On this week's episode of Inside Outside Innovation, we talk about the addictive nature of AI, the levels of innovation metrics, and how peer influence can make or break your AI rollout. 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

AI Addiction, Innovation Metrics, and Peer Influence in AI Rollouts

[00:00:30] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger, and with me, I have Robyn Bolton from Mile Zero. Robyn, welcome.

[00:00:47] Robyn Bolton: Thank you very much. Great to be here as always.

[00:00:50] Brian Ardinger: It's another amazing week in innovation and we thought we'd get right to it. The first article we want to talk about is called Acceleration Flow by Raymond Mark from the publication Mold and Yeast.

Why AI Feels Addictive to Builders and Coders

Fascinating article. The basic premise of the article talks about how Raymond is an addict. Not a metaphorical addict, but he is now addicted to building using AI such the fact that he's spending tokens like it's the end of the world. And he talks about this environment where the AI now has created almost a gambling type of a feeling where you vibe code your way to something. You put your tokens in and you pull a slot machine and out comes some type of output that's just good enough to get you to put the next tokens in to try the next prompt and the next prompt.

So, it was a fascinating look behind the scenes that I think just now more and more people are beginning to discover this particular anomaly or environment that people are becoming to find when they start doing this AI stuff.

[00:01:53] Robyn Bolton: Yeah, this was really interesting. I mean, I use AI every day and I felt this deeply. It actually reminded me of a conversation that I had with someone probably a year and a half, maybe two years ago, who astutely predicted she's like, I think AI is going to become the next cigarettes in terms of being addicting and it's now, it's cheap and plentiful and it's getting us hooked on it.

The Dopamine Loop of Generative AI and Vibe Coding

And then they can raise prices because we're addicted and we'll keep going with it. And this article lays out a really good argument for that. Not using cigarettes but using gaming and gambling as a metaphor and kind of everything that it outlines of, like you said, it's almost right. It's enough to get you to put the next token in. The feeling that you're upleveling and you're gaining capabilities when you're really kind of not. In fact, you're with kind of outsourcing tasks and things, you're actually losing capabilities, but you have the illusion that you're gaining capabilities. It was just really fascinating all of these almost mind tricks that happen when we use AI.

[00:03:07] Brian Ardinger: I read the article earlier last week and then three people came up to me this week unprompted and said, I'm addicted to this stuff. They just started to, you know, use Claude code or started to get a little bit more deeper than just prompting a chat bot and the word they used was addicted. One, again, it's so easy to get something back out that dopamine hit of, oh, I tried this and actually it's pretty good and let me try if I can go again.

AI FOMO, Always-On Agents, and the Fear of Falling Behind

And then the second addiction is, I'm addicted to the fact that I'm falling behind. I had a coder come up to me and said, I am very worried that I don't want to take a break because what, during my break, I want my agent to be doing something for me.

And so, this constant pressure to interact with the device to continue to move forward is interesting. I think the flip side to that is what are we building and what are we doing? Are we just putting tokens into the machine or are we actually creating value in the process? And I think that's the next phase that people will be hopefully going through.

[00:04:04] Robyn Bolton: This line struck me, making yourself obsolete feels like freedom, dressed up as ambition. And I just thought, Ooh, that, that hits a little close to home.

[00:04:14] Brian Ardinger: And well, we will see what happens. I am addicted as well. Probably not to the extent that some of these folks I'm talking to, but, but who knows, you know, there's always next week.

[00:04:21] Robyn Bolton: Exactly.

How Peer Influence Drives AI Adoption at Work

[00:04:23] Brian Ardinger: The second article I want to talk about today is from HBR. It's talking about Peer influence can make or break your AI rollout.

Fascinating thing about this is HBR took a look at how companies were deploying AI and which ones were being successful at deploying it and which ones were not. And one of the primary findings was the fact that companies and the people that were actually peer reviewing or showing what they were building with their colleagues, and that using peer influence as a way to encourage adoption was actually a more effective way than either a mandate or just giving people the opportunity to interact with these particular tools.

[00:04:59] Robyn Bolton: The degree to which the peer-to-peer learning influences, it was surprising. The fact that it has an influence I didn't find surprising. What I did find really shocking was that leadership communication and leader encouragement had little to no impact on AI usage.

Why Leadership Messaging Alone Does Not Increase AI Usage

And you know, the article does go on to say that like, hey, even though there's no measurable impact, leaders do still play a really important part in encouraging the experimentation. Encouraging the sharing of learnings. I was surprised by that. And also, as I said, not surprised by the peer-to-peer because when somebody you work closely with and trust is like, hey, I'm doing this. It's just kind of this reassurance of like, oh, if I log into the GPT, I'm not going to get fired like, because I've been replaced. Here's someone who's still employed using AI. I can do it.

[00:05:54] Brian Ardinger: I'm hearing more and more people tell me, oh, I used this tool to do this. Versus in the past, you could see their work and say, you obviously used something for this. But they're more open about sharing those things, and I think that environment in your company to be open to sharing both the good and the bad and like, what's working, what's not working, here's what I'm using it for, I think opens up a lot of doors because I think a lot of people just don't know necessarily how to use this or what particular use cases could be valuable.

It's all about, at this stage, kind of the experimentation and understanding and seei...