Ep 64: Adapting to Change, Tech, and AI in the Workplace
Watch the YouTube video version above or listen to the podcast below!
Episode Summary
Key Themes:
Generational reactions to media narratives
The psychological cycle of adopting change
Challenges of AI adoption in modern workplaces
Organizational complexity and data integration
Emerging roles in marketing and tech teams
Segment Breakdown:
Generational Responses to Change:
Alex kicks things off by comparing how each generation reacts to new technologies, likening the cultural resistance to AI to the way boomers and Gen X reacted to millennials. The hosts laugh about how every generation is labeled as "lazy" and "entitled" by the one before them.Adoption Cycles and Magical Thinking:
Ruthi introduces the classic "peak of excitement → trough of disillusionment → equilibrium" cycle seen with new tech and generational integration. The conversation explores how initial enthusiasm often clashes with real-world implementation challenges—what Dave calls "magical thinking" versus reality.The Myth of the Easy Button:
Alex and Dave deconstruct the fallacy of the “launch button” in tech projects. From website overhauls to language localization, they emphasize the depth of unseen labor behind seemingly simple requests. Home improvement metaphors abound, with painting rooms becoming a perfect analogy for project underestimation.AI and Workforce Realities:
Dave shares anecdotes of people blaming AI for job losses, and the group agrees that unwillingness to adapt is often the real culprit. They explore how real adoption of AI takes time, effort, and mental energy—luxuries not all employees have.Company Culture & Structured Learning Time:
Highlighting Airtable’s week-long AI exploration initiative, the hosts discuss the importance of giving employees space to learn. Ruthi compares this to Ford’s 7-month shutdown to convert factories to electricity—change takes dedicated time.The Emerging “Super Glue” Role:
A lively discussion about the emerging, undefined roles bridging IT, data, marketing, and compliance. Ruthi coins the term "Super Glue"—those unsung heroes ensuring tools, teams, and data work together. This role resembles SEO professionals of the past: undefined, cross-functional, and critical.AI, Martech, and Data Privacy Challenges:
The episode closes with discussion on AI’s integration into marketing stacks, including issues like data cleanliness, legal compliance, and the challenge of building a “smart CRM.” Dave raises concerns about agency access to proprietary data and forecasts deeper discussions in upcoming episodes.
Ep 64: Adapting to Change, Tech, and AI in the Workplace Podcast and Video Transcript
[Disclaimer: This transcription was written by AI using a tool called Descript, and has not been edited for content.]
Dave Dougherty: All right. Welcome to the latest episode of Enterprising Minds. We got the whole crew here, and that's been awesome. I really wish you guys would've heard what we were talking about before we hit record. So we're going to, we're going to jump you back in. Into that conversation. Alex, Peru, you have the interesting insight where we're like, huh, we should record that.
Go ahead and queue us up.
Generational Reactions to News
Alex Pokorny: Think at least for part of the episode, we can talk about this. It's just an interesting comment on how different generations and the news media has always reacted to news about other generations. Thinking about the first memes and news about millennials and then right.
Gen Z Alpha, you name it. Every time there's a big splash article saying something about a generation, the other generations then have a reaction to it. And that reaction, I was wondering if that's kind of like the AI reaction of do we change what we're doing? No, I don't want to. Oh. But we need to eventually I guess we will like, there's like this whole like, process that everyone goes through and there's some people who get stuck on step one. They're like, no, I'm not changing they're a small part of the market. I don't need to change yet. And then they try not to ever change, and that probably goes poorly for them, let's be honest. And then there's others who are like, oh, I'm going to change immediately.
You're changing a little too fast. It's not quite there yet. Again, it's probably not going to go for it's just kind of interesting.
Adapting to Change and AI
Alex Pokorny: And then always there's this, immediate outcry kind of reaction that you get from the media each time something gets published about this generation versus that generation and that outcry seems.
So similar to the AI outcry of it's stealing our jobs, it's not stealing our jobs, it's going to replace doctors. It's not going to replace doctors. It's come on. Like what? What are we doing here?
Ruthi Corcoran: So, I was just curious, what was the memes around? What were the memes around millennials? I don't even remember.
Dave Dougherty: We were trash. We didn't know how to work. Yeah. It's always the same ones. Yeah. It's no matter what generation it is, it's, they don't want to work. They only want it their own way and they're selfish.
Alex Pokorny: Yeah. Something else probably, that's been true of each generation as they come up into the workforce is, oh, they don't know what they're doing.
It's yeah. because they just started yeah, you have to learn. That's part of the process. Also to teach them, which is also part of the process, but let's not have that responsibility.
Ruthi Corcoran: This is, this fits so perfectly. So there's that wonderful that wonderful chart of like people's stages going through a new change.
And there's like the peak of excitement and then there's like the trough illusion mint. And then you level out as people figure out what to do. And I see that as well. I think there's such a cool analogy here where it's oh, the next generation they're so excited. They're so passionate, right?
And then to your points. They get in the workforce and everybody goes, oh shit. They like, they've never done this before. They don't actually know how to do their job. They have to learn. And then, it's, they find this leveling off period. I see that same continuum that you guys just described very much with people's adoption of new tools.
Challenges of Implementing New Tools
Ruthi Corcoran: In the workforce or anywhere, but especially in the work that we do where there's a lot of hype and excitement about the potential for various tools. And then you get in, you go, okay, that excitement hits the reality of it takes a while to get these things configured or up and running. And then you go, okay, now I start to see.
Now we can lean into the areas where there really is value and it takes off. But you're never going to reach that initial site set of excitement because to some extent it was mixed with magic, with expectations about what could be, what was, what could happen. With these various tools,
Dave Dougherty: magical thinking is a very powerful placebo.
Yeah.
Ruthi Corcoran: It's,
It's
Dave Dougherty: wonderful if used correctly, but man, does that hurt when you suddenly smack into the wall of reality.
Alex Pokorny: The easy button, there's always this, especially during like website launches, there's always this funny step that people talk about of oh, then we launched the website, and my favorite reply always is that, how does that happen? Like step by step? And then you always get this pin drop because then it's oh wait, how does that happen?
I like everyone imagines there's this button, you just slap it and then suddenly oh, website's launched. We've done it. We hit the button like there's no button.
Dave Dougherty: Yeah. I had a leader once just, very dismissively say, okay, just go make those changes. And I'm like. That, no, we're talking about changing in like multiple languages, multiple countries.
Like right now, I can't just go do that. So how do you think this happens? And to your point, nothing I said, okay. Let me go draw you a process map so that you can understand all of the teams that are involved and how long this is actually going to take, given the way the systems are currently set up.
Then I can tell you when you'll have your answer by,
Alex Pokorny: You can totally see like it's reaction to our tech stack ideas. I quit this because it's like the marketing team gets so excited about some brand new thing and then it has a million questions and then everybody's like, why is it being so slow and such a stick in the mud?
Because they have to do the work and that's the only thing they get out of it is more work.
Ruthi Corcoran: But I. Experiences. There's such a, there's a cool thread here about. People's expectations about a project and what seems simple and then you get into the nuances.
Home Improvement Analogies
Ruthi Corcoran: And I think to just, I'll translate this into basic home improvement projects where you're like, oh, I'm just going to paint the room like, cool.
And you like, imagine yourself with a paintbrush and the paint can paint tank. But you've skipped over in your mind the 10 setup steps that need to happen, including two trips to Home Depot to get the thing and then get the thing that you forgot in the process. And it's a multi-day process, even though you thought oh yeah, one afternoon I'm just going to paint the room and we're going to be done with it.
And it reminds me of this thing that Alex has always said. Whenever you played a project, remember to triple the amount of time you think it's going to take. Because it is those hidden, unforeseen details. And humans are fantastic at just glossing right over those and just start imagining the almo, the end state of of the thing. And it's amazing that there's parallels between these DIY home projects. The tools we use at school with onboarding millennials or whoever the next generation is, and it's the same old song and dance. My friends,
Dave Dougherty: I would love to paint my studio. I have a wonderful idea of how it could look.
The thing that is keeping me from doing it is having to pull everything into the center of the room so that I can get access to all of the walls. And that's just a lot. That's just really heavy and I don't want to.
Alex Pokorny: Yeah. At least you've broken it down realistically to steps, yeah. Because it's so easy to be like, oh, we'll paint this room and this room and then we'll be done and it'll look great. And it's yes, that will look great. Wait. How are we going to do that? And at least you've broken it down enough
Dave Dougherty: to be like, no.
That's like the, all the classic, my wife jokes, right? It's oh, we're going to redesign the living room. It's who's this? We, who's this? We, because I'm going to have to pull the couches. I'm going to have to,
well see. You have a
Alex Pokorny: team, it's a project manager, and there's actual people who do the work. Absolutely. You're the people who do the work.
AI in the Workforce
Dave Dougherty: And what's interesting to me too is I've had a number of coffee talks recently just to keep the network alive and, say hi to people that I haven't seen, since summer was going on and everybody was away on vacation.
And the amount of stories that I've heard where some neighbors or some friends or their friend's parents or whoever got let go and they're going around saying, Hey, I took my job. That part's not necessarily interesting. The interesting part is the reaction of a lot of people going back and saying, no, you refuse to change.
Now granted that is a very specific sample of the people that I'm hanging out with, who would think to say those types of things. But I do think it's interesting to hear some of that pushback now where it's no, you can't just say that AI's taking your job. It's have you attempted to use AI for what it is you're doing?
Have you even thought of the different ways that you could be leveraging it to, state the case to keep you around. because I think once you start playing, it's not that hard to understand. Wow, okay. I have 3, 4, 5 different ways just initially that I could, play around with this.
So yeah. Any thoughts, comments, pushback on that or similar experiences with people or nothing?
Ruthi Corcoran: Whole host. I think you, you opened up a lot of space with just that interact set of interactions you've had, both in terms of people's reactions to their own experience, other people's reactions to how they experienced it.
And this is not a new phenomena. I'm sure it's going to be an omnipresent part of our world for the ne coming. Coming years in particular, as we go through the shift of the technical landscape for our type of jobs is changing quite significantly. And so the thing that comes to mind is just
it's hard, frankly. You
humans don't react super well to change. We like having the stability of knowing what we need to do, showing up, doing the thing, and then specializing in getting good in that particular space. We're not particularly I mean it varies human to human right, but we're not always so good at saying, okay, here's a totally different way to do the job that you've been doing for years and years.
And I wonder if. I don't know. I'm trying to figure out how to articulate this thought, but it's I suspect a lot of people, maybe they just don't, they don't want to have to try and innovate every single day at their job, right? Because they get, they got the rest of their life to live.
And the amount of mental energy it takes to show up and innovate every single day is taking away from other areas of your life. And I can see that being a challenge and. Those are my initial reactions, but I'm going to keep sitting on it because it's a dynamic that's like thinking it'd be continuous for all of us.
Alex Pokorny: Pulling it back to that generational kind of stereotyping of they don't know what to do. There's also teaching they haven't been taught. So creating an environment where you can help people transition. Into whatever the next version of their role is, right? And modernize their current role.
It takes effort and it takes work and it takes people around them being excited about it, like I've been around some. I'm not going to call 'em Luddites because they're in tech world, but at the same time they've been very resistant to ai. And then eventually we're like, you know what? It's all around me.
Everyone around me for coworkers is using it and I'll start going. And then they get into it and then there's, exactly the end. There's that little point of excitement where they start playing around with it and they're like, oh, this is actually fun. And then they get down to the reality of okay, how is this actually going to work in my day to day?
And they realize, it's going to be effort to integrate it. I heard a podcast with the CEO of Airtable and you're suggesting to any of his employees to take a full week off to just play around with AI tools.
The Role of Data in Marketing
Alex Pokorny: So to basically try to figure out how they can fit in their job and to try to move the company forward because they realize, especially like a SaaS company, you can't just throw some AI components on top right now, you really have to redo the company. So they reorganized their entire company to try to reorganize themselves around an AI fast moving basically portion to the company, and then a slower moving portion of the company to basically try to rationalize it and make it work.
Basically so that they can experiment and move a lot faster than those who are just trying to. To add an extra component then just bolted on with the promise of AI where really nothing's, 99% of it hasn't changed. So I think that's, that was an environment an example of they are pushing forward on that and everybody in that organization obviously is now has to push forward on that.
Ruthi Corcoran: There is something so important I think about that approach. And what I'm thinking about is, as I mentioned, like it's hard. It's, you got to show up and you got to change the way you work. But it's especially hard if that is an expectation on top of all the other things you're doing, right?
Yeah. Like your additional capacity, your brain power to be able to focus on that is just so short. You're. It's going to be much more difficult to be able to figure out novel ways of doing your job if it's a tack on. Maybe there's incremental stuff and you get lucky. And what it reminds me of is.
Ford electrifying their plants. Maybe I brought this up in the podcast before or not. So around the turn of the century a lot of, basically all of us industry went through this process of shifting from steam to electricity. And the process for doing this took about 10 years from when it was first like available and ready to be used to actually shifting all the capital equipment to be able to go and basically use electricity, power, your factory.
So Ford in particular, they shut down their entire factory. They had one here in St. Paul. And they shut it down. Stopped all car manufacturing. Can you imagine today one of the automobile manufacturers in this country just saying, Nope, we're going to shut down for seven months and we're not going to produce anything.
And they did this because they had to retool their entire production line to be electricity based versus steam based. And so I hear Alex here talk about this example where they said, everybody take a week off and go use AI and figure it out. That's almost like too short of time.
But it is the
equivalent idea of you need the time and the space to sit down, play around with it, figure, figure out what you could do, because you're essentially changing the fundamental technology on which you're doing things.
Dave Dougherty: I think it also depends on ages and stages, right? So that the trough of disillusionment and whatever else, like that same pattern shows up in the happiness studies across people's lives where it's okay, you hit your thirties and your happiness just starts tanking, and then it comes back up, towards the late forties.
And so if you're like the three of us, man, you're just in it,
And, yeah, if you're at the point where, all right, I just need five more years and then retirement maybe you can squeak that out. Maybe. I don't necessarily think so because it's hap AI's happening too fast for that. But man, if you're a Gen X leader or millennial in a leadership position or something like that, like you best be.
Learning this right now because it's going to change a lot of things. And that hit me a lot too. I was watching the HubSpot inbound live stream this week and there were a couple of takeaways. One, what they were offering as the new AI marketing methodology is very closely related to what we've talked about on this podcast.
So thank you for being so smart guys. And secondly. The way that they were talking about having a quote unquote smart CRM. Again, you need to have all of your data in one place. You need to have that MarTech stack set up to talk to one another so that you can create these a generative AI, tech workflows and have.
The data be filled out and useful, and then you need to have your teams standardizing that data and updating that data in a standardized way. And that's just, that is such a heavy lift when you may have 20, 30 years for some of these conglomerate, huge incumbent. Companies you have to go through all of that data and clean it up or figure out a way to put it in a format that the new tools can then use.
That is a huge lift. Of course, they're, it's going to be slower than, a lot of these startups. And I've been thinking about that a lot just because of, the cesspool of LinkedIn posts of I've got 80% of my workforce, handled by. AI bots now, it's that's cool for you if you're, a little solopreneur and you have no care in the world about your data privacy.
But for people who are in regulated environments or in, slightly bigger organizations, yeah, it has to be slower. It has to be more thoughtful. It has, if you're only selling in the us Yeah, go ahead. Be wild West. That's cool. You cross any kind of border, man, you got to think about that twice.
Emerging Roles in Tech
Alex Pokorny: I actually thought about that, of there's a new job coming of API, data cleanliness. Connection, maintainer administrator role. And it's a weird one because it's. Commonly would be heavily used by MarTech, but it's not really marketing job. It's a data analytics job, but it's not actually data analytics job.
It's it, but it's not it. And there's this job out there that basically is just that, like we have a giant email database. Great. How much of it is actually, valid email addresses? I don't know. You got to clean that up. Is that your email expert? Who's going to be going through that and cleaning throughout that process and doing a consistent basis.
But then again, if you're getting form fills on your leads. And you're capturing those and then now you're having Zapier automatically basically shoot out an enter introduction email based upon a territory map or something like that. Like now you've got sales data, salespeople connected to this thing, but is it going to a spam email address or not?
You're, you want to check in on that and make sure that, that thing's working. There's all these like little mini steps in between of the reality of. Just bots online and everything else, and things breaking also, like tracking suddenly not working and nobody noticing or Right.
A tag misfiring, so now you're getting double counts or something like that. There's all these little data things that are now, we are so dependent on. Yeah. Yet there's not really like a data expert. Person in the marketing world that basically has that kind of a standard role, which you can imagine I have a question about bills.
I'm going to go basically can look at, accounts payable and I'll talk to my people from the invoicing side of things like, but there's this, I don't know PPI question. It's whose job is it?
Dave Dougherty: The way you describe that makes me think of all of the SEO roles I've ever had. You're not quite marketing, you're not quite it, but you got to work with both of them.
And then you got to work with web development to launch the website. And if you don't have a copywriter, you're doing the copywriting. And if you do have a copywriter, you have to say, no, this is your word choice, this key word better be in the copy or you didn't do your job like, so this seems like a perfect position for, a more technical SEO who might have been hooking up APIs to keyword research tools and that kind.
That kind of stuff.
Ruthi Corcoran: I think it's a really cool point because I think SEO is a really good analogy where it is this middle ground and we've all experienced, it's very hard to define what it is we do. How does it add value, right? You have to really understand, here's how organic search adds value to the overall company because in some sense it's like SEO is a capability and it's the it, the.
There's not a name to it. To your point, Alex, of this type of role sits at the intersection of both different technologies from the API connections standpoint, different data flows, but also different teams who perhaps historically didn't need to talk to each other, but as our technologies and our data converge in terms of they need to talk to each other to create better experiences.
Now all of a sudden you need these sort of, these little hubs in between to be able to connect the dots. Because the coordination across all these different teams can become so complex. And somebody who cares about the product data over here maybe doesn't have the knowledge about the downstream effects, but they need to talk to each other if you're going to have a optimal syndication strategy or web strategy, et cetera, et cetera.
Alex Pokorny: That's such a
Ruthi Corcoran: cool observation.
Alex Pokorny: And to Dave's point, the legal side. Yeah, data privacy and legal, like the can spam law on top of, every removal of request out there that throws a wrench in every system and all the changes that are going on constantly in that area because Facebook has this endeavor that basically say like 2026 every ad campaign will be completely AI generated.
It's just the creative. Everything. Like you basically put in a goal in A URL and you're good to go and you're done. And it runs well. Cool. Except now that means that basically you are having a giant blind spot on your ad tech platform and where that data is being used, how that data is being used, all those terms and conditions and all the rest of that kind of stuff.
Because it's enough of an easy button that you sign up for it, you set it up, you go to the next thing, you sign up for it, you set it. But now you're not in the data, you're not actually going back to it, consistently like you're going to miss stuff. So there's all these alerts that you probably have to put on top of things, but on top of staying on top of the legal matters and brand changes and violations and every other kind of problem that comes up too, like complexity just grows.
Ruthi Corcoran: This connects su super well to the beginning of our conversation in the sense of. People's roles are changing with the technology shifts and it's, it may be hard to adapt or to see the opportunities and if some of the opportunities are things like this where new roles are emerging, but they're squishy.
No one has defined them yet. That's hard. That's uncomfortable. But then what AI is doing is it's making the lack of these types of functions even more obvious. Because if you don't have the nice data flows and you don't have the connections, you get all kinds of weird errors that show up to them.
People go, who do I talk to? There's not a natural person I talk to know how to do my job. I think I have a name though. I've come up with it just now. Steve. Not Steve, but I like where your head's at. Okay. So I used to work at Caribou Coffee. In fact I used to be a barista. Occasionally they'd stick me in front of the cash register, but if it was early morning, I was a little too grumpy and we didn't get many tips.
So they would stick me on the bar or if we had a five person team, which happened when it was very busy in the mornings there was, there used to be a role. Maybe there still is called the super glue. And the purpose of the super glue was to make sure everybody else on the team had what they need. So if the bar ran out of milk, you went in the back.
Gave them got them the milk. If the cash register folks were too busy to make the next set of drip coffee, you did that, you piped in if there needed to be some blender action going on. And they were making sure that everything was move, moving smoothly within the morning. I think that's what this role is.
They're the super glue. They're bringing these different themes together to make sure that the end product goes smoothly.
Dave Dougherty: So you and I both have that same experience. Ironically,
Ruthi Corcoran: no way.
Dave Dougherty: I had one 7:00 AM drive through experience and the manager forever refused to put me on.
So I was the milk getter, I was the cooler maker. I was the shot puller. Yeah. That was, that super glue was me. But I could schmooze the church crowd so we could get the tips on Sunday mornings after they were feeling generous. So that was, yeah.
I will tell you the actual story when we're not recording. Yeah. This is why we got to launch a
Alex Pokorny: Paton exclusive. I'm just saying.
Dave Dougherty: Exactly. Exactly. Yeah. Come hang out and hear all the nasty stories.
Yeah. It's interesting to see what will happen. I do think it is pretty squishy and the. The HubSpot thing was interesting because it was like, wow, okay, this makes so much sense for their target market, right? The small to medium sized businesses that maybe have one or two marketing people, or maybe they have a team, a small team.
The one thing that I haven't seen though, and maybe this will be a good topic for a next episode, is how do you involve your agency partners in these ecosystems? Because if you are building out these huge data sets, how much of that do you actually want to be proprietary? Or is any of it anymore Because you could just scrape it from, some tool like similar web or screaming Frog even.
Just even some of the capabilities you can get with those things like, yeah. We'll have a think on that. I think this was a good episode, so thank you for coming in and joining this topic, like subscribe and share. Also, thank you to everybody who signed up to the Pathways newsletter that continues to grow.
So come join a bun. A bunch of other marketers who are getting weekly newsletters deeper dives, if you will, on this. Looking forward to that and see you in the next episode.
