On this week's Inside Outside Innovation, Robyn and Brian sit down to talk about the AI question that no one wants to answer, the power of a good value proposition, and why industry veterans are building tomorrow's billion-dollar startups. 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 Opening Reflections on Innovation and the Year Ahead [00:00:30] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger, and we have Robyn Bolton, our co-host from Mile Zero. Welcome, Robyn. [00:00:53] Robyn Bolton: Thank you. Great to be here as always. [00:00:55] Brian Ardinger: We've got the number of different articles we're going to talk about today. As everyone knows, this podcast is about giving the real insights of what's going on in the world when it comes to innovation. What's going on in your world? [00:01:07] Robyn Bolton: It's funny, it's time of year, so kind of feels like everyone is both wrapping up and gearing up, trying to bring things to a close. So, we can all effortlessly and go on the holidays, but January we'll be here before you know it. And so people are already starting to think about what's going on with AI in 2026, and what does the new world of work look like? [00:01:29] Brian Ardinger: I'm looking forward to my inbox being filled with the best things that happened in 2025 and what to look forward to in 2026, and like kind of year-end wrap stuff that you get. It's interesting times, especially like on the investment front, you know, a lot of things slow down at the end of the year as people start planning for it. I kind of love and hate this time of the year from the standpoint of, gives you some time sometimes to do that stuff that you don't always have time to do and remap what you're going to do for 2026. [00:01:55] Robyn Bolton: Yes. And speaking of the emails, wrapping things up. Spotify's Yearend rap came out I think a couple days ago, so also getting a lot of those in the old inbox. [00:02:07] Brian Ardinger: Alright, well let's get into it. We've got a couple of articles to talk to today. The first one that we came upon was from KP Ready. It is called the AI Question. Nobody wants to Answer and KP does a good analysis. He basically says, is the juice worth the squeeze when it comes to AI. And I think a lot of people are asking that question right now. You know, as more and more enterprises, you're hearing about more and more experiments, more and more people using the technology, and you're getting conflicting results and feedback on is this really paying off. All the money that's being spent into ai, all the things that we're doing around it. Are we seeing the returns and when will we see the returns? You know, from my understanding and what I've seen, the question is not like, will we receive returns, but when and how do we get through this exploration phase so that we can be effective with using the dollars and the time and the resources around this to actually find the value that's created. And so let's start with that particular article. What was your thought on it? Is the Juice Worth the Squeeze? AI ROI and Experimentation [00:03:04] Robyn Bolton: There's always this level of uncertainty around new technologies of is the juice worth the squeeze? Are we gonna get ROI? When are we going to get ROI? Running lots of experiments, but it definitely seems like AI has kind of amplified that. I actually just wrote a blog post asking, like, did your AI strategy, was it developed by the underpants gnomes? And just in case there, we have listeners who don't know who the underpants gnomes are, they're from South Park, and basically their business plan is phase one, collect underpants, phase two, question mark, phase three profit. And it just seems like there are so many AI startups, companies, experts, consultants, et cetera out there who have become underpants gnomes. And kind of just have this like, hi, put it on top of everything, and profit, and no one's kind of slowing down to kind of like, well, do we even need AI? How do we need it? Like, what makes sense here? [00:04:04] Brian Ardinger: I think a lot of people are not necessarily thinking. They feel the pressure to start doing something with AI, and so they start immediately deploying and doing things without looking at, well, is this a particular area that really would benefit? Or could we create real value if we can get this right? And they oftentimes overlook some of the other kind of hidden costs when you talk about it, deploying technology that's new or different. And I think more importantly, how it affects the culture of the people deploying it. So, you've got the, you know, the data infrastructure costs, you've got the integration complexity, you've got the change management, ongoing maintenance, all these kind of hidden costs when you're dealing with a brand new technology that you don't necessarily know. And some of the things I saw in the article that were interesting and I've seen in real life too, is how you can kind of maybe think through this process of, you know, which particular project should we deploy and that? Don't be afraid to kill experiments quickly if you're not seeing ROI in a particular area, you know, maybe shelve that particular idea and focus on one that is showing some value to it. Don't focus on having to deploy it everywhere, all at once. Again, try to find the particular areas or the particular people that are more willing and able to make those steps. And then thinking about that, you have to build everything yourself. I think that's another place where I'm seeing a lot of brand new tools and folks out there that are trying things that have already built some things that maybe you can go out and purchase and buy and experiment rather than having to come up with your own team to do and make all the mistakes that they're probably already going through it and made that tool in the first place. [00:05:00] Robyn Bolton: So, all great advice, and I just want to underscore the people aspect is you have people who are going to use this, people that you hope will benefit from it. Some people who will be resistant, and so don't underestimate the people, the human. AI interaction and all of those dynamics as part of the rollout, the implementation, the change management, all of that. Sharp Value Propositions in the AI Era [00:05:30] Brian Ardinger: All right. The second article is from our good friend Ben Yoskovitz. He always puts out some great stuff. His article on his substack called Focus Chaos is called the Real Differentiator in the AI era, A sharp specific Value proposition. Ben talks about how a lot of folks are falling into particular traps of, again, thinking that, well, I've got AI so hot, I'm going to be deploying AI, and let's go out there and build a startup around that, and without thinking about, well...
