expect from a conference's called Thinkers 50. Fascinating, fascinating conversations.

[00:02:47] Brian Ardinger: Now we're going to open the box and what do we find when, when it's opened? The box is already open. You know, we're going down that path no matter what. And you know, it is kind of interesting. You, you're seeing a lot more bubble talk and things like that, but yet yesterday Nvidia had their quarterly announcements and $5 trillion valuation and blew out their estimates.

And so it's like, well, it's not a bubble yet, or people are at least spending money NVIDIA's getting paid for this stuff. So, we'll, we'll see where it all shakes out.

[00:03:12] Robyn Bolton: Yeah. Even if it's a bubble, I mean, we had an internet bubble back in the early part of the century and it didn't mean the internet went away. It just means we resorted ourselves. So even if AI is a bubble, I don't think it's going away.

The Flywheel Effect, Customer Obsession, and Human-Centered Touchpoints

[00:03:26] Brian Ardinger: Got three articles to talk about today. First one's called the Flywheel Effect: How Customer Obsession Creates Self-Reinforcing Advantages. This is from Wildfire Labs. They've been putting out some great content. The Flying Wheel Effect talks about building a startup isn't about growth hacking. It's really about how do you create customer experiences and these flywheels that generate self-reinforcing momentum because there's so many things out there taking aways attention and competing for dollars and mindset.

So how do you build into your process different ways that you can create a flywheel to differentiate and build it up? So, one of the examples they talk about is chewy.com and how Chewy built into their experience the idea of when a person's pet passes away, they actually sent them flowers. And created an experience and a touchpoint as part of that to relate to their customers but also create a means for further conversations. And, you know, creating a positive experience with that brand and with that company.

[00:04:27] Robyn Bolton: Yeah, I think it's so interesting and this idea of flywheel, it's one of the things mentioned in the article is the first step is creating an exceptional experience that creates emotional impact.

Rising Customer Acquisition Costs and the Decline of Consumer Trust

And you just think of our world right now, which is focused on cost cutting and on driving waste out of the system and on AI. The first step of creating this flywheel and this incredible loyalty and retention and word of mouth is so very human.

You know, I think more and more we're going to start seeing that the more human you can be, you know, a handwritten card, sending flowers. That's something probably you could get AI to do, but it's a very human thing to acknowledge the grief that comes with the loss of a pet.

The more human businesses can be, especially at key moments, that's where they're going to win. That's where they're going to differentiate themselves, in a world that is increasingly kind of more robotic and lean.

[00:05:27] Brian Ardinger: The ironic thing is, startups have the exact same tools to create and reach customers as in the past. So it's being commoditized, the ability to actually grab a customer and have that first interaction.

But the cost of customer acquisition, I think some of the statistics they had in the article talked about what costs, you know, a hundred dollars in 2019 now costs $160. You know, a startup that spends 61% of their new capital on customer acquisition up from 28% in 2018. So those are massive jumps and it's hard to make a business model work if you have that much to acquire the brand new customer and you can't keep them from churning or going somewhere else.

Community Building, Trust Signals, and Real Startup Differentiation

And the other things, the idea of trust and how consumer brands are, the ability to trust brands is going down 73%, I think they said reported increased skepticism toward marketing claims, and that makes sense that you're seeing a lot of AI slop and a lot of things. Who do you trust anymore?

And then finally, this idea of how do you build a community around your company, not just a product or service, word of mouth being so important. 78% of successful seed stage companies cite that community and referrals as one of their primary acquisition sources.

[00:06:35] Robyn Bolton: To create all of that, to build the trust, to build the community, to build the word of mouth, it doesn't take millions of dollars. I mean, I think about companies that I've bought from, and I get like a little, again, handwritten card in that first shipment and that's so different from getting the Amazon package that I just don't even bother looking at what's in it and just pull out my product.

Practical Customer Journey Mapping and Choosing One Moment of Truth

I'm loyal to those companies with that human touch because I'm like, oh, there are actual humans here that are doing this, and that doesn't cost millions of dollars. Especially if you're a startup. You just kind of get this huge bang for your buck by just taking a moment and you get that trust. You build that loyalty. You build those social media moments by doing the little things and that's so much easier. I will say not easy, but easier for a startup to do it and build in, versus a huge multinational company.

[00:07:35] Brian Ardinger: And again, I think a lot of startups fall into the trap. They see what's on the internet and they follow the five-steps advice that they see on the blog or, or something along those lines. But just doing some basic blocking and tackling as far as like, okay, how can you map out the customer journey? Like how do they first interact with you? What are the touch points that you have? How can you identify those critical interactions?

And then what can you do to enhance or improve or double down or differentiate those particular experiences and recommend anybody out there, go through your customer journey if, if you have customers out there and try to figure out what are those kind of key moments of truth to work on?

[00:08:10] Robyn Bolton: And it doesn't have to be every single moment of truth. Pick one. Yeah, start there and see what happens.

Reverse Engineering AI Startups and the Problem of Repackaged APIs

[00:08:16] Brian Ardinger: Alright, the second article is titled I Reversed Engineered 200 AI Startups, 146 are Selling You Repackaged Chat GPT. So welcome to the world of AI. This is an article from Towards AI. And this person did an amazing analysis.

We looked at the 200 funded AI startups from Y Combinator and some other places and did a deep dive on what these platforms were being built on and did an analysis of trying to figure out what's the underlying thing and, and from that he looked at network traffic. The code traced some API calls, and he found out that 73% of these 200 startups are running third party APIs with just extra steps.

Just basically running on top of open AI or, or Claude. While that's not necessarily the problem, it's how the landscape has changed and how they are positioning their companies around this and kind of saying, we've got these proprietary new things. Well, a lot of times it's really just a wrapper and buyer beware.

[00:09:17] Robyn Bolton: This article, when you sent it to me, I literally stopped everything I was doing. Just kind of chuckled because in some ways when you're playing with, when you're experimenting with a bunch of different AI offerings, there's kind of this creeping suspicion of like, are you just layering on top of Chat GPT?

Defensibility, Real AI Innovation, and Investor Due Diligence

Because I could ask ChatGPT or Claude or whoever this question and get the same answer and it takes me back to a session at the InnoLead conference impact. That happened at the end of October, and there was a woman on there, Rana El Kalioubi, who was talking about the state of AI today, and she said, as an investor, she has a VC firm, that one of the first questions she asks is, what is your defensibility as an AI offering?

What is it that you are uniquely bringing? Because if you can answer that. Then it's fine that you're building on top of, but if you don't have anything defensible, then bubble alert.

[00:10:18] Brian Ardinger: Looking at the data of the 200 startups, he said that 8% were actually pretty concerning from the standpoint they copied open source code without attribution. Basically, we're misrepresenting exactly what they had. And effectively what you could have done as either a customer, you could have just be paying premium prices for an API that you could just literally drop into, into chat GPT yourself and asked the same kind of questions.

Bubble Signals, Ecosystem Implications, and Developer Opportunity

He did say that there were 27% of the companies that he looked at were doing some, building real tech, building off novel architectures or specialized data sources or that were creating some uniqueness to it. And I think the bottom line is, again, a lot of people will say, well, who cares if it works? And then you're creating value. Let people buy and use whatever they want.

But I think as we are trying to understand. The value of AI and how do we build and create things in this marketplace, it's important for investors. You know, taking a look at, are you funding prompt engineering or AI research and make sure you're paying the valuations for what you are paying for.

From a customer perspective, are you paying premium for an API costs that are just marked up. For developers, you know, looking at, quite frankly, this was kind of exciting from a developer perspective. You could look at it and say, all these companies out there, they're creating real businesses that are getting paid for that. And I can build something too, because there's barrier for entry to actually test and try and build things, are pretty low. And then finally, from an ecosystem perspective, when 73% of the companies are misrepresenting their technology, we're probably in a bubble territory in some form or fashion.

[00:11:48] Robyn Bolton: As you just described, there are so many layers to this article. It's so well researched. And Interesting that wherever listeners fall in the ecosystem, it is well worth reading because I read it from the user, the consumer, the casual civilian point of view.

Employee Trust, AI Adoption Resistance, and Organizational Dynamics

I sent it to my husband who is a programmer, a developer, and he took away completely different things, but still it's like, wow, this is incredibly well researched and fascinating and has a really important message about kind of the state of AI at the moment.

[00:12:24] Brian Ardinger: And it's a great segue to our third article, which is from Harvard Business Review, and the title of the article is Workers Don't Trust AI: Here's How Companies Can Change That.

So, this take was more from the standpoint of an organizational perspective. There's research showing that companies that are putting AI tools into the workplace, employees are, are not feeling the love of that a lot of times and not trusting necessarily what's coming out of the exec room, as well as kinda maybe the disconnect that they're hearing from the marketplace where AI is gonna take your job.

And yet all these companies are saying, Hey, you've got to use AI. There's definitely a tug and pull around what do we do with this new technology and, and how can we position ourselves for this?

[00:13:03] Robyn Bolton: The stats that begin the article make me chuckle that trust and company provided gen AI tools fell 31% between May and July. Usage of employer provided AI tools declined 15% between February and July. And to these employees, company-sanctioned tools, feel imposed, not introduced, mandated, not co-created.

Misaligned Communication, Job Security Fears, and Predictable Pushback

And that, as you said, employees that are being asked to advance the very technology that's going to replace them. And this made me chuckle because I'm like, yes, this is totally predictable. If you just imagine humans and especially large companies where decisions, especially a purchaser, an implementation of big eyed, AI tends to be centralized and then just pushed out.

They're not excited to train their replacement and put themselves out of a job. And so, especially with a lot of top-down things, if you just kind of say, hey, here's this AI, it's going to help you. You know, people are like, no, it's not. It's going to replace me, and so I'm not going to use it. I'm not going to train it, and I'm going to keep doing my job so that I get to keep my job.

In so many ways, this was like, yeah, saw this coming. It was fascinating to see the data start to prove it out. But then also, you know, there are some success stories in the article that are like, hey, here are things you can do to try to get some ROI from that AI.

[00:14:28] Brian Ardinger: You know, I think a lot of it is probably partially from the ecosystem of media talking about a variety of different things. Everything from AI's going to cure cancer to whatever. And you get into an environment where you start using it, and it's like, well, this isn't going to cure cancer. Could barely do, you know, the basic research or something. But you can see that you know, the step from here to there.

AI Timeframes, Realistic Expectations, and Misaligned Use Cases

And part of it, I think is, you know, maybe the timeframe that people are getting confused on or, you know, is this going to happen tomorrow? Like everybody's saying, it's going to happen, or is it going to take place over a longer period of time?

And, and I think the other thing is, a lot of companies are not necessarily very good at trying to understand like, what's the best use case. So that they're looking at it from let's deploy to technology versus what are we trying to solve here?

And what's the best way to solve that problem? And is AI a component of that or not? And I think when you just throw technology at a person, say you've gotta use this without clear understanding of what you're using it for and the benefits that you're trying to build, it does create an environment where it's hard to know how to navigate.

[00:15:29] Robyn Bolton: Yeah, I was talking to our mutual friend, an innovation colleague, Jared Simmons, earlier this week, and he had this great analogy that with AI, we've essentially dropped a combustion engine into a buggy factory.

What a lot of companies are doing is they're like, okay, let's figure out how to bolt the combustion engine onto the buggy. And what we really need to do is figure out what is going to happen to the horse when we turn this thing on. What's going to happen to the stability of the buggy? What's going to happen to the driver? And we need to think through a whole lot of things before we just jam everything into the existing paradigm.

Tactics to Try: Gratitude, Culture, and Flywheel Thinking

[00:16:02] Brian Ardinger: That leads us to our tactics to try for the week, maybe thank your team, thank your customers. Be grateful for the world we're living in today.

[00:16:10] Robyn Bolton: I'll pile onto that, and taking an inspiration from the flywheel is think about how you can make gratitude a flywheel part of your business. So not just in Thanksgiving, but kind of every day, every time you know your process is run, how can you build expressing gratitude into that. And just make it part of how you do business.

[00:16:32] Brian Ardinger: Excellent. Well, thanks again for coming on Inside Outside Innovation. We look forward to seeing you next time and have a great Thanksgiving.

That's it for another episode of Inside Outside Innovation. Today's episode was produced and engineered by Susan Stibal. If you want to learn more about our teams, our content, our services, check out insideoutside.io or if you want to connect with Robyn Bolton, go to MileZero.io, and until next time, go out and innovate.